diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml new file mode 100644 index 0000000..a264d3c --- /dev/null +++ b/.github/workflows/test.yml @@ -0,0 +1,41 @@ +name: test + +on: + push: + branches: [main] + pull_request: + branches: [main] + +jobs: + test: + runs-on: ubuntu-latest + defaults: + run: + working-directory: server + strategy: + matrix: + node-version: [20, 22] + steps: + - uses: actions/checkout@v4 + + - name: Set up Node ${{ matrix.node-version }} + uses: actions/setup-node@v4 + with: + node-version: ${{ matrix.node-version }} + cache: npm + cache-dependency-path: server/package-lock.json + + - name: Install dependencies + run: npm ci + + - name: Type check + run: npm run typecheck + + - name: Build + run: npm run build + + - name: Unit tests + run: npm run test:unit + + - name: Flow tests + run: npm run test:flow diff --git a/CITATION.cff b/CITATION.cff index ff3db7e..0adcd7b 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -33,5 +33,5 @@ references: repository-code: 'https://github.com/joelparkerhenderson/decision-record/' abstract: >- The canonical concept, template, and teamwork model for decision - records — preserved in this fork at docs/upstream-canon.md and - templates/canonical.md. + records — preserved in this fork at docs/explanation/why-decision-records.md + and templates/canonical.md. diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 31a3c63..0853e98 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -24,7 +24,7 @@ This repo is the planning system itself. We deliberately stop at the handoff — ## Attribution -The conceptual core derives from Joel Parker Henderson's [canonical decision-record repo](https://github.com/joelparkerhenderson/decision-record). Preserve attribution to upstream in any rework of `docs/upstream-canon.md` or `templates/canonical.md`. +The conceptual core derives from Joel Parker Henderson's [canonical decision-record repo](https://github.com/joelparkerhenderson/decision-record). Preserve attribution to upstream in any rework of `docs/explanation/why-decision-records.md` or `templates/canonical.md`. ## License diff --git a/LICENSE b/LICENSE index 30603ec..04d47e0 100644 --- a/LICENSE +++ b/LICENSE @@ -22,8 +22,8 @@ SOFTWARE. --- -The preserved canonical material in `docs/upstream-canon.md` and the -canonical decision record template at `templates/canonical.md` derive from +The preserved canonical material in `docs/explanation/why-decision-records.md` +and the canonical decision record template at `templates/canonical.md` derive from the upstream work of Joel Parker Henderson: . That material should be attributed to its original author; see CITATION.cff. diff --git a/README.md b/README.md index 8a8a886..4a14326 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,7 @@ This repository is a Claude Code plugin + bundled MCP server. It runs inside a fresh or template repo, partners with a human and an AI agent, and produces an executable MVP plan: a scoped manifest, a set of accepted decision records, and a dependency-aware task graph. Output goes to Linear (primary) or stays as filesystem artifacts (fallback). -This project is a derivative of [Joel Parker Henderson's canonical decision-record repo](https://github.com/joelparkerhenderson/decision-record). The canonical explanation of what a DR is and why it matters is preserved at [`docs/upstream-canon.md`](docs/upstream-canon.md). What this fork adds is **enforcement**: workflows, tools, and a state machine that make DRs a non-skippable part of planning with an agentic system. +This project is a derivative of [Joel Parker Henderson's canonical decision-record repo](https://github.com/joelparkerhenderson/decision-record). The canonical explanation of what a DR is and why it matters is preserved at [`docs/explanation/why-decision-records.md`](docs/explanation/why-decision-records.md). What this fork adds is **enforcement**: workflows, tools, and a state machine that make DRs a non-skippable part of planning with an agentic system. ## What you get @@ -17,7 +17,16 @@ This project is a derivative of [Joel Parker Henderson's canonical decision-reco ## Status -Active development — first usable cut is in. The pipeline is functional end-to-end (intake → scope → decisions → tasks → handoff to filesystem or Linear). See [`docs/quickstart.md`](docs/quickstart.md) for the five-minute walkthrough, [`docs/usage.md`](docs/usage.md) for the full interaction model, and [`docs/architecture.md`](docs/architecture.md) for the data model. +Active development — first usable cut is in. The pipeline is functional end-to-end (intake → scope → decisions → tasks → handoff to filesystem or Linear). A standalone CLI (`decision-record`) ships alongside the Claude Code plugin and MCP server. + +## Documentation + +Docs follow the [Diátaxis](https://diataxis.fr) framework — start at [`docs/README.md`](docs/README.md) to orient. + +- **Brand new?** → [`docs/tutorials/your-first-plan.md`](docs/tutorials/your-first-plan.md) is a 15-minute end-to-end walkthrough. +- **How do I do X?** → [`docs/how-to/`](docs/how-to/) (install, run the CLI, configure providers, hand off to Linear, calibrate gates). +- **What's the exact spec?** → [`docs/reference/`](docs/reference/) (CLI flags, MCP tools, data model, gates). +- **Why is it built this way?** → [`docs/explanation/`](docs/explanation/) (design rationale, the five phases, why decision records). ## How it's structured @@ -58,18 +67,26 @@ npm install npm run build ``` -Then either link as a Claude Code plugin (symlink the repo into `~/.claude/plugins/decision-record/`) or run the MCP server standalone via `node /path/to/decision-record/server/dist/index.js`. Full instructions: [`docs/quickstart.md`](docs/quickstart.md). +Then either: +- Use the **standalone CLI**: `export OPENAI_API_KEY=… && node dist/cli.js --idea "your idea here"` +- Use the **Claude Code plugin**: symlink the repo into `~/.claude/plugins/decision-record/` and run `/plan` inside Claude Code. + +Full install instructions: [`docs/how-to/install.md`](docs/how-to/install.md). First-run walkthrough: [`docs/tutorials/your-first-plan.md`](docs/tutorials/your-first-plan.md). (A published marketplace release is on the roadmap.) +## Benchmarks + +We use a canonical prompt — an AI-driven roguelike POC — to spot regressions as the system evolves. See [`benchmarks/`](benchmarks/) for the prompt, expected output shape, and a `run.sh` to re-run it. + ## Contributing See [CONTRIBUTING.md](CONTRIBUTING.md). Issues and pull requests welcome. ## Acknowledgments -The conceptual core — what a decision record is, the canonical template structure, the teamwork model around DRs — is the work of [Joel Parker Henderson](https://joelparkerhenderson.com). See [`docs/upstream-canon.md`](docs/upstream-canon.md) for the preserved canonical material, and [CITATION.cff](CITATION.cff) for citation metadata. +The conceptual core — what a decision record is, the canonical template structure, the teamwork model around DRs — is the work of [Joel Parker Henderson](https://joelparkerhenderson.com). See [`docs/explanation/why-decision-records.md`](docs/explanation/why-decision-records.md) for the preserved canonical material, and [CITATION.cff](CITATION.cff) for citation metadata. ## License -[MIT](LICENSE) — for the code, schemas, and tooling in this repository. The preserved canonical content in `docs/upstream-canon.md` and the canonical template at `templates/canonical.md` derive from upstream and should be attributed to Joel Parker Henderson per CITATION.cff. +[MIT](LICENSE) — for the code, schemas, and tooling in this repository. The preserved canonical content in `docs/explanation/why-decision-records.md` and the canonical template at `templates/canonical.md` derive from upstream and should be attributed to Joel Parker Henderson per CITATION.cff. diff --git a/benchmarks/README.md b/benchmarks/README.md new file mode 100644 index 0000000..a5416ca --- /dev/null +++ b/benchmarks/README.md @@ -0,0 +1,32 @@ +# Benchmarks + +Canonical prompts we run against the decision-record planning pipeline to catch regressions as the system evolves. + +| Benchmark | Prompt | Effort | Purpose | +|---|---|---|---| +| [roguelike-ai-poc](roguelike-ai-poc/) | AI-driven roguelike where the agent plays the game | `poc` | Exercises all five pipeline phases on a small, well-bounded problem. The original dogfood case. | + +## How to run a benchmark + +```bash +cd benchmarks/ +./run.sh +``` + +Each benchmark has: + +- `prompt.md` — the exact idea, effort level, and what "good output" looks like +- `reference/` — a baseline artifact snapshot from a canonical run +- `run.sh` — one-shot runner that fires the CLI against a fresh tmp dir + +## What we look for when comparing runs + +Each benchmark's `prompt.md` defines its own success criteria. Generally: + +- Pipeline reaches `handed-off` +- Decision count and shape match expectations for the effort tier +- Tasks are vertical slices, every leaf has a decision ref, graph validates +- Render artifacts are emitted (Markdown + HTML) +- Event log is coherent + +These benchmarks are **not unit tests** — they're regression observability. Different runs will produce slightly different plans and that's by design. Treat the reference as "shape we expect," not "bytes we require." diff --git a/benchmarks/roguelike-ai-poc/prompt.md b/benchmarks/roguelike-ai-poc/prompt.md new file mode 100644 index 0000000..745bdb9 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/prompt.md @@ -0,0 +1,63 @@ +# Benchmark: roguelike-ai-poc + +This is the canonical benchmark for the decision-record planning pipeline. We re-run it as the system evolves to spot regressions in plan quality, gate behavior, agent prompts, and rendering. + +## The prompt + +**Idea (free-form):** + +> A minimal roguelike where the player primes an AI agent with a strategy, then the agent autonomously navigates a single ASCII-rendered room over a tick system until it wins the objective or dies. Goal: prove the agent-as-player concept with the smallest viable surface area. + +**Effort level:** `poc` + +## Invocation + +```bash +decision-record \ + --title "AI-driven roguelike POC" \ + --description "$(cat <<'EOF' +A minimal roguelike where the player primes an AI agent with a strategy, then the agent autonomously navigates a single ASCII-rendered room over a tick system until it wins the objective or dies. Goal: prove the agent-as-player concept with the smallest viable surface area. +EOF +)" \ + --effort poc \ + --cwd ./tmp-roguelike-bench \ + --yes +``` + +Or the one-shot wrapper: `./run.sh` (creates a fresh tmp dir, runs the CLI, prints where the artifacts landed). + +## What "good output" looks like + +A run is healthy if the produced plan: + +- **Pipeline reaches `handed-off`** — every gate passes, sign-offs recorded, project finalized. +- **3-5 significant decisions** are proposed and accepted — language, world representation, agent action contract, tick-loop control. (Not 1; not 12.) +- **5-8 vertical-slice tasks** — bootstrap → world → renderer → agent client → action handlers → game loop → CLI entry. Every leaf ≤ 16h (poc cap). Every task references at least one accepted DR. +- **The seed library is consulted** for at least the language decision (`dr_seed_search` + `dr_seed_load` on `language-choice`). +- **Graph validates clean** — no cycles, no orphan deps, no missing decision refs. +- **Artifacts emitted** — `dr/project.json`, `dr/decisions/*.json`, `dr/tasks/*.json`, rendered `.md` siblings, `dr/index.html`. `.dr/events.jsonl` contains a coherent audit trail. + +## Reference snapshot + +`./reference/` holds the artifacts from the canonical run produced by hand-driving the MCP tools (2026-05-16, the dogfood test that originally produced this benchmark). Treat it as a "this is what good looks like" baseline, not a strict equality target — different agent runs will pick slightly different positions, phrasing, and task decomposition, and that's fine. + +When comparing a new run against `./reference/`: + +- **Same final phase, gate decisions, event mix** → no regression. +- **More/fewer decisions or tasks** → check whether the new run is denser/sparser appropriately or whether the agent over- or under-decomposed. +- **Different selected positions** → fine if defensible; concerning if the argument is weaker. +- **Missing seed usage** → bug or prompt drift; the agent should reach for `language-choice` here. +- **Tasks without decision refs** → regression. Every task must link to a DR. +- **Validation failures** → regression. The graph must validate. + +## What this benchmark exercises + +| Surface | Coverage | +|---|---| +| Phase machine | All five transitions: intake → scoping → deciding → decomposing → handing-off → handed-off | +| Seed library | At least one `dr_seed_load` (language-choice) | +| Decision lifecycle | propose → update with position + argument → accept (no review under poc preset) | +| Task graph | Multi-node dependency chain with decision_refs | +| Gates | `min_tasks=3`, `max_task_estimate_hours=16`, `require_human_signoff_phases=['handing-off']` | +| Render | Markdown per record + static HTML index | +| Handoff | Filesystem path (Linear path is exercised by separate live test) | diff --git a/benchmarks/roguelike-ai-poc/reference/decisions/0001-choose-the-implementation-language.json b/benchmarks/roguelike-ai-poc/reference/decisions/0001-choose-the-implementation-language.json new file mode 100644 index 0000000..f07d744 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/decisions/0001-choose-the-implementation-language.json @@ -0,0 +1,115 @@ +{ + "id": "0001-choose-the-implementation-language", + "number": 1, + "slug": "choose-the-implementation-language", + "title": "Choose the implementation language", + "status": "accepted", + "template_variant": "architecture", + "created_at": "2026-05-17T04:13:38.681Z", + "updated_at": "2026-05-17T04:13:38.685Z", + "summary": "Decide the primary implementation language for the project.", + "issue": "Every other foundational decision (runtime, package manager, framework choices, testing tools) flows from the language choice. Picking this early and explicitly avoids drift.", + "assumptions": [ + "Team has existing language strengths to lean on.", + "Project lifespan is long enough that hiring and onboarding matter.", + "Ecosystem maturity matters for the project's domain." + ], + "constraints": [ + "Team's current expertise.", + "Target runtime environments (browser, server, native, embedded).", + "Performance and memory budgets.", + "Licensing or compliance restrictions on language ecosystems." + ], + "positions": [ + { + "title": "TypeScript", + "description": "Strongly typed JavaScript. Best for full-stack web work, ubiquitous tooling.", + "pros": [ + "Ubiquitous in web", + "Strong types catch errors early", + "Massive ecosystem", + "Frontend/backend code sharing" + ], + "cons": [ + "Build step overhead", + "Type system can be over-engineered", + "Slower than native languages for hot paths" + ], + "links": [] + }, + { + "title": "Python", + "description": "Dynamic, batteries-included. Best for data work, scripting, ML, fast prototypes.", + "pros": [ + "Excellent ML/data ecosystem", + "Fast to write", + "Readable", + "Huge stdlib" + ], + "cons": [ + "Slow runtime without C extensions", + "GIL limits concurrency", + "Dynamic typing → runtime errors" + ], + "links": [] + }, + { + "title": "Go", + "description": "Statically typed, compiled, built for concurrent services.", + "pros": [ + "Simple language", + "Single binary deployment", + "Strong concurrency primitives", + "Fast compile times" + ], + "cons": [ + "Generics still maturing", + "Verbose error handling", + "Less rich third-party ecosystem than JS/Python" + ], + "links": [] + }, + { + "title": "Rust", + "description": "Memory-safe systems language. Best for performance-critical or systems work.", + "pros": [ + "No GC, predictable performance", + "Memory safety", + "Excellent tooling (cargo)", + "Strong types" + ], + "cons": [ + "Steep learning curve", + "Slower to ship initial features", + "Compile times can be long" + ], + "links": [] + } + ], + "opinions": [], + "argument": "Python is fastest to write for a single-script game-loop POC. The OpenAI SDK + a tiny terminal renderer fit naturally; no build step or transpile loop slows iteration. Team is comfortable with Python and the project never needs to leave a single repo.", + "selected_position": "Python", + "implications": [ + "Use the official openai Python SDK for agent calls.", + "Single-file or small-module layout; no package manager beyond pip/uv.", + "Pin to Python 3.11+ for ergonomic match-statement parsing of agent actions." + ], + "depends_on": [], + "related_decisions": [], + "related_artifacts": [], + "review": [], + "sign_off": { + "by": "human", + "actor": "kj", + "at": "2026-05-17T04:13:38.685Z", + "notes": "poc preset, no review required" + }, + "seed_origin": "language-choice", + "tags": [ + "foundation", + "poc", + "foundation", + "architecture", + "stack" + ] +} diff --git a/benchmarks/roguelike-ai-poc/reference/decisions/0001-choose-the-implementation-language.md b/benchmarks/roguelike-ai-poc/reference/decisions/0001-choose-the-implementation-language.md new file mode 100644 index 0000000..8a3a4b3 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/decisions/0001-choose-the-implementation-language.md @@ -0,0 +1,120 @@ +# 0001-choose-the-implementation-language — Choose the implementation language + +| Field | Value | +| --- | --- | +| Status | `accepted` | +| Template | `architecture` | +| Updated | 2026-05-17T04:13:38.685Z | +| Selected | **Python** | +| Depends on | _(none)_ | + +## Summary + +Decide the primary implementation language for the project. + +## Issue + +Every other foundational decision (runtime, package manager, framework choices, testing tools) flows from the language choice. Picking this early and explicitly avoids drift. + +## Assumptions + +- Team has existing language strengths to lean on. +- Project lifespan is long enough that hiring and onboarding matter. +- Ecosystem maturity matters for the project's domain. + +## Constraints + +- Team's current expertise. +- Target runtime environments (browser, server, native, embedded). +- Performance and memory budgets. +- Licensing or compliance restrictions on language ecosystems. + +## Positions + +### TypeScript + +Strongly typed JavaScript. Best for full-stack web work, ubiquitous tooling. + +**Pros** + +- Ubiquitous in web +- Strong types catch errors early +- Massive ecosystem +- Frontend/backend code sharing + +**Cons** + +- Build step overhead +- Type system can be over-engineered +- Slower than native languages for hot paths + +### Python ✅ + +Dynamic, batteries-included. Best for data work, scripting, ML, fast prototypes. + +**Pros** + +- Excellent ML/data ecosystem +- Fast to write +- Readable +- Huge stdlib + +**Cons** + +- Slow runtime without C extensions +- GIL limits concurrency +- Dynamic typing → runtime errors + +### Go + +Statically typed, compiled, built for concurrent services. + +**Pros** + +- Simple language +- Single binary deployment +- Strong concurrency primitives +- Fast compile times + +**Cons** + +- Generics still maturing +- Verbose error handling +- Less rich third-party ecosystem than JS/Python + +### Rust + +Memory-safe systems language. Best for performance-critical or systems work. + +**Pros** + +- No GC, predictable performance +- Memory safety +- Excellent tooling (cargo) +- Strong types + +**Cons** + +- Steep learning curve +- Slower to ship initial features +- Compile times can be long + +## Argument + +Python is fastest to write for a single-script game-loop POC. The OpenAI SDK + a tiny terminal renderer fit naturally; no build step or transpile loop slows iteration. Team is comfortable with Python and the project never needs to leave a single repo. + +## Implications + +- Use the official openai Python SDK for agent calls. +- Single-file or small-module layout; no package manager beyond pip/uv. +- Pin to Python 3.11+ for ergonomic match-statement parsing of agent actions. + +## Sign-off + +- **By:** kj (human) +- **At:** 2026-05-17T04:13:38.685Z +- **Notes:** poc preset, no review required + +--- + +_Instantiated from seed: `language-choice`_ diff --git a/benchmarks/roguelike-ai-poc/reference/decisions/0002-define-the-world-representation-and-renderer.json b/benchmarks/roguelike-ai-poc/reference/decisions/0002-define-the-world-representation-and-renderer.json new file mode 100644 index 0000000..7afe41a --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/decisions/0002-define-the-world-representation-and-renderer.json @@ -0,0 +1,85 @@ +{ + "id": "0002-define-the-world-representation-and-renderer", + "number": 2, + "slug": "define-the-world-representation-and-renderer", + "title": "Define the world representation and renderer", + "status": "accepted", + "template_variant": "data-model", + "created_at": "2026-05-17T04:13:38.686Z", + "updated_at": "2026-05-17T04:13:38.688Z", + "summary": "How the room is stored in memory and rendered to the terminal each tick.", + "issue": "The world is small (one 10×10 room) but the representation must support: easy frame rendering, fast collision/hazard checks, and a stable serialization that the agent can read on each tick. Pick a model now so the action handlers and renderer can converge.", + "assumptions": [ + "10×10 fixed grid", + "Single player entity", + "Static tiles set at startup", + "Frame fits in a single terminal redraw" + ], + "constraints": [ + "Frame must be readable both by humans and the LLM", + "No external graphics libraries" + ], + "positions": [ + { + "title": "Nested list of chars", + "description": "world: list[list[str]] indexed by [y][x]. Player position stored separately.", + "pros": [ + "Simplest possible", + "Trivial to mutate", + "Renders by row-join" + ], + "cons": [ + "No type safety on tile semantics", + "Have to scan grid for entity positions" + ], + "links": [] + }, + { + "title": "Tile-grid + entity dict", + "description": "static_tiles: list[list[str]] for walls/floor/hazard/exit; entities: dict[id, {pos, hp, glyph}] overlaid at render time.", + "pros": [ + "Separates static map from dynamic state", + "Easy to add entities later if needed", + "Clean serialization to JSON" + ], + "cons": [ + "Two structures to keep consistent", + "Slightly more code" + ], + "links": [] + }, + { + "title": "Single 2D numpy array + glyph table", + "description": "Each cell is an int; render by mapping ints to glyphs.", + "pros": [ + "Compact", + "Fast", + "Numpy is familiar" + ], + "cons": [ + "Numpy is overkill for 10×10", + "Adds a dep we do not otherwise need", + "Less Pythonic for tiny data" + ], + "links": [] + } + ], + "opinions": [], + "argument": "Static map + entity overlay is the simplest model that survives the day-2 question can we add a second entity? without a rewrite. It serializes naturally to JSON for the LLM payload and keeps render code in one row-join.", + "selected_position": "Tile-grid + entity dict", + "implications": [ + "Tile glyphs: # wall, . floor, X hazard, > exit; entities overlay (@ for player).", + "Each tick the renderer composes static_tiles + entity glyphs at their positions.", + "JSON state sent to the agent: { frame: [], hp, tick, exit_pos, player_pos }." + ], + "depends_on": [], + "related_decisions": [], + "related_artifacts": [], + "review": [], + "sign_off": { + "by": "human", + "actor": "kj", + "at": "2026-05-17T04:13:38.688Z" + }, + "tags": [] +} diff --git a/benchmarks/roguelike-ai-poc/reference/decisions/0002-define-the-world-representation-and-renderer.md b/benchmarks/roguelike-ai-poc/reference/decisions/0002-define-the-world-representation-and-renderer.md new file mode 100644 index 0000000..dfbf675 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/decisions/0002-define-the-world-representation-and-renderer.md @@ -0,0 +1,92 @@ +# 0002-define-the-world-representation-and-renderer — Define the world representation and renderer + +| Field | Value | +| --- | --- | +| Status | `accepted` | +| Template | `data-model` | +| Updated | 2026-05-17T04:13:38.688Z | +| Selected | **Tile-grid + entity dict** | +| Depends on | _(none)_ | + +## Summary + +How the room is stored in memory and rendered to the terminal each tick. + +## Issue + +The world is small (one 10×10 room) but the representation must support: easy frame rendering, fast collision/hazard checks, and a stable serialization that the agent can read on each tick. Pick a model now so the action handlers and renderer can converge. + +## Assumptions + +- 10×10 fixed grid +- Single player entity +- Static tiles set at startup +- Frame fits in a single terminal redraw + +## Constraints + +- Frame must be readable both by humans and the LLM +- No external graphics libraries + +## Positions + +### Nested list of chars + +world: list[list[str]] indexed by [y][x]. Player position stored separately. + +**Pros** + +- Simplest possible +- Trivial to mutate +- Renders by row-join + +**Cons** + +- No type safety on tile semantics +- Have to scan grid for entity positions + +### Tile-grid + entity dict ✅ + +static_tiles: list[list[str]] for walls/floor/hazard/exit; entities: dict[id, {pos, hp, glyph}] overlaid at render time. + +**Pros** + +- Separates static map from dynamic state +- Easy to add entities later if needed +- Clean serialization to JSON + +**Cons** + +- Two structures to keep consistent +- Slightly more code + +### Single 2D numpy array + glyph table + +Each cell is an int; render by mapping ints to glyphs. + +**Pros** + +- Compact +- Fast +- Numpy is familiar + +**Cons** + +- Numpy is overkill for 10×10 +- Adds a dep we do not otherwise need +- Less Pythonic for tiny data + +## Argument + +Static map + entity overlay is the simplest model that survives the day-2 question can we add a second entity? without a rewrite. It serializes naturally to JSON for the LLM payload and keeps render code in one row-join. + +## Implications + +- Tile glyphs: # wall, . floor, X hazard, > exit; entities overlay (@ for player). +- Each tick the renderer composes static_tiles + entity glyphs at their positions. +- JSON state sent to the agent: { frame: [], hp, tick, exit_pos, player_pos }. + +## Sign-off + +- **By:** kj (human) +- **At:** 2026-05-17T04:13:38.688Z diff --git a/benchmarks/roguelike-ai-poc/reference/decisions/0003-define-the-agent-action-contract.json b/benchmarks/roguelike-ai-poc/reference/decisions/0003-define-the-agent-action-contract.json new file mode 100644 index 0000000..0e98040 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/decisions/0003-define-the-agent-action-contract.json @@ -0,0 +1,83 @@ +{ + "id": "0003-define-the-agent-action-contract", + "number": 3, + "slug": "define-the-agent-action-contract", + "title": "Define the agent action contract", + "status": "accepted", + "template_variant": "architecture", + "created_at": "2026-05-17T04:13:38.689Z", + "updated_at": "2026-05-17T04:13:38.690Z", + "summary": "How the LLM receives the world state per tick and how it returns the chosen action.", + "issue": "The agent must produce a structured, validated action every tick. We need the protocol pinned so the game loop never has to guess what the agent meant.", + "assumptions": [ + "OpenAI-compatible API is the LLM transport", + "Strategy prompt is supplied once at startup", + "Per-tick latency budget ~2-5s is acceptable" + ], + "constraints": [ + "Action set is small (move N/S/E/W + noop)", + "Agent must not stall the game with malformed output", + "Must be debuggable from logs" + ], + "positions": [ + { + "title": "Plain-text response parsing", + "description": "Agent returns N/S/E/W/noop as plain text; we parse first token.", + "pros": [ + "Lowest token cost", + "Works with any model" + ], + "cons": [ + "Brittle to extra punctuation/prose", + "No reasoning surface", + "Hard to audit why" + ], + "links": [] + }, + { + "title": "Tool-call (function calling) with one tool: do_action(direction)", + "description": "Define a single OpenAI tool; agent invokes it once per tick with a strict enum direction.", + "pros": [ + "Schema-validated", + "Free reasoning text alongside the call", + "Easy to extend with new actions later" + ], + "cons": [ + "Slightly more tokens per call", + "Requires a model that supports function calling" + ], + "links": [] + }, + { + "title": "JSON-only response with output_config", + "description": "Force agent to emit {\"action\":\"N\",\"reason\":\"…\"} via structured outputs.", + "pros": [ + "Schema-validated", + "Reasoning captured in same payload" + ], + "cons": [ + "Some providers do not honor strict mode", + "Slightly more setup than tool-call" + ], + "links": [] + } + ], + "opinions": [], + "argument": "Tool-calling is the cleanest contract: the model gets free-form reasoning in `content` AND a strict-enum action in `tool_calls`. We can log both, and extending to new actions later is just adding enum values. Plain-text parsing trades 100 tokens of savings for a constant brittleness tax.", + "selected_position": "Tool-call (function calling) with one tool: do_action(direction)", + "implications": [ + "Define tool `do_action` with input_schema requiring `direction` in {N,S,E,W,noop}.", + "Use tool_choice=\"required\" each tick to force a call.", + "Log the assistant message text (the reasoning) alongside the chosen direction for replay/debug." + ], + "depends_on": [], + "related_decisions": [], + "related_artifacts": [], + "review": [], + "sign_off": { + "by": "human", + "actor": "kj", + "at": "2026-05-17T04:13:38.690Z" + }, + "tags": [] +} diff --git a/benchmarks/roguelike-ai-poc/reference/decisions/0003-define-the-agent-action-contract.md b/benchmarks/roguelike-ai-poc/reference/decisions/0003-define-the-agent-action-contract.md new file mode 100644 index 0000000..1bd6e3a --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/decisions/0003-define-the-agent-action-contract.md @@ -0,0 +1,90 @@ +# 0003-define-the-agent-action-contract — Define the agent action contract + +| Field | Value | +| --- | --- | +| Status | `accepted` | +| Template | `architecture` | +| Updated | 2026-05-17T04:13:38.690Z | +| Selected | **Tool-call (function calling) with one tool: do_action(direction)** | +| Depends on | _(none)_ | + +## Summary + +How the LLM receives the world state per tick and how it returns the chosen action. + +## Issue + +The agent must produce a structured, validated action every tick. We need the protocol pinned so the game loop never has to guess what the agent meant. + +## Assumptions + +- OpenAI-compatible API is the LLM transport +- Strategy prompt is supplied once at startup +- Per-tick latency budget ~2-5s is acceptable + +## Constraints + +- Action set is small (move N/S/E/W + noop) +- Agent must not stall the game with malformed output +- Must be debuggable from logs + +## Positions + +### Plain-text response parsing + +Agent returns N/S/E/W/noop as plain text; we parse first token. + +**Pros** + +- Lowest token cost +- Works with any model + +**Cons** + +- Brittle to extra punctuation/prose +- No reasoning surface +- Hard to audit why + +### Tool-call (function calling) with one tool: do_action(direction) ✅ + +Define a single OpenAI tool; agent invokes it once per tick with a strict enum direction. + +**Pros** + +- Schema-validated +- Free reasoning text alongside the call +- Easy to extend with new actions later + +**Cons** + +- Slightly more tokens per call +- Requires a model that supports function calling + +### JSON-only response with output_config + +Force agent to emit {"action":"N","reason":"…"} via structured outputs. + +**Pros** + +- Schema-validated +- Reasoning captured in same payload + +**Cons** + +- Some providers do not honor strict mode +- Slightly more setup than tool-call + +## Argument + +Tool-calling is the cleanest contract: the model gets free-form reasoning in `content` AND a strict-enum action in `tool_calls`. We can log both, and extending to new actions later is just adding enum values. Plain-text parsing trades 100 tokens of savings for a constant brittleness tax. + +## Implications + +- Define tool `do_action` with input_schema requiring `direction` in {N,S,E,W,noop}. +- Use tool_choice="required" each tick to force a call. +- Log the assistant message text (the reasoning) alongside the chosen direction for replay/debug. + +## Sign-off + +- **By:** kj (human) +- **At:** 2026-05-17T04:13:38.690Z diff --git a/benchmarks/roguelike-ai-poc/reference/decisions/0004-define-the-tick-loop-and-termination-conditions.json b/benchmarks/roguelike-ai-poc/reference/decisions/0004-define-the-tick-loop-and-termination-conditions.json new file mode 100644 index 0000000..4f6becd --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/decisions/0004-define-the-tick-loop-and-termination-conditions.json @@ -0,0 +1,68 @@ +{ + "id": "0004-define-the-tick-loop-and-termination-conditions", + "number": 4, + "slug": "define-the-tick-loop-and-termination-conditions", + "title": "Define the tick loop and termination conditions", + "status": "accepted", + "template_variant": "architecture", + "created_at": "2026-05-17T04:13:38.691Z", + "updated_at": "2026-05-17T04:13:38.692Z", + "summary": "How the game advances tick by tick, when it stops, and how the user observes it.", + "issue": "With an LLM in the loop, each tick is slow (~2-5s). We need a predictable loop with hard stops so the POC always terminates and is always watchable.", + "assumptions": [ + "One-player synchronous game", + "User runs the script in a terminal and watches frames", + "LLM calls happen on the same thread" + ], + "constraints": [ + "Must terminate on win, death, or step limit", + "Frame must visibly update each tick", + "Must not deadlock on a stuck agent" + ], + "positions": [ + { + "title": "Synchronous loop with step cap", + "description": "while not terminal: render → ask agent → apply → check win/death. Hard cap at N steps (e.g., 50).", + "pros": [ + "Simplest mental model", + "Easy to log", + "Predictable termination" + ], + "cons": [ + "UI freezes during LLM call (acceptable for POC)" + ], + "links": [] + }, + { + "title": "Async loop with timeout per tick", + "description": "Wrap each agent call in a 10s timeout; on timeout, treat as noop.", + "pros": [ + "Robust to slow API", + "Game keeps moving" + ], + "cons": [ + "More complex", + "Asyncio inside a CLI script is heavier than warranted" + ], + "links": [] + } + ], + "opinions": [], + "argument": "For a single-window terminal demo, synchronous is fine. Adding asyncio doubles the code size for no demo-visible benefit. The step cap protects against an agent that wanders forever and ensures every run terminates.", + "selected_position": "Synchronous loop with step cap", + "implications": [ + "Step cap = 50; on cap, exit with status \"timeout\" and final HP.", + "Use time.sleep(0.05) after each render so the user can see the frames advance.", + "Loop logs each tick to stdout: frame, action, reasoning, hp, tick#." + ], + "depends_on": [], + "related_decisions": [], + "related_artifacts": [], + "review": [], + "sign_off": { + "by": "human", + "actor": "kj", + "at": "2026-05-17T04:13:38.692Z" + }, + "tags": [] +} diff --git a/benchmarks/roguelike-ai-poc/reference/decisions/0004-define-the-tick-loop-and-termination-conditions.md b/benchmarks/roguelike-ai-poc/reference/decisions/0004-define-the-tick-loop-and-termination-conditions.md new file mode 100644 index 0000000..0d83a25 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/decisions/0004-define-the-tick-loop-and-termination-conditions.md @@ -0,0 +1,74 @@ +# 0004-define-the-tick-loop-and-termination-conditions — Define the tick loop and termination conditions + +| Field | Value | +| --- | --- | +| Status | `accepted` | +| Template | `architecture` | +| Updated | 2026-05-17T04:13:38.692Z | +| Selected | **Synchronous loop with step cap** | +| Depends on | _(none)_ | + +## Summary + +How the game advances tick by tick, when it stops, and how the user observes it. + +## Issue + +With an LLM in the loop, each tick is slow (~2-5s). We need a predictable loop with hard stops so the POC always terminates and is always watchable. + +## Assumptions + +- One-player synchronous game +- User runs the script in a terminal and watches frames +- LLM calls happen on the same thread + +## Constraints + +- Must terminate on win, death, or step limit +- Frame must visibly update each tick +- Must not deadlock on a stuck agent + +## Positions + +### Synchronous loop with step cap ✅ + +while not terminal: render → ask agent → apply → check win/death. Hard cap at N steps (e.g., 50). + +**Pros** + +- Simplest mental model +- Easy to log +- Predictable termination + +**Cons** + +- UI freezes during LLM call (acceptable for POC) + +### Async loop with timeout per tick + +Wrap each agent call in a 10s timeout; on timeout, treat as noop. + +**Pros** + +- Robust to slow API +- Game keeps moving + +**Cons** + +- More complex +- Asyncio inside a CLI script is heavier than warranted + +## Argument + +For a single-window terminal demo, synchronous is fine. Adding asyncio doubles the code size for no demo-visible benefit. The step cap protects against an agent that wanders forever and ensures every run terminates. + +## Implications + +- Step cap = 50; on cap, exit with status "timeout" and final HP. +- Use time.sleep(0.05) after each render so the user can see the frames advance. +- Loop logs each tick to stdout: frame, action, reasoning, hp, tick#. + +## Sign-off + +- **By:** kj (human) +- **At:** 2026-05-17T04:13:38.692Z diff --git a/benchmarks/roguelike-ai-poc/reference/events.jsonl b/benchmarks/roguelike-ai-poc/reference/events.jsonl new file mode 100644 index 0000000..42ab62f --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/events.jsonl @@ -0,0 +1,33 @@ +{"at":"2026-05-17T04:12:02.030Z","actor":"agent","kind":"project_initialized","entity_kind":"project","entity_id":"ai-driven-roguelike-poc","payload":{"effort_level":"poc"}} +{"at":"2026-05-17T04:12:40.988Z","actor":"agent","kind":"phase_advanced","entity_kind":"phase","entity_id":"scoping","payload":{"from":"intake","to":"scoping"}} +{"at":"2026-05-17T04:12:40.991Z","actor":"agent","kind":"scope_updated","entity_kind":"project","entity_id":"ai-driven-roguelike-poc","payload":{"scope":{"in_scope":["A 10×10 ASCII-rendered single room with walls (#), floor (.), player (@), exit (>), and a hazard tile (X)","Tick-based game loop: each tick prints the frame, then queries the agent for one action","A small action vocabulary: move N/S/E/W and noop","Player has HP; stepping on hazard removes HP; reaching exit = win, HP=0 = death","Strategy prompt provided once at startup, fed to the agent as system prompt for every tick","LLM agent receives current frame + HP + tick number, returns a single action"],"out_of_scope":["Multiple rooms, dungeon generation, procedural levels","Combat with enemies, NPCs, monsters","Inventory, items, equipment","Save/load, persistence","Visual UI beyond ASCII to terminal","Multiplayer, networking","Self-improving agent loops or RL training"],"success_criteria":["A user can run a single command, 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graph validates clean."}} +{"at":"2026-05-17T04:14:44.523Z","actor":"human","actor_name":"kj","kind":"sign_off_recorded","entity_kind":"phase","entity_id":"handing-off"} +{"at":"2026-05-17T04:14:44.538Z","actor":"agent","kind":"render_run","payload":{"decisions":4,"tasks":7}} +{"at":"2026-05-17T04:14:44.540Z","actor":"human","actor_name":"kj","kind":"export_started","entity_kind":"project","entity_id":"ai-driven-roguelike-poc","payload":{"target":"filesystem"}} +{"at":"2026-05-17T04:14:44.540Z","actor":"human","actor_name":"kj","kind":"export_completed","entity_kind":"project","entity_id":"ai-driven-roguelike-poc","payload":{"target":"filesystem","issue_count":7,"document_count":4}} +{"at":"2026-05-17T04:14:44.544Z","actor":"agent","kind":"render_run","payload":{"decisions":4,"tasks":7}} diff --git a/benchmarks/roguelike-ai-poc/reference/index.html b/benchmarks/roguelike-ai-poc/reference/index.html new file mode 100644 index 0000000..75276fc --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/index.html @@ -0,0 +1,231 @@ + + + + + +AI-driven roguelike POC — Decision Record + + + +
+ +
+
ai-driven-roguelike-poc
+

AI-driven roguelike POC

+
+ Phase: handed-off + Effort: poc + Updated: 2026-05-17T04:14:44.540Z + Decisions: 4 (4 accepted) + Tasks: 7 (0 done) +
+
+ +

A minimal roguelike where the player primes an AI agent with a strategy, then the agent autonomously navigates a single ASCII-rendered room over a tick system until it wins the objective or dies. Goal: prove the agent-as-player concept with the smallest viable surface area.

+ +
+

Scope

+
+
+

In scope

+
  • A 10×10 ASCII-rendered single room with walls (#), floor (.), player (@), exit (>), and a hazard tile (X)
  • Tick-based game loop: each tick prints the frame, then queries the agent for one action
  • A small action vocabulary: move N/S/E/W and noop
  • Player has HP; stepping on hazard removes HP; reaching exit = win, HP=0 = death
  • Strategy prompt provided once at startup, fed to the agent as system prompt for every tick
  • LLM agent receives current frame + HP + tick number, returns a single action
+
+

Success criteria

+
  • A user can run a single command, supply a strategy prompt, and watch the agent play until win or death
  • Win and death paths both observed in manual playtests
  • Different strategy prompts produce visibly different agent behavior
  • End-to-end run completes in under 60 seconds wall time on a typical OpenAI API call
+
+

Out of scope

+
  • Multiple rooms, dungeon generation, procedural levels
  • Combat with enemies, NPCs, monsters
  • Inventory, items, equipment
  • Save/load, persistence
  • Visual UI beyond ASCII to terminal
  • Multiplayer, networking
  • Self-improving agent loops or RL training
+
+

Nice to have

+
  • Configurable room layout from a text file
  • Replay log written to disk for post-hoc inspection
  • A few preset strategy prompts to demo (cautious, greedy, exploratory)
+
+
+
+
+

Handed off

+
+ Target: filesystem + At: 2026-05-17T04:14:44.540Z + + +
+
+ +

Decisions

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
IDTitleStatusSelectedDepends on
0001-choose-the-implementation-languageChoose the implementation language [architecture]acceptedPython—
0002-define-the-world-representation-and-rendererDefine the world representation and renderer [data-model]acceptedTile-grid + entity dict—
0003-define-the-agent-action-contractDefine the agent action contract [architecture]acceptedTool-call (function calling) with one tool: do_action(direction)—
0004-define-the-tick-loop-and-termination-conditionsDefine the tick loop and termination conditions [architecture]acceptedSynchronous loop with step cap—
+ +

Task graph

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
IDTitleStatusPriEstimateDepends onDecision refs
T0001-bootstrap-repositoryBootstrap repositoryreadyp01h—0001-choose-the-implementation-language
T0002-implement-world-module-tile-grid-entity-dictImplement world module (tile grid + entity dict)openp02hT0001-bootstrap-repository0002-define-the-world-representation-and-renderer
T0003-implement-frame-rendererImplement frame rendereropenp01hT0002-implement-world-module-tile-grid-entity-dict0002-define-the-world-representation-and-renderer
T0004-implement-openai-agent-clientImplement OpenAI agent clientopenp02hT0001-bootstrap-repository0003-define-the-agent-action-contract
T0005-implement-action-handlers-and-termination-checksImplement action handlers and termination checksopenp01hT0002-implement-world-module-tile-grid-entity-dict0002-define-the-world-representation-and-renderer
T0006-implement-the-tick-based-game-loopImplement the tick-based game loopopenp02hT0003-implement-frame-renderer T0004-implement-openai-agent-client T0005-implement-action-handlers-and-termination-checks0004-define-the-tick-loop-and-termination-conditions 0002-define-the-world-representation-and-renderer
T0007-implement-cli-entry-scriptImplement CLI entry scriptopenp01hT0006-implement-the-tick-based-game-loop0001-choose-the-implementation-language 0004-define-the-tick-loop-and-termination-conditions
+ +
+ Generated by decision-record · + Last render: 2026-05-17T04:14:44.544Z +
+ +
+ + \ No newline at end of file diff --git a/benchmarks/roguelike-ai-poc/reference/project.json b/benchmarks/roguelike-ai-poc/reference/project.json new file mode 100644 index 0000000..3b4c9fb --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/project.json @@ -0,0 +1,64 @@ +{ + "id": "ai-driven-roguelike-poc", + "title": "AI-driven roguelike POC", + "description": "A minimal roguelike where the player primes an AI agent with a strategy, then the agent autonomously navigates a single ASCII-rendered room over a tick system until it wins the objective or dies. Goal: prove the agent-as-player concept with the smallest viable surface area.", + "created_at": "2026-05-17T04:12:02.030Z", + "updated_at": "2026-05-17T04:14:44.540Z", + "effort_level": "poc", + "status": "handed-off", + "scope": { + "in_scope": [ + "A 10×10 ASCII-rendered single room with walls (#), floor (.), player (@), exit (>), and a hazard tile (X)", + "Tick-based game loop: each tick prints the frame, then queries the agent for one action", + "A small action vocabulary: move N/S/E/W and noop", + "Player has HP; stepping on hazard removes HP; reaching exit = win, HP=0 = death", + "Strategy prompt provided once at startup, fed to the agent as system prompt for every tick", + "LLM agent receives current frame + HP + tick number, returns a single action" + ], + "out_of_scope": [ + "Multiple rooms, dungeon generation, procedural levels", + "Combat with enemies, NPCs, monsters", + "Inventory, items, equipment", + "Save/load, persistence", + "Visual UI beyond ASCII to terminal", + "Multiplayer, networking", + "Self-improving agent loops or RL training" + ], + "success_criteria": [ + "A user can run a single command, supply a strategy prompt, and watch the agent play until win or death", + "Win and death paths both observed in manual playtests", + "Different strategy prompts produce visibly different agent behavior", + "End-to-end run completes in under 60 seconds wall time on a typical OpenAI API call" + ], + "nice_to_have": [ + "Configurable room layout from a text file", + "Replay log written to disk for post-hoc inspection", + "A few preset strategy prompts to demo (cautious, greedy, exploratory)" + ] + }, + "sign_offs": [ + { + "phase": "handing-off", + "by": "human", + "actor": "kj", + "at": "2026-05-17T04:14:44.523Z", + "notes": "All decisions accepted, graph validates clean." + }, + { + "phase": "handing-off", + "by": "human", + "actor": "kj", + "at": "2026-05-17T04:14:44.540Z" + } + ], + "handoff": { + "target": "filesystem", + "exported_at": "2026-05-17T04:14:44.540Z", + "issue_count": 7, + "document_count": 4 + }, + "gate_config": { + "preset": "poc" + }, + "tags": [] +} diff --git a/benchmarks/roguelike-ai-poc/reference/project.md b/benchmarks/roguelike-ai-poc/reference/project.md new file mode 100644 index 0000000..538b476 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/project.md @@ -0,0 +1,64 @@ +# AI-driven roguelike POC + +| Field | Value | +| --- | --- | +| ID | `ai-driven-roguelike-poc` | +| Status | `handed-off` | +| Effort level | `poc` | +| Created | 2026-05-17T04:12:02.030Z | +| Updated | 2026-05-17T04:14:44.540Z | +| Decisions | 4 | +| Tasks | 7 | + +## Description + +A minimal roguelike where the player primes an AI agent with a strategy, then the agent autonomously navigates a single ASCII-rendered room over a tick system until it wins the objective or dies. Goal: prove the agent-as-player concept with the smallest viable surface area. + +## Scope + +**In scope** + +- A 10×10 ASCII-rendered single room with walls (#), floor (.), player (@), exit (>), and a hazard tile (X) +- Tick-based game loop: each tick prints the frame, then queries the agent for one action +- A small action vocabulary: move N/S/E/W and noop +- Player has HP; stepping on hazard removes HP; reaching exit = win, HP=0 = death +- Strategy prompt provided once at startup, fed to the agent as system prompt for every tick +- LLM agent receives current frame + HP + tick number, returns a single action + +**Success criteria** + +- A user can run a single command, supply a strategy prompt, and watch the agent play until win or death +- Win and death paths both observed in manual playtests +- Different strategy prompts produce visibly different agent behavior +- End-to-end run completes in under 60 seconds wall time on a typical OpenAI API call + +**Out of scope** + +- Multiple rooms, dungeon generation, procedural levels +- Combat with enemies, NPCs, monsters +- Inventory, items, equipment +- Save/load, persistence +- Visual UI beyond ASCII to terminal +- Multiplayer, networking +- Self-improving agent loops or RL training + +**Nice to have** + +- Configurable room layout from a text file +- Replay log written to disk for post-hoc inspection +- A few preset strategy prompts to demo (cautious, greedy, exploratory) + +## Sign-offs + +- **handing-off** by kj (human) at 2026-05-17T04:14:44.523Z — All decisions accepted, graph validates clean. + +- **handing-off** by kj (human) at 2026-05-17T04:14:44.540Z + +## Handoff + +| Field | Value | +| --- | --- | +| Target | `filesystem` | +| Exported at | 2026-05-17T04:14:44.540Z | +| Target ID | — | +| Target URL | — | diff --git a/benchmarks/roguelike-ai-poc/reference/tasks/T0001-bootstrap-repository.json b/benchmarks/roguelike-ai-poc/reference/tasks/T0001-bootstrap-repository.json new file mode 100644 index 0000000..c433a10 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/tasks/T0001-bootstrap-repository.json @@ -0,0 +1,30 @@ +{ + "id": "T0001-bootstrap-repository", + "number": 1, + "slug": "bootstrap-repository", + "title": "Bootstrap repository", + "description": "Initialize the Python project layout: pyproject.toml or requirements.txt with openai pin, a src/ module path, a README stub, and a .gitignore. Verify a `python -c \"import openai\"` succeeds in a fresh venv.", + "status": "ready", + "estimate": { + "unit": "hours", + "value": 1, + "confidence": "high" + }, + "acceptance_criteria": [ + "pyproject.toml or requirements.txt committed", + "openai SDK installable in a venv", + "README explains 30-second quickstart", + "python -c \"from src import __init__\" runs" + ], + "depends_on": [], + "decision_refs": [ + "0001-choose-the-implementation-language" + ], + "priority": "p0", + "labels": [ + "foundation" + ], + "assignee_hint": "agent", + "created_at": "2026-05-17T04:14:22.524Z", + "updated_at": "2026-05-17T04:14:22.524Z" +} diff --git a/benchmarks/roguelike-ai-poc/reference/tasks/T0001-bootstrap-repository.md b/benchmarks/roguelike-ai-poc/reference/tasks/T0001-bootstrap-repository.md new file mode 100644 index 0000000..09effaa --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/tasks/T0001-bootstrap-repository.md @@ -0,0 +1,23 @@ +# T0001-bootstrap-repository — Bootstrap repository + +| Field | Value | +| --- | --- | +| Status | `ready` | +| Priority | `p0` | +| Estimate | 1 hours (high confidence) | +| Depends on | _(none)_ | +| Decision refs | `0001-choose-the-implementation-language` — Choose the implementation language | +| Assignee hint | agent | +| Labels | `foundation` | +| Updated | 2026-05-17T04:14:22.524Z | + +## Description + +Initialize the Python project layout: pyproject.toml or requirements.txt with openai pin, a src/ module path, a README stub, and a .gitignore. Verify a `python -c "import openai"` succeeds in a fresh venv. + +## Acceptance criteria + +- [ ] pyproject.toml or requirements.txt committed +- [ ] openai SDK installable in a venv +- [ ] README explains 30-second quickstart +- [ ] python -c "from src import __init__" runs diff --git a/benchmarks/roguelike-ai-poc/reference/tasks/T0002-implement-world-module-tile-grid-entity-dict.json b/benchmarks/roguelike-ai-poc/reference/tasks/T0002-implement-world-module-tile-grid-entity-dict.json new file mode 100644 index 0000000..c7a6c75 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/tasks/T0002-implement-world-module-tile-grid-entity-dict.json @@ -0,0 +1,32 @@ +{ + "id": "T0002-implement-world-module-tile-grid-entity-dict", + "number": 2, + "slug": "implement-world-module-tile-grid-entity-dict", + "title": "Implement world module (tile grid + entity dict)", + "description": "Build src/world.py: World dataclass with static_tiles: list[list[str]] and entities: dict[str, dict]. Provide constructors for a default 10×10 room (walls border, one hazard, one exit). Pure data and helpers; no rendering, no game logic.", + "status": "open", + "estimate": { + "unit": "hours", + "value": 2, + "confidence": "med" + }, + "acceptance_criteria": [ + "World.default_room() returns a valid 10x10 with #, ., X, > tiles", + "entities dict contains a player at a known spawn", + "is_walkable(x,y) returns False for walls, True for floor and hazard", + "unit test: default room is fully walkable from spawn to exit" + ], + "depends_on": [ + "T0001-bootstrap-repository" + ], + "decision_refs": [ + "0002-define-the-world-representation-and-renderer" + ], + "priority": "p0", + "labels": [ + "core" + ], + "assignee_hint": "agent", + "created_at": "2026-05-17T04:14:22.526Z", + "updated_at": "2026-05-17T04:14:22.526Z" +} diff --git a/benchmarks/roguelike-ai-poc/reference/tasks/T0002-implement-world-module-tile-grid-entity-dict.md b/benchmarks/roguelike-ai-poc/reference/tasks/T0002-implement-world-module-tile-grid-entity-dict.md new file mode 100644 index 0000000..ff06ca3 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/tasks/T0002-implement-world-module-tile-grid-entity-dict.md @@ -0,0 +1,23 @@ +# T0002-implement-world-module-tile-grid-entity-dict — Implement world module (tile grid + entity dict) + +| Field | Value | +| --- | --- | +| Status | `open` | +| Priority | `p0` | +| Estimate | 2 hours (med confidence) | +| Depends on | `T0001-bootstrap-repository` | +| Decision refs | `0002-define-the-world-representation-and-renderer` — Define the world representation and renderer | +| Assignee hint | agent | +| Labels | `core` | +| Updated | 2026-05-17T04:14:22.526Z | + +## Description + +Build src/world.py: World dataclass with static_tiles: list[list[str]] and entities: dict[str, dict]. Provide constructors for a default 10×10 room (walls border, one hazard, one exit). Pure data and helpers; no rendering, no game logic. + +## Acceptance criteria + +- [ ] World.default_room() returns a valid 10x10 with #, ., X, > tiles +- [ ] entities dict contains a player at a known spawn +- [ ] is_walkable(x,y) returns False for walls, True for floor and hazard +- [ ] unit test: default room is fully walkable from spawn to exit diff --git a/benchmarks/roguelike-ai-poc/reference/tasks/T0003-implement-frame-renderer.json b/benchmarks/roguelike-ai-poc/reference/tasks/T0003-implement-frame-renderer.json new file mode 100644 index 0000000..0caf6b1 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/tasks/T0003-implement-frame-renderer.json @@ -0,0 +1,32 @@ +{ + "id": "T0003-implement-frame-renderer", + "number": 3, + "slug": "implement-frame-renderer", + "title": "Implement frame renderer", + "description": "Build src/render.py: render_frame(world) -> list[str]. Compose static_tiles + entity glyphs (entity overrides tile). Provide a small HUD line below the frame showing tick number, HP, and last action. Return as list of strings so the game loop can join + print or send to LLM.", + "status": "open", + "estimate": { + "unit": "hours", + "value": 1, + "confidence": "high" + }, + "acceptance_criteria": [ + "render_frame returns 10 strings of length 10", + "player @ is visible at its current position", + "HUD line includes tick, hp, last_action", + "manual visual check: frame looks like a roguelike room" + ], + "depends_on": [ + "T0002-implement-world-module-tile-grid-entity-dict" + ], + "decision_refs": [ + "0002-define-the-world-representation-and-renderer" + ], + "priority": "p0", + "labels": [ + "core" + ], + "assignee_hint": "agent", + "created_at": "2026-05-17T04:14:22.527Z", + "updated_at": "2026-05-17T04:14:22.527Z" +} diff --git a/benchmarks/roguelike-ai-poc/reference/tasks/T0003-implement-frame-renderer.md b/benchmarks/roguelike-ai-poc/reference/tasks/T0003-implement-frame-renderer.md new file mode 100644 index 0000000..8bfc535 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/tasks/T0003-implement-frame-renderer.md @@ -0,0 +1,23 @@ +# T0003-implement-frame-renderer — Implement frame renderer + +| Field | Value | +| --- | --- | +| Status | `open` | +| Priority | `p0` | +| Estimate | 1 hours (high confidence) | +| Depends on | `T0002-implement-world-module-tile-grid-entity-dict` | +| Decision refs | `0002-define-the-world-representation-and-renderer` — Define the world representation and renderer | +| Assignee hint | agent | +| Labels | `core` | +| Updated | 2026-05-17T04:14:22.527Z | + +## Description + +Build src/render.py: render_frame(world) -> list[str]. Compose static_tiles + entity glyphs (entity overrides tile). Provide a small HUD line below the frame showing tick number, HP, and last action. Return as list of strings so the game loop can join + print or send to LLM. + +## Acceptance criteria + +- [ ] render_frame returns 10 strings of length 10 +- [ ] player @ is visible at its current position +- [ ] HUD line includes tick, hp, last_action +- [ ] manual visual check: frame looks like a roguelike room diff --git a/benchmarks/roguelike-ai-poc/reference/tasks/T0004-implement-openai-agent-client.json b/benchmarks/roguelike-ai-poc/reference/tasks/T0004-implement-openai-agent-client.json new file mode 100644 index 0000000..cdc8821 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/tasks/T0004-implement-openai-agent-client.json @@ -0,0 +1,34 @@ +{ + "id": "T0004-implement-openai-agent-client", + "number": 4, + "slug": "implement-openai-agent-client", + "title": "Implement OpenAI agent client", + "description": "Build src/agent.py: AgentClient class with constructor(strategy_prompt, model, api_key). Single method choose_action(world_state_json, tick, hp) → (direction, reasoning). Uses tool-calling with one tool do_action(direction in {N,S,E,W,noop}); tool_choice=\"required\". Returns the chosen direction and the assistant message content as reasoning.", + "status": "open", + "estimate": { + "unit": "hours", + "value": 2, + "confidence": "med" + }, + "acceptance_criteria": [ + "AgentClient instantiates without making a call", + "choose_action returns a valid direction enum", + "reasoning is captured as a string (may be empty)", + "malformed responses raise a clear error (does not silently noop)", + "strategy_prompt is in the system role on every call" + ], + "depends_on": [ + "T0001-bootstrap-repository" + ], + "decision_refs": [ + "0003-define-the-agent-action-contract" + ], + "priority": "p0", + "labels": [ + "llm", + "core" + ], + "assignee_hint": "agent", + "created_at": "2026-05-17T04:14:22.528Z", + "updated_at": "2026-05-17T04:14:22.528Z" +} diff --git a/benchmarks/roguelike-ai-poc/reference/tasks/T0004-implement-openai-agent-client.md b/benchmarks/roguelike-ai-poc/reference/tasks/T0004-implement-openai-agent-client.md new file mode 100644 index 0000000..0244119 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/tasks/T0004-implement-openai-agent-client.md @@ -0,0 +1,24 @@ +# T0004-implement-openai-agent-client — Implement OpenAI agent client + +| Field | Value | +| --- | --- | +| Status | `open` | +| Priority | `p0` | +| Estimate | 2 hours (med confidence) | +| Depends on | `T0001-bootstrap-repository` | +| Decision refs | `0003-define-the-agent-action-contract` — Define the agent action contract | +| Assignee hint | agent | +| Labels | `llm`, `core` | +| Updated | 2026-05-17T04:14:22.528Z | + +## Description + +Build src/agent.py: AgentClient class with constructor(strategy_prompt, model, api_key). Single method choose_action(world_state_json, tick, hp) → (direction, reasoning). Uses tool-calling with one tool do_action(direction in {N,S,E,W,noop}); tool_choice="required". Returns the chosen direction and the assistant message content as reasoning. + +## Acceptance criteria + +- [ ] AgentClient instantiates without making a call +- [ ] choose_action returns a valid direction enum +- [ ] reasoning is captured as a string (may be empty) +- [ ] malformed responses raise a clear error (does not silently noop) +- [ ] strategy_prompt is in the system role on every call diff --git a/benchmarks/roguelike-ai-poc/reference/tasks/T0005-implement-action-handlers-and-termination-checks.json b/benchmarks/roguelike-ai-poc/reference/tasks/T0005-implement-action-handlers-and-termination-checks.json new file mode 100644 index 0000000..20ad30f --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/tasks/T0005-implement-action-handlers-and-termination-checks.json @@ -0,0 +1,33 @@ +{ + "id": "T0005-implement-action-handlers-and-termination-checks", + "number": 5, + "slug": "implement-action-handlers-and-termination-checks", + "title": "Implement action handlers and termination checks", + "description": "Build src/actions.py: apply_action(world, direction) -> ActionResult. Moves the player one cell if walkable; otherwise noop. Compute side effects: HP-1 when stepping onto hazard, win flag when player_pos == exit_pos, dead flag when HP <= 0. Return ActionResult dataclass with new_world, hp_delta, terminal, terminal_reason.", + "status": "open", + "estimate": { + "unit": "hours", + "value": 1, + "confidence": "high" + }, + "acceptance_criteria": [ + "Moving into a wall is a noop with no HP change", + "Moving onto hazard triggers hp_delta = -1", + "Moving onto exit triggers terminal=\"win\"", + "HP reaching 0 triggers terminal=\"death\"", + "Unit tests for each transition" + ], + "depends_on": [ + "T0002-implement-world-module-tile-grid-entity-dict" + ], + "decision_refs": [ + "0002-define-the-world-representation-and-renderer" + ], + "priority": "p0", + "labels": [ + "core" + ], + "assignee_hint": "agent", + "created_at": "2026-05-17T04:14:22.529Z", + "updated_at": "2026-05-17T04:14:22.529Z" +} diff --git a/benchmarks/roguelike-ai-poc/reference/tasks/T0005-implement-action-handlers-and-termination-checks.md b/benchmarks/roguelike-ai-poc/reference/tasks/T0005-implement-action-handlers-and-termination-checks.md new file mode 100644 index 0000000..5ad2496 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/tasks/T0005-implement-action-handlers-and-termination-checks.md @@ -0,0 +1,24 @@ +# T0005-implement-action-handlers-and-termination-checks — Implement action handlers and termination checks + +| Field | Value | +| --- | --- | +| Status | `open` | +| Priority | `p0` | +| Estimate | 1 hours (high confidence) | +| Depends on | `T0002-implement-world-module-tile-grid-entity-dict` | +| Decision refs | `0002-define-the-world-representation-and-renderer` — Define the world representation and renderer | +| Assignee hint | agent | +| Labels | `core` | +| Updated | 2026-05-17T04:14:22.529Z | + +## Description + +Build src/actions.py: apply_action(world, direction) -> ActionResult. Moves the player one cell if walkable; otherwise noop. Compute side effects: HP-1 when stepping onto hazard, win flag when player_pos == exit_pos, dead flag when HP <= 0. Return ActionResult dataclass with new_world, hp_delta, terminal, terminal_reason. + +## Acceptance criteria + +- [ ] Moving into a wall is a noop with no HP change +- [ ] Moving onto hazard triggers hp_delta = -1 +- [ ] Moving onto exit triggers terminal="win" +- [ ] HP reaching 0 triggers terminal="death" +- [ ] Unit tests for each transition diff --git a/benchmarks/roguelike-ai-poc/reference/tasks/T0006-implement-the-tick-based-game-loop.json b/benchmarks/roguelike-ai-poc/reference/tasks/T0006-implement-the-tick-based-game-loop.json new file mode 100644 index 0000000..129cd6b --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/tasks/T0006-implement-the-tick-based-game-loop.json @@ -0,0 +1,35 @@ +{ + "id": "T0006-implement-the-tick-based-game-loop", + "number": 6, + "slug": "implement-the-tick-based-game-loop", + "title": "Implement the tick-based game loop", + "description": "Build src/loop.py: run_game(world, agent_client, max_steps=50). Each iteration: render frame, call agent_client.choose_action, apply action, check terminal, sleep 0.05s, repeat. Logs each tick: tick#, frame, action, reasoning excerpt, hp. Exits on terminal or step cap; returns final state + reason.", + "status": "open", + "estimate": { + "unit": "hours", + "value": 2, + "confidence": "med" + }, + "acceptance_criteria": [ + "Loop terminates on win, death, or step cap (≤50)", + "Each tick prints the frame and HUD to stdout", + "Final summary line shows reason and step count", + "No exceptions leak from agent timeouts/errors (logged and treated as noop)" + ], + "depends_on": [ + "T0003-implement-frame-renderer", + "T0004-implement-openai-agent-client", + "T0005-implement-action-handlers-and-termination-checks" + ], + "decision_refs": [ + "0004-define-the-tick-loop-and-termination-conditions", + "0002-define-the-world-representation-and-renderer" + ], + "priority": "p0", + "labels": [ + "core" + ], + "assignee_hint": "agent", + "created_at": "2026-05-17T04:14:22.530Z", + "updated_at": "2026-05-17T04:14:22.530Z" +} diff --git a/benchmarks/roguelike-ai-poc/reference/tasks/T0006-implement-the-tick-based-game-loop.md b/benchmarks/roguelike-ai-poc/reference/tasks/T0006-implement-the-tick-based-game-loop.md new file mode 100644 index 0000000..3338646 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/tasks/T0006-implement-the-tick-based-game-loop.md @@ -0,0 +1,23 @@ +# T0006-implement-the-tick-based-game-loop — Implement the tick-based game loop + +| Field | Value | +| --- | --- | +| Status | `open` | +| Priority | `p0` | +| Estimate | 2 hours (med confidence) | +| Depends on | `T0003-implement-frame-renderer`, `T0004-implement-openai-agent-client`, `T0005-implement-action-handlers-and-termination-checks` | +| Decision refs | `0004-define-the-tick-loop-and-termination-conditions` — Define the tick loop and termination conditions; `0002-define-the-world-representation-and-renderer` — Define the world representation and renderer | +| Assignee hint | agent | +| Labels | `core` | +| Updated | 2026-05-17T04:14:22.530Z | + +## Description + +Build src/loop.py: run_game(world, agent_client, max_steps=50). Each iteration: render frame, call agent_client.choose_action, apply action, check terminal, sleep 0.05s, repeat. Logs each tick: tick#, frame, action, reasoning excerpt, hp. Exits on terminal or step cap; returns final state + reason. + +## Acceptance criteria + +- [ ] Loop terminates on win, death, or step cap (≤50) +- [ ] Each tick prints the frame and HUD to stdout +- [ ] Final summary line shows reason and step count +- [ ] No exceptions leak from agent timeouts/errors (logged and treated as noop) diff --git a/benchmarks/roguelike-ai-poc/reference/tasks/T0007-implement-cli-entry-script.json b/benchmarks/roguelike-ai-poc/reference/tasks/T0007-implement-cli-entry-script.json new file mode 100644 index 0000000..030f430 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/tasks/T0007-implement-cli-entry-script.json @@ -0,0 +1,33 @@ +{ + "id": "T0007-implement-cli-entry-script", + "number": 7, + "slug": "implement-cli-entry-script", + "title": "Implement CLI entry script", + "description": "Build src/__main__.py: argparse for --strategy (or read from stdin), --model (default gpt-4o), --max-steps (default 50). Construct AgentClient, build default room, call run_game. Print the final outcome. Document the env vars (OPENAI_API_KEY) and a sample invocation in README.", + "status": "open", + "estimate": { + "unit": "hours", + "value": 1, + "confidence": "high" + }, + "acceptance_criteria": [ + "python -m src --strategy \"cautious explorer\" runs end-to-end", + "README has a complete example invocation", + "--help prints usage", + "Exit code 0 on win/timeout, 1 on death (so scripts can chain)" + ], + "depends_on": [ + "T0006-implement-the-tick-based-game-loop" + ], + "decision_refs": [ + "0001-choose-the-implementation-language", + "0004-define-the-tick-loop-and-termination-conditions" + ], + "priority": "p0", + "labels": [ + "cli" + ], + "assignee_hint": "agent", + "created_at": "2026-05-17T04:14:22.532Z", + "updated_at": "2026-05-17T04:14:22.532Z" +} diff --git a/benchmarks/roguelike-ai-poc/reference/tasks/T0007-implement-cli-entry-script.md b/benchmarks/roguelike-ai-poc/reference/tasks/T0007-implement-cli-entry-script.md new file mode 100644 index 0000000..ba9f268 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/reference/tasks/T0007-implement-cli-entry-script.md @@ -0,0 +1,23 @@ +# T0007-implement-cli-entry-script — Implement CLI entry script + +| Field | Value | +| --- | --- | +| Status | `open` | +| Priority | `p0` | +| Estimate | 1 hours (high confidence) | +| Depends on | `T0006-implement-the-tick-based-game-loop` | +| Decision refs | `0001-choose-the-implementation-language` — Choose the implementation language; `0004-define-the-tick-loop-and-termination-conditions` — Define the tick loop and termination conditions | +| Assignee hint | agent | +| Labels | `cli` | +| Updated | 2026-05-17T04:14:22.532Z | + +## Description + +Build src/__main__.py: argparse for --strategy (or read from stdin), --model (default gpt-4o), --max-steps (default 50). Construct AgentClient, build default room, call run_game. Print the final outcome. Document the env vars (OPENAI_API_KEY) and a sample invocation in README. + +## Acceptance criteria + +- [ ] python -m src --strategy "cautious explorer" runs end-to-end +- [ ] README has a complete example invocation +- [ ] --help prints usage +- [ ] Exit code 0 on win/timeout, 1 on death (so scripts can chain) diff --git a/benchmarks/roguelike-ai-poc/run.sh b/benchmarks/roguelike-ai-poc/run.sh new file mode 100755 index 0000000..67915d1 --- /dev/null +++ b/benchmarks/roguelike-ai-poc/run.sh @@ -0,0 +1,35 @@ +#!/usr/bin/env bash +# Run the roguelike-ai-poc benchmark prompt against a fresh tmp dir. +# Requires OPENAI_API_KEY in the environment. +# Usage: +# ./run.sh # run with defaults +# OUT=./my-output ./run.sh # specify output dir +# MODEL=gpt-4o-mini ./run.sh # override model + +set -euo pipefail + +if [[ -z "${OPENAI_API_KEY:-}" ]]; then + echo "OPENAI_API_KEY not set — refusing to run." >&2 + exit 2 +fi + +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +REPO_ROOT="$(cd "$HERE/../.." && pwd)" +OUT="${OUT:-$(mktemp -d -t dr-bench-roguelike-XXXX)}" + +DESCRIPTION="A minimal roguelike where the player primes an AI agent with a strategy, then the agent autonomously navigates a single ASCII-rendered room over a tick system until it wins the objective or dies. Goal: prove the agent-as-player concept with the smallest viable surface area." + +cd "$REPO_ROOT/server" +[[ -f dist/cli.js ]] || npm run build >&2 + +node dist/cli.js \ + --title "AI-driven roguelike POC" \ + --description "$DESCRIPTION" \ + --effort poc \ + --cwd "$OUT" \ + --yes \ + ${MODEL:+--model "$MODEL"} + +echo "" +echo "── Benchmark artifacts at: $OUT" +echo "Compare with: $HERE/reference/" diff --git a/docs/README.md b/docs/README.md new file mode 100644 index 0000000..2063fb4 --- /dev/null +++ b/docs/README.md @@ -0,0 +1,50 @@ +# Documentation + +The decision-record docs follow the [Diátaxis](https://diataxis.fr) framework — four kinds of documentation, each serving a different need. + +| You want to… | Read | +|---|---| +| **Learn** by following a guided first run | [Tutorials](tutorials/) | +| **Accomplish** a specific task | [How-to guides](how-to/) | +| **Look up** facts about a flag, tool, schema | [Reference](reference/) | +| **Understand** the design — why things are the way they are | [Explanation](explanation/) | + +## Start here + +**Brand new?** → [Your first plan](tutorials/your-first-plan.md) (15 minutes, end-to-end). + +**Already installed and want to do a thing?** → [How-to guides](how-to/). + +**Need the exact spec?** → [Reference](reference/). + +**Want the rationale?** → [Explanation](explanation/) — especially [why decision records](explanation/why-decision-records.md) and [design rationale](explanation/design-rationale.md). + +## Index + +### Tutorials +- [Your first plan](tutorials/your-first-plan.md) — run the roguelike benchmark prompt end-to-end + +### How-to guides +- [Install the plugin or CLI](how-to/install.md) +- [Run the CLI](how-to/run-the-cli.md) — idea, PRD, resume +- [Configure LLM providers](how-to/configure-providers.md) — OpenAI, OpenRouter, Ollama, vLLM, LiteLLM +- [Hand off to Linear](how-to/handoff-to-linear.md) +- [Calibrate gates](how-to/calibrate-gates.md) — `poc` / `mvp` / `full` + overrides + +### Reference +- [CLI](reference/cli.md) — every flag, env var, exit code +- [MCP tools](reference/mcp-tools.md) — full tool surface +- [Data model](reference/data-model.md) — entities, fields, types +- [Gates](reference/gates.md) — per-phase gate matrix + +### Explanation +- [Why decision records?](explanation/why-decision-records.md) — Joel Parker Henderson's canonical material +- [Design rationale](explanation/design-rationale.md) — why filesystem, why hard gates, why lens-rotating skeptic +- [The five phases](explanation/the-five-phases.md) — what each phase does and why this shape + +## Outside the docs tree + +- [Repo README](../README.md) — overview, status, install summary +- [CONTRIBUTING](../CONTRIBUTING.md) — how to contribute seeds, templates, and code +- [Benchmarks](../benchmarks/) — canonical prompts we use to spot regressions +- [Schemas](../schemas/) — JSON Schema source of truth for every entity diff --git a/docs/architecture.md b/docs/architecture.md deleted file mode 100644 index 60ed315..0000000 --- a/docs/architecture.md +++ /dev/null @@ -1,197 +0,0 @@ -# Architecture - -The decision-record plugin is two pieces: - -1. **An MCP server** (`server/`) — TypeScript, speaks the Model Context Protocol over stdio. Stateless aside from in-flight handling; durable state lives on disk in the target repo. -2. **A Claude Code plugin** (`.claude-plugin/`, `commands/`, `agents/`) — declares the slash command and sub-agents that drive the pipeline through MCP tool calls. - -This document covers the data model, the gate machine, and the rationale for each design choice. - -## Data model - -JSON Schema source of truth lives in [`schemas/`](../schemas/). Zod mirrors live in [`server/src/schemas/index.ts`](../server/src/schemas/index.ts). - -### Entity overview - -| Entity | Cardinality | File | Source of truth | -| --- | --- | --- | --- | -| Project | 1 per repo | `dr/project.json` | This file | -| PipelineState | 1 per repo | `.dr/state.json` | This file | -| Event | many, append-only | `.dr/events.jsonl` | This file (one entry per line) | -| Decision | 0..N | `dr/decisions/.json` | This file | -| Task | 0..N | `dr/tasks/.json` | This file | - -Markdown renderings (`*.md`, `index.html`) are **derived** — regenerated by `dr_render` from the JSON. Never edit them directly; they'll be overwritten. - -### Project - -The MVP manifest. Captures intent, scope, status, effort calibration, and post-handoff metadata. - -Key fields: -- `id` — stable kebab-case slug -- `status` — current phase (intake/scoping/deciding/decomposing/handing-off/handed-off) -- `effort_level` — `poc | mvp | full`; calibrates gate strictness -- `scope` — `{ in_scope, out_of_scope, success_criteria, nice_to_have }` -- `sign_offs` — array of phase-level sign-offs (`{ phase, by, actor, at, notes }`) -- `handoff` — populated at `handing-off → handed-off` with target + identifiers -- `gate_config` — `{ preset, overrides }`; overrides take precedence per-knob - -### Decision (DR) - -A single significant choice. Mirrors Joel Parker Henderson's canonical template structure (issue, assumptions, constraints, positions, opinions, argument, implications, related) with a few additions for the pipeline: - -- `template_variant` — `canonical | lightweight | scoping | vendor | architecture | data-model`. Affects rendering and (eventually) which sections are required. -- `status` — `rfc | proposed | accepted | rejected | deprecated | superseded`. Only `accepted` satisfies the deciding gate. -- `selected_position` — title of the winning position (must exist in `positions`). -- `review[]` — antagonistic-review passes (`reviewer`, `lens`, `verdict`, `score`, `concerns`). -- `sign_off` — final acceptance record (`by`, `actor`, `at`, `notes`). -- `depends_on[]` — IDs of decisions that must be accepted first. -- `seed_origin` — name of the seed template this DR was instantiated from, if any. - -### Task - -A beads-style work unit. Pre-handoff only — post-handoff lifecycle lives in Linear (or wherever else). - -- `status` — `open | ready | in_progress | done | blocked | deferred` -- `priority` — `p0..p3` -- `estimate` — `{ unit: 'hours'|'days', value, confidence }` -- `acceptance_criteria` — concrete done-when statements -- `depends_on[]` — task IDs that must complete first -- `decision_refs[]` — DR IDs this task implements (traceability) -- `external_ref` — set at handoff to the target system's identifier - -### PipelineState - -Internal state. Never edited by hand. - -- `phase` — same as `Project.status` but read-only from the pipeline's perspective -- `effective_gate_config` — materialized gate (preset merged with overrides) for fast lookup -- `next_decision_seq` / `next_task_seq` — monotonically-increasing counters -- `pending_questions[]` — open questions the agent has surfaced -- `gate_failures[]` — history of failed `dr_advance` attempts (useful for the agent to remember what to fix) - -### Event - -One JSONL line per state change. The events log is append-only and is the audit trail. - -Event kinds include: `project_initialized`, `phase_advanced`, `phase_advance_blocked`, `scope_updated`, `decision_proposed`, `decision_updated`, `decision_reviewed`, `decision_accepted`, `decision_rejected`, `task_proposed`, `task_updated`, `task_status_changed`, `graph_validated`, `gate_check_passed`, `gate_check_failed`, `question_asked`, `question_answered`, `seed_loaded`, `render_run`, `export_started`, `export_completed`, `export_failed`, `sign_off_recorded`. - -A future UI can replay this stream to reconstruct any historical state. - -## Gate machine - -The pipeline is a state machine with hard gates. Phases: - -``` -intake → scoping → deciding → decomposing → handing-off → handed-off -``` - -`dr_advance` is the only way to transition. The server evaluates the gate for the *next* phase against the current state. If all gate checks pass and any required sign-off is provided, the phase changes and an event is emitted. Otherwise, gate-failure reasons come back unchanged. - -### Per-phase checks - -| Phase advancing to | Checks | -| --- | --- | -| `scoping` | Project has title and description | -| `deciding` | `scope.in_scope` non-empty; `scope.success_criteria` non-empty; if review_required_phases includes 'scoping', a scoping-variant DR has a passing review | -| `decomposing` | ≥ min_decisions; if `decisions_required_status === 'accepted'`, no decisions in `proposed`/`rfc`; if `review_required_per_decision`, every accepted decision has a passing review; if `review_required_phases` includes 'deciding', at least one decision has a passing review; no dangling decision dependencies | -| `handing-off` | ≥ min_tasks; no dangling task dependencies; no cycles; every task has an estimate ≤ max_task_estimate_hours; every task's `decision_refs` resolve | -| `handed-off` | `project.handoff` exists (run dr_export_filesystem or dr_export_linear first) | - -### Sign-off requirement - -Each phase transition can require human sign-off via `require_human_signoff_phases`. When set, `dr_advance` only proceeds if you pass `sign_off_by: 'human'`. The agent cannot self-approve a human-required gate. - -## Gate configuration - -Three preset tiers calibrate strictness: - -``` -poc: - decisions_required_status: accepted - review_required_phases: [] - review_required_per_decision: false - max_task_estimate_hours: 16 - require_human_signoff_phases: [handing-off] - min_decisions: 0 - min_tasks: 3 - -mvp: - decisions_required_status: accepted - review_required_phases: [scoping, decomposing] - review_required_per_decision: false - max_task_estimate_hours: 8 - require_human_signoff_phases: [scoping, decomposing, handing-off] - min_decisions: 3 - min_tasks: 8 - -full: - decisions_required_status: accepted - review_required_phases: [scoping, deciding, decomposing] - review_required_per_decision: true - max_task_estimate_hours: 4 - require_human_signoff_phases: [scoping, deciding, decomposing, handing-off] - min_decisions: 6 - min_tasks: 15 -``` - -`gate_overrides` on the project let you tune individual knobs without changing preset: - -```json -{ - "preset": "mvp", - "overrides": { - "min_tasks": 5, - "review_required_phases": ["scoping"] - } -} -``` - -The materialized result lives at `state.effective_gate_config` for fast lookup. - -## MCP tool surface - -| Group | Tools | -| --- | --- | -| Pipeline | `dr_init`, `dr_status`, `dr_advance`, `dr_update_project`, `dr_update_scope` | -| Decisions | `dr_propose_decision`, `dr_update_decision`, `dr_review_decision`, `dr_accept_decision`, `dr_reject_decision`, `dr_list_decisions`, `dr_get_decision`, `dr_ready_decisions` | -| Tasks | `dr_propose_task`, `dr_update_task`, `dr_set_task_status`, `dr_list_tasks`, `dr_get_task`, `dr_ready_tasks`, `dr_validate_graph` | -| Seeds | `dr_seed_search`, `dr_seed_list`, `dr_seed_get`, `dr_seed_load` | -| Render | `dr_render` | -| Handoff | `dr_export_filesystem`, `dr_export_linear` | - -All tools accept `cwd` (target repo) and default to `process.cwd()` when omitted. - -## Why this shape - -### Why filesystem instead of SQLite - -[beads_rust](https://github.com/Dicklesworthstone/beads_rust) uses SQLite + JSONL. We picked filesystem-only because the user prefers data-driven artifacts that are git-diffable and human-readable, and because the working set is small (tens of decisions, dozens of tasks). The JSONL event log gives us the audit trail without the SQLite dependency. - -### Why TypeScript - -Best fit for a Claude Code plugin. Easy to iterate on prompts and templates. Smaller install footprint than a Python/Rust toolchain. We can revisit if performance ever matters (it won't at this scale). - -### Why hard gates instead of soft suggestions - -Soft gates degrade. People learn to skip them. By making the wizard refuse to emit a "ship-ready plan" until criteria are met, the artifact becomes trustworthy: if it exists, it's complete. - -### Why per-project calibration - -Not every project deserves a SWOT analysis. The POC preset removes ceremony for hack-day work; the Full preset keeps it for regulated or production-grade work. The user picks at init time. - -### Why state-driven over form-driven - -A rigid form would force the wizard to ask the same questions in the same order regardless of project shape. State-driven means: the agent reads what's in the state, identifies what's missing for the gate, and picks the next question. This is the pattern Automaker's resume-check uses ([reference here](https://github.com/protoLabsAI/automaker)). - -### Why antagonistic review - -Decisions made fast without pushback ossify. The `dr-skeptic` agent forces a structured "what could go wrong here?" pass before accepting. Inspired by Automaker's two-reviewer pattern (Ava operational + Jon strategic). - -### Why Linear as the primary handoff target - -The user works in Linear. Linear's official MCP server is mature; Linear's data model (Project + Issue + Project-Update + Initiative + Milestone) maps cleanly to our manifest + tasks. Other target adapters (Plane, GitHub Projects, Jira) can be added by following the `handoff/linear.ts` pattern. - -## Versioning - -`PipelineState.schema_version` is the durable contract. We bump it on breaking layout changes. The server refuses to mutate older versions until migrated. There's no migration tooling yet — when we cross 1.0, we'll add it. diff --git a/docs/explanation/design-rationale.md b/docs/explanation/design-rationale.md new file mode 100644 index 0000000..7b759a7 --- /dev/null +++ b/docs/explanation/design-rationale.md @@ -0,0 +1,104 @@ +# Design rationale + +The decisions behind how this system is built. Use these when you want to understand "why this way and not the obvious other way." + +## Hard gates instead of soft suggestions + +Soft gates degrade. People learn to skip them, the optional becomes invisible, and within a few iterations the artifact stops being trustworthy. We made every phase transition refusal-by-default: if a gate fails, the wizard returns reasons, does not advance, and there is no `--force`. The artifact's value is the assurance that everything it claims is real. + +Consequence: when a gate is too strict, you change the gate, not bypass it. The `gate_config.overrides` mechanism is the official escape hatch — explicit and recorded. + +## Five phases, exactly + +Intake → Scoping → Deciding → Decomposing → Handoff is the smallest sequence that gives each artifact a clean home and makes ordering load-bearing: + +- **Intake** captures the seed. +- **Scoping** sets the perimeter before decisions are made (so decisions can be evaluated against scope). +- **Deciding** resolves significant choices before tasks are written (so tasks can reference decisions for traceability). +- **Decomposing** turns decisions into work (so the work shape follows from the choices). +- **Handoff** finalizes (so the artifact has a clear "done" state). + +We tried collapsing decisions and decomposition. The decomposer ended up making decisions in passing — implicit, unreviewed, untraceable. Splitting the phases forced decisions to be first-class. + +## File-system, not a database + +Beads_rust uses SQLite + JSONL. We went filesystem-only: + +- The working set is small (tens of decisions, dozens of tasks). +- JSON files diff well in git; engineers can read them without tooling. +- A future UI can read the same files; no schema migration tax. +- The JSONL event log gives us the audit trail without the DB dependency. + +The trade-off: queries are O(N) directory scans. Acceptable at our scale. If we ever need cross-project indexing or multi-user concurrency, we revisit. + +## TypeScript everywhere + +Single language across the MCP server, CLI, and tests. Best fit for the Claude Code plugin ecosystem. The `openai` SDK is mature in TypeScript. Iterating on prompts and templates is fast. We considered Rust to match beads_rust's philosophy — rejected because we iterate on prompts more than perf, and a 100KB CLI bundle is fine. + +## OpenAI-compatible, single provider + +We initially planned dual backends (Anthropic SDK + openai SDK). Cut to OpenAI-compat only because: + +- A single SDK is half the surface area to maintain. +- `OPENAI_BASE_URL` already covers Anthropic-via-OpenRouter, local Ollama/vLLM, LiteLLM proxies, and most enterprise gateways. +- The agents do straightforward tool calling; nothing requires a vendor-specific SDK feature. + +If we ever need Anthropic-native features (cache_control, adaptive thinking), we add a thin adapter — but we don't anticipate it. + +## Antagonistic review with lens rotation + +We use a `dr-skeptic` sub-agent that reviews decisions through one specific lens (operational, strategic, security, cost, user-impact) per invocation. For the `full` preset, every decision runs through all five lenses. + +Inspired by Automaker's two-reviewer pattern (Ava operational + Jon strategic), but generalized: the lens menu is open-ended, and each lens is its own scoped prompt instead of a single reviewer trying to hold all perspectives at once. A focused agent finds more concrete concerns than a broad one. + +The skeptic doesn't have to win. A human can override `block` verdicts with explicit sign-off. But the lens output is recorded on the DR forever — visible to anyone who reads it later. + +## State-driven, not form-driven + +The wizard's job is to read the current state, identify what's missing for the next gate, and pick the next action. It is not a fixed Q&A sequence. This matches Automaker's resume-check pattern — drop in mid-pipeline, the wizard recovers gracefully. + +Practical consequence: every wizard invocation starts with `dr_status`. There's no implicit conversation state in the agent loop; everything is on disk. + +## Pre-MVP only, deliberately + +The pipeline stops at `handed-off`. We don't track post-handoff execution. That belongs in whatever execution system the team uses — Linear, Plane, GitHub Projects, etc. + +Why: planning tools that grow into execution tools accumulate scope until they're nothing in particular. By stopping at handoff, the boundary is clear: the plan is the artifact; execution is somebody else's tool. + +## Per-project gate calibration + +A weekend hack does not need the same gates as a regulated production rollout. Three presets (`poc`, `mvp`, `full`) calibrate strictness; per-knob overrides handle the edge cases. Picked at init. + +This was the user feedback that shaped the gate machine: the same hard-gate philosophy can apply to wildly different project shapes, as long as the strictness scales. + +## Seed library + +A small set (currently nine) of canned decisions for territory the agent will repeatedly see: language, runtime, data store, auth, deployment, CI/CD, testing, observability, scope-statement. Each is a starter — the agent loads it and customizes for the project. + +Why ship these: avoids the agent rediscovering the same trade-offs each project. The seed encodes prior pattern-matching as a starting point, not a final answer. The user can fork the seed library and add their team's defaults. + +## Linear as the primary handoff target + +The user's primary use case is Linear; the data model maps cleanly. We use Linear's GraphQL API directly with an API key, not their MCP server, because: + +- We need precise control over the project/issue/relation creation sequence. +- The GraphQL API is mature and well-documented. +- Adding MCP-server-as-downstream adds an extra dependency layer for a one-shot operation. + +Other handoff targets follow the `server/src/handoff/linear.ts` pattern: `buildExportPlan` (pure, testable) + per-target API calls. + +## What we explicitly didn't build + +- **A web UI** — the data model is UI-ready (JSON-everywhere, JSONL event log) but we ship Markdown + static HTML for now. UI work would dwarf the pipeline work. +- **Real-time multi-user collaboration** — single-user, single-machine. The artifact is git-tracked; that's how teams share. +- **A built-in LLM** — we depend on OpenAI-compat endpoints. No model bundling. +- **Reconciliation for partial Linear exports** — a known follow-up. For now, a failed export means deleting the partial Linear project and re-running. +- **A CI integration** — beyond the test suite. The plugin produces artifacts; what teams do with them in CI is up to the team. + +## Open questions + +- Does the lens-rotating skeptic produce meaningfully better decisions than a single skeptic? Needs benchmark data over time. +- Is the nine-seed library the right size? Probably grows. +- Should `handed-off` have a "re-open for amendment" path? Currently it's a terminal state. + +We track these by re-running benchmarks as the system changes. diff --git a/docs/explanation/the-five-phases.md b/docs/explanation/the-five-phases.md new file mode 100644 index 0000000..b1352a0 --- /dev/null +++ b/docs/explanation/the-five-phases.md @@ -0,0 +1,133 @@ +# The five phases + +The pipeline has exactly five phases between an idea and a ship-ready plan. Each phase has a single job; each transition is gated. + +``` +intake → scoping → deciding → decomposing → handing-off → handed-off +``` + +This page explains what each phase accomplishes and why it exists. + +## Intake + +**Job:** Capture the idea. + +**Inputs:** a one-line idea, an optional PRD, an effort-level choice. + +**Outputs:** a `Project` object with title, description, effort_level, and an empty everything-else. + +**Gate to next phase:** title and description non-empty. + +**Why it exists:** to write the seed down. Until the idea has an `id` on disk, the wizard has nothing to read on subsequent turns. Intake is mechanical and fast. + +## Scoping + +**Job:** Pin the MVP perimeter. + +**Inputs:** the project description, optionally a PRD, optionally a `scope-statement` seed. + +**Outputs:** + +- `project.scope.in_scope` — capabilities the MVP MUST ship +- `project.scope.out_of_scope` — explicit non-goals (this is the load-bearing list) +- `project.scope.success_criteria` — measurable signals +- `project.scope.nice_to_have` — optional capabilities +- Under `mvp`/`full` presets: a `scope-statement` DR with a selected shape (lean / walking-skeleton / polished) and an argument + +**Gate to next phase:** `in_scope` and `success_criteria` non-empty. Under `mvp`/`full`, the scope DR has a passing review. + +**Why it exists:** without explicit scope, decisions and tasks expand silently. Pinning scope first means every decision evaluated against it has a clear target. The `out_of_scope` list, in particular, is the thing that prevents scope creep later — if it's not on the in_scope list, it's not in the plan. + +## Deciding + +**Job:** Resolve significant decisions. + +**Inputs:** the scoped project. Each decision area is a "would otherwise be re-litigated" choice — language, data store, auth, deployment target, agent contract, etc. + +**Outputs:** a set of `Decision` records, each with: + +- An issue framing +- 2–4 positions with pros/cons +- A `selected_position` and an `argument` +- Under `full` preset: one `Review` entry per lens (operational, strategic, security, cost, user-impact) +- Final `status: accepted` with a `sign_off` + +**Gate to next phase:** ≥ `min_decisions` count; every decision either `accepted` or `rejected` (no in-flight `proposed`); per-decision review passed if `review_required_per_decision`; no dangling decision dependencies. + +**Why it exists:** decisions made implicitly during decomposition are untraceable. Forcing them into first-class records means future-you (or future-them) can see why the team chose X. The `seed_origin` field also lets the agent learn from past projects without redeciding the obvious. + +## Decomposing + +**Job:** Turn decisions into a task graph. + +**Inputs:** accepted decisions + scope. Each task is a vertical slice that ships some user-visible behavior end-to-end, sized to fit under the preset's `max_task_estimate_hours`. + +**Outputs:** a set of `Task` records, each with: + +- A title and description +- Acceptance criteria (concrete done-when statements) +- An estimate (hours/days + confidence) +- `decision_refs` linking back to the decisions it implements +- `depends_on` for ordering + +**Gate to next phase:** ≥ `min_tasks`; no cycles; no orphan dependencies; every estimate within budget; every `decision_refs` resolves; under `mvp`/`full`, the decomposing phase has been reviewed. + +**Why it exists:** without explicit dependencies, the team works in arbitrary order and discovers blockers late. The dependency graph makes the order legible. The `decision_refs` make traceability automatic — if a decision changes, you can find every task affected. + +## Handing off + +**Job:** Finalize the plan into a target system. + +**Inputs:** the validated decision + task graph; a handoff target (Linear or filesystem). + +**Outputs:** + +- For Linear: a Linear Project, an Issue per decision (labeled `decision`), an Issue per task with priority/estimate/acceptance criteria, `blocks` relations for `depends_on`. Each task's local JSON gets an `external_ref` for traceability. +- For filesystem: the `dr/` tree is finalized, `project.json.handoff` is set, mutations are halted. + +**Gate to next phase:** `project.handoff` set; sign-off provided. + +**Why it exists:** to mark the plan as complete and hand it to the execution system. After this point, the pipeline considers the work done; ongoing changes happen wherever the engineering team works. + +## Handed off (terminal) + +**Job:** Hold the final state. + +**Inputs:** the finished pipeline. + +**Outputs:** none. This is a terminal state — `dr_advance` from `handed-off` returns null. + +**Why it exists:** the pipeline has a clear "done." There is no post-handoff lifecycle in this system; that belongs in Linear/Plane/wherever. + +## Why exactly these five + +We tried a few alternative shapes: + +- **Three phases** (idea → plan → handoff) — too coarse; the agent had to make scope decisions and task decisions in the same step, and they collapsed into each other. +- **Seven phases** (adding "research" before scope and "verification" before handoff) — felt heavier than the workload warranted. The agent can pull research into scoping; verification is what the gates already do. +- **No explicit handoff phase** (just an export tool) — the export ended up being the implicit handoff, but without a phase boundary the gate machine couldn't enforce sign-off and completeness. + +The current shape is the smallest that gives each artifact a single owner and makes every transition load-bearing. + +## What happens between phases + +Between phases, the wizard: + +1. Reads the current state with `dr_status`. +2. Evaluates the gate to the next phase. +3. If passing and no human sign-off is required, calls `dr_advance` directly. +4. If passing and human sign-off is required, prompts the user (or auto-confirms under `--yes`). +5. If failing, surfaces the gate reasons and tries to make the agent fix them — usually by running the phase's sub-agent again. + +The phase machine is therefore not just "what's the next thing" — it's "what gate is blocking us, and what work closes that gate." + +## State-driven progression + +Critically: phase progression is **state-driven, not turn-driven**. The wizard doesn't say "we just finished scoping so I'll move to deciding." It says "scope is non-empty, the scope DR is reviewed, the gate passes, so I'll advance." This means: + +- The wizard can resume cleanly mid-phase. +- Partial work isn't wasted. +- A human can edit `project.json` between sessions and the wizard adapts. +- Phase order is enforced by the gate machine, not by the agent's memory. + +That's the underlying primitive that makes the rest work. diff --git a/docs/upstream-canon.md b/docs/explanation/why-decision-records.md similarity index 100% rename from docs/upstream-canon.md rename to docs/explanation/why-decision-records.md diff --git a/docs/how-to/calibrate-gates.md b/docs/how-to/calibrate-gates.md new file mode 100644 index 0000000..6bffb99 --- /dev/null +++ b/docs/how-to/calibrate-gates.md @@ -0,0 +1,79 @@ +# Calibrate gates + +The pipeline is hard-gated — every phase transition checks a set of conditions, and refuses to advance if they're not met. The strictness of those conditions is set per-project by an **effort level** preset, with optional per-knob overrides. + +## Choose a preset + +```bash +decision-record --idea "…" --effort poc # loosest +decision-record --idea "…" --effort mvp # default +decision-record --idea "…" --effort full # strictest +``` + +| Knob | `poc` | `mvp` (default) | `full` | +|---|---|---|---| +| Minimum decisions to advance from deciding | 0 | 3 | 6 | +| Minimum tasks to advance from decomposing | 3 | 8 | 15 | +| Max hours per leaf task | 16 | 8 | 4 | +| Phases that require reviewed scope/decisions/decomp | (none) | scoping, decomposing | scoping, deciding, decomposing | +| Every DR reviewed individually (lens-rotating skeptic) | no | no | **yes** | +| Phases that require human sign-off | handing-off | scoping, decomposing, handing-off | scoping, deciding, decomposing, handing-off | + +**When to use each:** + +- **`poc`** — weekend hacks, prototypes, internal-only spikes. Minimal ceremony. +- **`mvp`** (default) — a real product slice. Scope and decomposition get scrutiny; individual decisions don't get a full review pass. +- **`full`** — production work, regulated domains, anything where reading the decisions in six months matters. Every DR is reviewed by the lens-rotating skeptic before acceptance. + +## Override individual knobs + +Sometimes a preset is close but one knob is off. Override at init time: + +```bash +# Use MVP defaults but require only 5 tasks instead of 8 +decision-record --idea "…" --effort mvp \ + # (override flags coming — for now use the MCP dr_update_project tool after init) +``` + +> The CLI does not currently expose per-knob overrides as flags. You can override them by calling `dr_update_project` via the MCP server, or by editing `dr/project.json` directly (then re-running with `--resume`). A `--gate-override key=value` flag is a planned addition. + +### Override schema + +`project.json` has a `gate_config.overrides` object. Any knob you set there wins over the preset: + +```json +{ + "gate_config": { + "preset": "mvp", + "overrides": { + "min_tasks": 5, + "review_required_per_decision": true, + "max_task_estimate_hours": 6 + } + } +} +``` + +Available override knobs: + +| Key | Type | Effect | +|---|---|---| +| `decisions_required_status` | `"accepted"` \| `"any"` | What DR status counts toward the deciding gate. Use `"any"` to allow rejection without re-deciding. | +| `review_required_phases` | `string[]` | Phases at which an antagonistic review must happen before advance. | +| `review_required_per_decision` | `boolean` | If true, every DR needs a passing review before acceptance. | +| `max_task_estimate_hours` | `number` | Leaf task estimate ceiling. | +| `require_human_signoff_phases` | `string[]` | Phases that need human (not agent) sign-off to advance. | +| `min_decisions` | `integer` | Minimum decisions to advance from deciding. | +| `min_tasks` | `integer` | Minimum tasks to advance from decomposing. | + +## Inspect the effective config + +```bash +cat /.dr/state.json | jq '.effective_gate_config' +``` + +The `effective_gate_config` is the materialized preset + overrides; it's what the gate evaluator actually checks against. Edit `project.json` overrides, then re-run with `--resume` to see the change. + +## Why hard gates? + +Soft gates degrade. People learn to skip them. By refusing to emit a "ship-ready plan" until the criteria are met, the resulting artifact becomes trustworthy: if it exists, it's complete. See [the design rationale](../explanation/design-rationale.md) for the longer version. diff --git a/docs/how-to/configure-providers.md b/docs/how-to/configure-providers.md new file mode 100644 index 0000000..19e68f5 --- /dev/null +++ b/docs/how-to/configure-providers.md @@ -0,0 +1,103 @@ +# Configure LLM providers + +The CLI uses the **OpenAI-compatible** API surface. Anything that speaks that protocol works — OpenAI itself, OpenRouter, Ollama, vLLM, LiteLLM, etc. + +## OpenAI (the default) + +```bash +export OPENAI_API_KEY=sk-… +decision-record --idea "…" +``` + +Default model: `gpt-4o`. Override per-call: + +```bash +decision-record --idea "…" --model gpt-4o-mini +``` + +Or persistently: + +```bash +export OPENAI_MODEL=gpt-4o-mini +``` + +## OpenRouter + +[OpenRouter](https://openrouter.ai/) proxies many providers behind a single OpenAI-compatible endpoint. + +```bash +export OPENAI_API_KEY=sk-or-… +export OPENAI_BASE_URL=https://openrouter.ai/api/v1 +export OPENAI_MODEL=anthropic/claude-sonnet-4-6 +decision-record --idea "…" +``` + +## Ollama (local) + +[Ollama](https://ollama.com/) serves an OpenAI-compatible endpoint on `:11434`. + +```bash +ollama pull llama3.1:70b # one time +ollama serve # if not already running +``` + +```bash +export OPENAI_API_KEY=ollama # any non-empty string works +export OPENAI_BASE_URL=http://localhost:11434/v1 +export OPENAI_MODEL=llama3.1:70b +decision-record --idea "…" +``` + +> **Tool calling matters.** The agents rely on the model emitting tool calls. Verify your local model supports OpenAI-style function calling before running a full pipeline. Smaller models often struggle here. + +## vLLM (self-hosted) + +[vLLM](https://github.com/vllm-project/vllm) exposes an OpenAI-compatible server. + +```bash +python -m vllm.entrypoints.openai.api_server \ + --model meta-llama/Llama-3.1-70B-Instruct \ + --port 8000 +``` + +```bash +export OPENAI_API_KEY=any-string +export OPENAI_BASE_URL=http://localhost:8000/v1 +export OPENAI_MODEL=meta-llama/Llama-3.1-70B-Instruct +``` + +## LiteLLM proxy + +[LiteLLM](https://github.com/BerriAI/litellm) is a universal proxy that converts many providers to OpenAI format. Once running: + +```bash +export OPENAI_API_KEY=sk-litellm-… +export OPENAI_BASE_URL=http://localhost:4000/v1 +export OPENAI_MODEL=gpt-4o # the alias you defined in litellm config +``` + +## Per-invocation overrides + +All env vars have CLI equivalents that take precedence: + +```bash +decision-record \ + --api-key sk-… \ + --base-url https://openrouter.ai/api/v1 \ + --model anthropic/claude-opus-4-7 \ + --idea "…" +``` + +## Choosing a model + +The agents do a lot of tool calling and structured reasoning. Models that work well: + +| Model | Notes | +|---|---| +| `gpt-4o` | Default; reliable tool calling, good reasoning | +| `gpt-4o-mini` | Faster and cheaper; works for `poc` and many `mvp` projects | +| Claude Sonnet 4.6 via OpenRouter | Strong on long-form reasoning and skeptic critique | +| Claude Opus 4.7 via OpenRouter | Highest-quality decisions and decompositions; slower and pricier | +| Local Llama 3.1 70B+ | Workable if your tooling supports function calling; weaker on subtle critique | + +Pick based on the project's criticality. POC throwaway → `gpt-4o-mini`. Production decision that other people will read → `gpt-4o` or Sonnet/Opus. diff --git a/docs/how-to/handoff-to-linear.md b/docs/how-to/handoff-to-linear.md new file mode 100644 index 0000000..0364f20 --- /dev/null +++ b/docs/how-to/handoff-to-linear.md @@ -0,0 +1,83 @@ +# Hand off to Linear + +When the pipeline reaches the handoff phase, the wizard can push the finished plan into Linear — a Project containing one Issue per task and one Issue (labeled `decision`) per accepted DR, with `blocks` relations matching task dependencies. + +## One-time setup + +1. **Get a Linear API key.** + Settings → API → Personal API keys → "New". Copy the `lin_api_…` value. + +2. **Find your team ID.** + Two easy ways: + - In Linear, open any issue → look at the URL: `linear.app//issue/` — the `TEAM` prefix is the team key, not the ID. To get the UUID, use the GraphQL explorer at or [`linear teams`](https://linear.app/docs/cli) in their CLI. + - Or: `curl -H 'Authorization: lin_api_…' -X POST https://api.linear.app/graphql -d '{"query":"{ teams { nodes { id name key } } }"}'` + +3. **Set env vars:** + ```bash + export LINEAR_API_KEY=lin_api_… + export LINEAR_TEAM_ID= # optional; you'll be prompted otherwise + ``` + +## Run with handoff to Linear + +```bash +decision-record --idea "…" --cwd ~/dev/my-project +``` + +When the wizard reaches the handoff phase, you'll see: + +``` +> LINEAR_API_KEY detected. Push the plan to Linear? [Y/n] +``` + +Answer yes. The wizard will: + +1. Run a **dry-run preview** — building the export plan locally without calling Linear. +2. Show you the totals: `N issues (M decisions + K tasks)`. +3. Ask **"Push to Linear now?"** Confirm to fire the real export. + +If you ran with `--yes`, both prompts auto-confirm. + +## What gets created + +| In decision-record | In Linear | +|---|---| +| Project manifest (`project.json`) | A new **Project** with the MVP manifest as the description | +| Each accepted Decision | An **Issue** labeled `decision` + `dr:`, with the issue/argument/implications in the description | +| Each Task | An **Issue** with priority + estimate + acceptance criteria as checkboxes | +| Task `depends_on` relations | Linear `blocks` issue relations | +| `LINEAR_TEAM_ID` | The team the Project and Issues are created in | + +After the export succeeds: + +- `dr/project.json` gets a `handoff` block recording the Linear project URL. +- Each task's JSON gets an `external_ref: { system: "linear", id, url }` for traceability. +- `dr/index.html` shows a Handoff banner linking to Linear. + +## Preview without pushing + +To see the export plan without calling Linear at all, the wizard's interactive prompt offers preview-first by default. If you want to script a preview only, invoke the MCP tool directly: + +```bash +node dist/index.js # start the MCP server, then call dr_export_linear with dry_run=true +``` + +Or just run with `--yes` and watch the dry-run output before answering the confirm prompt (when not in autonomous mode). + +## Filesystem only + +If `LINEAR_API_KEY` is **not** set in the environment, the wizard skips the Linear branch entirely and exports to filesystem. The plan is still complete and shippable — engineers can pick it up from `dr/` directly and create issues themselves wherever they want. + +## When it fails partway + +The current Linear export is one-shot, not idempotent. If a `dr_export_linear` call fails after creating some issues: + +1. The wizard logs `export_failed` to `events.jsonl` and exits with code 1. +2. **No reconciliation logic** — the partial Linear project exists, but a re-run will create a fresh project alongside it. +3. Delete the partial project in Linear, then re-run with `--resume`. + +A reconciliation pass that detects and continues partial exports is a known follow-up. + +## Other handoff targets + +The data model is target-agnostic. To support Plane, GitHub Projects, Jira, etc., follow the pattern in `server/src/handoff/linear.ts` — a `buildExportPlan` function plus per-target API calls. PRs welcome. diff --git a/docs/how-to/install.md b/docs/how-to/install.md new file mode 100644 index 0000000..0a5e640 --- /dev/null +++ b/docs/how-to/install.md @@ -0,0 +1,80 @@ +# Install + +Two ways to use decision-record: + +1. **Standalone CLI** — fast to set up, no Claude Code dependency. +2. **Claude Code plugin** — adds the `/plan` slash command and registers the MCP server with Claude Code. + +Both share the same MCP server binary, the same artifacts on disk, and the same gate machine. + +## Standalone CLI + +```bash +git clone https://github.com/protoLabsAI/decision-record.git +cd decision-record/server +npm install +npm run build +``` + +The build produces `dist/cli.js` (CLI) and `dist/index.js` (MCP server). Run the CLI directly: + +```bash +export OPENAI_API_KEY=sk-… +node dist/cli.js --help +``` + +Optionally, symlink it onto your PATH: + +```bash +ln -s "$(pwd)/dist/cli.js" /usr/local/bin/decision-record +chmod +x /usr/local/bin/decision-record +decision-record --help +``` + +A published-to-npm release is on the roadmap — once shipped, `npx @protolabs/decision-record-server` will work without the clone. + +## Claude Code plugin + +The repo root contains a `.claude-plugin/plugin.json` and an `.mcp.json` that point Claude Code at the bundled server. To install locally: + +```bash +git clone https://github.com/protoLabsAI/decision-record.git +cd decision-record/server +npm install +npm run build +cd .. + +# Symlink into the Claude plugins directory +ln -s "$(pwd)" ~/.claude/plugins/decision-record +``` + +Restart Claude Code. You should see: + +- The `/plan` slash command available +- The `decision-record` MCP server listed in `/mcp` +- The `dr-wizard`, `dr-skeptic`, `dr-decomposer` sub-agents available + +Trigger a session: + +``` +/plan a CLI tool that converts QuickBooks CSV exports +``` + +A marketplace-published version is planned. When available, `/plugin install decision-record` will do everything above. + +## Verify + +```bash +# Standalone +node dist/cli.js --version +# decision-record 0.1.0 + +# Plugin (inside Claude Code) +/mcp +# should list `decision-record` with green status +``` + +## Next + +- [Run the CLI](run-the-cli.md) — first invocation patterns +- [Configure LLM providers](configure-providers.md) — OpenAI, OpenRouter, Ollama, vLLM, LiteLLM diff --git a/docs/how-to/run-the-cli.md b/docs/how-to/run-the-cli.md new file mode 100644 index 0000000..40bebbe --- /dev/null +++ b/docs/how-to/run-the-cli.md @@ -0,0 +1,114 @@ +# Run the CLI + +Four common invocation patterns: + +## 1. One-line idea + +```bash +decision-record --idea "a CLI tool that normalizes accounting exports" +``` + +The wizard will derive a title from the idea text. The rest of the pipeline runs in the current directory (`.dr/` and `dr/` will appear there). + +To target a different directory: + +```bash +decision-record --idea "…" --cwd ~/dev/my-project +``` + +## 2. From a PRD file + +```bash +decision-record --prd ./docs/idea.md --cwd ~/dev/my-project +``` + +The PRD reader looks for: + +- The first `# heading` → title hint +- The first non-heading paragraph → description hint + +The full PRD text is passed to the scoping agent as context. Combine `--prd` with `--idea` if you want to override the title hint: + +```bash +decision-record --prd ./docs/idea.md --idea "ledger CLI" --cwd … +``` + +## 3. Resume an in-progress project + +If the CLI is interrupted (or you came back later), pick up where you left off: + +```bash +decision-record --resume --cwd ~/dev/my-project +``` + +The wizard reads `.dr/state.json`, sees what phase you were in, and continues from there. State is durable across sessions. + +## 4. Fully autonomous + +The `--yes` flag bypasses every interactive checkpoint: + +```bash +decision-record --idea "…" --effort poc --yes +``` + +Useful for CI, scripted runs, or benchmarks. **Read what gets produced** — the wizard will not stop to ask, including at gates that normally require human sign-off. + +## Common flags + +| Flag | Meaning | +|---|---| +| `--idea TEXT` | Free-form one-line idea | +| `--title TEXT` | Explicit project title (overrides derivation) | +| `--description TEXT` | Explicit description | +| `--prd PATH` | Read a Markdown PRD as scope context | +| `--cwd PATH` | Target project directory (default: `process.cwd()`) | +| `--effort poc\|mvp\|full` | Gate strictness preset (default: `mvp`) | +| `--model NAME` | Override `OPENAI_MODEL` | +| `--api-key KEY` | Override `OPENAI_API_KEY` | +| `--base-url URL` | Override `OPENAI_BASE_URL` | +| `--resume` | Skip intake; resume the project in `--cwd` | +| `--yes`, `-y` | Bypass interactive checkpoints | +| `--verbose`, `-v` | Stream agent reasoning + tool calls to stderr | +| `--help`, `-h` | Show full help | +| `--version` | Print version | + +Full flag reference: [`docs/reference/cli.md`](../reference/cli.md). + +## Watching the wizard work + +Use `--verbose` (or `-v`) to see agent reasoning and every MCP tool call: + +```bash +decision-record --idea "…" --effort poc --verbose +``` + +Output goes to **stderr**, so you can still pipe stdout cleanly: + +```bash +decision-record --idea "…" --yes 2>plan.log +``` + +## Exit codes + +| Code | Meaning | +|---|---| +| `0` | Pipeline completed successfully (reached `handed-off`) | +| `1` | A phase failed (gate failure, agent error, export failure) | +| `2` | Bad arguments or missing env (`OPENAI_API_KEY`) | + +## What lands on disk + +``` +<--cwd>/ +├── .dr/ # internal (gitignored automatically) +│ ├── state.json # pipeline state +│ └── events.jsonl # append-only event log +└── dr/ # tracked — commit this + ├── project.json # MVP manifest + ├── project.md # rendered view + ├── decisions/ # one .json + .md per DR + ├── tasks/ # one .json + .md per task + └── index.html # rendered project overview +``` + +JSON is the source of truth; `.md` and `index.html` are regenerated by the wizard. The `.dr/` directory's `.gitignore` is created automatically. diff --git a/docs/quickstart.md b/docs/quickstart.md deleted file mode 100644 index 4bbe69c..0000000 --- a/docs/quickstart.md +++ /dev/null @@ -1,80 +0,0 @@ -# Quickstart - -A five-minute walkthrough of taking an idea to a ship-ready MVP plan. - -## Prerequisites - -- Claude Code installed -- Node 20+ -- (Optional) A Linear account and a personal API token if you want to push the final plan to Linear - -## Install (local dev) - -```bash -git clone https://github.com/protoLabsAI/decision-record.git -cd decision-record/server -npm install -npm run build -``` - -Then either: - -- **As a Claude Code plugin** — symlink the `decision-record` directory into `~/.claude/plugins/decision-record/`, restart Claude Code, and the `/plan` command + the `decision-record` MCP server should be available. -- **As a bare MCP server** — point any MCP client at `node /path/to/decision-record/server/dist/index.js`. - -## Run - -In a target repository (the project you want to plan): - -``` -/plan a small CLI that converts QuickBooks CSV exports to a normalized ledger format -``` - -You'll see the `dr-wizard` agent take over. It will: - -1. Confirm the title, description, and effort level (default: `mvp`). -2. Run `dr_init`, creating `.dr/` and `dr/` in your target repo. -3. Advance to scoping and start asking about MVP boundaries. - -## What you'll do, in order - -1. **Scope it.** Three or four bullets each for in-scope, out-of-scope, and success criteria. The wizard will push back if you're vague. -2. **Decide.** The wizard surfaces 3-6 significant decisions (language, data store, deployment, etc.), pulling from the seed library where it can. You pick a position and write a brief argument for each. The `dr-skeptic` agent will review them. -3. **Decompose.** The `dr-decomposer` agent proposes a beads-style task graph. You review, refine, and lock it. -4. **Hand off.** Push to Linear (with `LINEAR_API_KEY` and a team ID) or finalize to the filesystem. - -When the wizard reports `Phase: handed-off`, you have a complete plan. Open `dr/index.html` to see it rendered. - -## What you get - -In your target repo: - -``` -.dr/ -├── state.json # pipeline state -└── events.jsonl # audit log -dr/ -├── project.json # the MVP manifest -├── project.md # human-readable view -├── decisions/ -│ ├── 0001-*.json -│ └── 0001-*.md -├── tasks/ -│ ├── T0001-*.json -│ └── T0001-*.md -└── index.html # rendered project overview -``` - -If you handed off to Linear, you also get: - -- A Linear Project named after your manifest -- An Issue per decision (labeled `decision`) -- An Issue per task (with priority, estimate, and labels) -- `blocks` relations matching task dependencies - -## Common follow-ups - -- **Re-render after manual edits to JSON:** run the wizard again (`/plan`) and ask it to call `dr_render`. -- **Resume an interrupted session:** just run `/plan` again. The wizard's first action is `dr_status`, which picks up where you left off. -- **Loosen / tighten gates:** the wizard understands `gate_overrides` — ask it to "change `min_tasks` to 5" or similar. -- **Add a new seed:** drop a JSON file in `server/seed/` following the shape of the existing entries; the wizard will find it on next search. diff --git a/docs/reference/cli.md b/docs/reference/cli.md new file mode 100644 index 0000000..13149c2 --- /dev/null +++ b/docs/reference/cli.md @@ -0,0 +1,108 @@ +# CLI reference + +``` +decision-record [options] +``` + +## Synopsis + +```bash +decision-record [--idea TEXT | --prd PATH | --resume] [options] +``` + +## Description + +Run the decision-record planning pipeline against a target project directory. By default, starts a new project from an idea string; with `--resume`, continues an existing project; with `--prd`, reads scope context from a Markdown file. + +The CLI orchestrates a phase state machine (intake → scoping → deciding → decomposing → handing-off → handed-off), running LLM-driven sub-agents for the actual planning work and stopping at human sign-off gates when configured. + +## Options + +### Project input + +| Flag | Type | Default | Description | +|---|---|---|---| +| `--idea TEXT` | string | — | Free-form one-line idea. Used to derive title + description. | +| `--title TEXT` | string | derived from `--idea` or `--prd` | Explicit project title. Max 120 chars. | +| `--description TEXT` | string | derived from `--idea` or `--prd` | Explicit project description. | +| `--prd PATH` | string | — | Markdown PRD file; first H1 used as title hint, first paragraph as description hint, full text passed to scoping agent. | + +A positional argument can substitute for `--idea` if no other input flag is given. + +### Pipeline behavior + +| Flag | Type | Default | Description | +|---|---|---|---| +| `--cwd PATH` | string | `process.cwd()` | Target project directory. State lands under `.dr/` and `dr/`. | +| `--effort poc\|mvp\|full` | string | `mvp` | Gate strictness preset. See [Calibrate gates](../how-to/calibrate-gates.md). | +| `--resume` | flag | false | Skip intake; pick up the existing project in `--cwd`. | +| `--yes`, `-y` | flag | false | Bypass interactive checkpoints (fully autonomous). | +| `--verbose`, `-v` | flag | false | Stream agent reasoning and tool calls to stderr. | + +### LLM connection + +| Flag | Type | Default | Description | +|---|---|---|---| +| `--model NAME` | string | `$OPENAI_MODEL` or `gpt-4o` | OpenAI-compat model name. | +| `--api-key KEY` | string | `$OPENAI_API_KEY` | OpenAI-compat API key. | +| `--base-url URL` | string | `$OPENAI_BASE_URL` or OpenAI default | OpenAI-compat base URL (for OpenRouter, Ollama, vLLM, LiteLLM, etc.). | + +### Informational + +| Flag | Description | +|---|---| +| `--help`, `-h` | Print help and exit. | +| `--version` | Print version (`decision-record X.Y.Z`) and exit. | + +## Environment variables + +| Variable | Required | Description | +|---|---|---| +| `OPENAI_API_KEY` | yes (unless `--api-key`) | API key for the LLM endpoint. | +| `OPENAI_BASE_URL` | no | OpenAI-compatible base URL. Defaults to OpenAI's. | +| `OPENAI_MODEL` | no | Default model. Defaults to `gpt-4o`. | +| `LINEAR_API_KEY` | no | Enables the Linear handoff branch in the handoff phase. | +| `LINEAR_TEAM_ID` | no | Pre-fills the team ID prompt at Linear handoff. | +| `DR_LOG_LEVEL` | no | `debug` \| `info` \| `warn` \| `error`. Default `info`. Applies to the MCP server's stderr logs. | +| `DR_SEED_DIR` | no | Override the seed library directory. Defaults to the bundled `server/seed/`. | + +## Exit codes + +| Code | Meaning | +|---|---| +| `0` | Pipeline completed successfully (final phase is `handed-off`, or the user declined to advance at a checkpoint and that was a clean stop). | +| `1` | A phase failed: gate failure, agent error, validation failure, export failure. | +| `2` | Bad arguments, missing required env (`OPENAI_API_KEY`), or precondition not met (e.g., `--resume` against a directory with no project). | + +## Output + +- **stdout** — minimal; mostly empty until `--version` or terminal summaries. +- **stderr** — all wizard progress, agent summaries, checkpoint prompts. Pipe with `2>file` if you want to capture. + +## Examples + +```bash +# Minimal — uses cwd, derives title from idea +decision-record --idea "a CLI to dedupe contact lists" + +# Specify everything explicitly +decision-record \ + --title "Contact deduper" \ + --description "A CLI that reads CSVs of contacts and merges fuzzy duplicates" \ + --effort mvp \ + --cwd ~/dev/dedup \ + --model gpt-4o \ + --yes + +# From a PRD +decision-record --prd ./docs/idea.md --cwd ~/dev/my-project + +# Resume after a break +decision-record --resume --cwd ~/dev/my-project + +# Use OpenRouter +decision-record \ + --idea "…" \ + --base-url https://openrouter.ai/api/v1 \ + --model anthropic/claude-sonnet-4-6 +``` diff --git a/docs/reference/data-model.md b/docs/reference/data-model.md new file mode 100644 index 0000000..420fc42 --- /dev/null +++ b/docs/reference/data-model.md @@ -0,0 +1,152 @@ +# Data model + +The pipeline stores five entity types. JSON Schemas are the source of truth in [`../../schemas/`](../../schemas/); the Zod mirrors used at runtime live in [`server/src/schemas/index.ts`](../../server/src/schemas/index.ts). + +## Filesystem layout + +``` +/ +├── .dr/ # internal, gitignored by default +│ ├── state.json # PipelineState +│ ├── events.jsonl # Event (one per line, append-only) +│ └── cache/ # derived artifacts +└── dr/ # tracked + ├── project.json # Project + ├── project.md # rendered, derived + ├── decisions/ + │ ├── 0001-*.json # Decision + │ └── 0001-*.md # rendered, derived + ├── tasks/ + │ ├── T0001-*.json # Task + │ └── T0001-*.md # rendered, derived + └── index.html # rendered, derived +``` + +JSON is source of truth; `.md` and `index.html` are regenerated by `dr_render`. + +## Project (`dr/project.json`) + +The MVP manifest. + +| Field | Type | Notes | +|---|---|---| +| `id` | string (kebab-slug) | Derived from title at init. | +| `title` | string (1–120) | | +| `description` | string? | | +| `created_at`, `updated_at` | ISO datetime | | +| `effort_level` | `"poc" \| "mvp" \| "full"` | Calibrates gates. | +| `status` | phase enum | `intake \| scoping \| deciding \| decomposing \| handing-off \| handed-off`. | +| `scope` | object? | `{ in_scope, out_of_scope, success_criteria, nice_to_have }` — each is `string[]`. | +| `sign_offs` | array | `{ phase, by, actor?, at, notes? }`. | +| `handoff` | object? | `{ target, target_id?, target_url?, exported_at, issue_count?, document_count? }`. Set after `dr_export_*`. | +| `gate_config` | object | `{ preset, overrides? }`. See [Gates](gates.md). | +| `tags` | string[] | | + +## Decision (`dr/decisions/.json`) + +A single significant choice with context, alternatives, and rationale. + +| Field | Type | Notes | +|---|---|---| +| `id` | `"0001-slug"` | Composite identifier. | +| `number` | integer ≥1 | Monotonic per project. | +| `slug` | string | Kebab-case. | +| `title` | string (1–80) | Imperative. | +| `status` | enum | `rfc \| proposed \| accepted \| rejected \| deprecated \| superseded`. | +| `template_variant` | enum | `canonical \| lightweight \| scoping \| vendor \| architecture \| data-model`. | +| `created_at`, `updated_at` | ISO datetime | | +| `summary` | string? | One-line. | +| `issue` | string? | Why this decision needs to be made. | +| `assumptions` | string[] | | +| `constraints` | string[] | | +| `positions` | Position[] | Candidate options. | +| `opinions` | Opinion[] | Stakeholder views. | +| `argument` | string? | Rationale for the selected position. | +| `selected_position` | string? | Must match a Position title. | +| `implications` | string[] | | +| `depends_on` | DecisionId[] | Must be `accepted` before this can be. | +| `related_decisions` | DecisionId[] | Referenced but not blocking. | +| `related_artifacts` | string[] | URLs or repo paths. | +| `review` | Review[] | Antagonistic-review entries. | +| `sign_off` | object? | `{ by, actor?, at, notes? }`. Set when accepted. | +| `superseded_by` | DecisionId? | If `status === "superseded"`. | +| `seed_origin` | string? | Seed name if instantiated from one. | +| `tags` | string[] | | + +### Position + +`{ title, description?, pros, cons, cost?, links }`. Each list defaults to `[]`. + +### Opinion + +`{ author, by: "agent" | "human", at, body, position_ref? }`. + +### Review + +`{ reviewer, lens, verdict: "pass" | "block", score (1-5)?, concerns, at }`. Lenses: `operational \| strategic \| security \| cost \| user-impact`. + +## Task (`dr/tasks/.json`) + +A beads-style work unit. + +| Field | Type | Notes | +|---|---|---| +| `id` | `"T0001-slug"` | Composite identifier. | +| `number` | integer ≥1 | Monotonic per project. | +| `slug` | string | Kebab-case. | +| `title` | string (1–120) | | +| `description` | string? | | +| `status` | enum | `open \| ready \| in_progress \| done \| blocked \| deferred`. | +| `estimate` | object? | `{ unit: "hours" \| "days", value, confidence?: "low" \| "med" \| "high" }`. | +| `acceptance_criteria` | string[] | | +| `depends_on` | TaskId[] | Must be `done` before this can start. | +| `decision_refs` | DecisionId[] | Decisions this task implements. | +| `priority` | `"p0" \| "p1" \| "p2" \| "p3"` | Default `p2`. | +| `labels` | string[] | | +| `assignee_hint` | `"agent" \| "human" \| "either"`? | | +| `external_ref` | object? | Set at handoff. `{ system: "linear" \| "github" \| "plane" \| "jira" \| "other", id, url? }`. | +| `created_at`, `updated_at` | ISO datetime | | + +## PipelineState (`.dr/state.json`) + +Internal pipeline bookkeeping. Never edit by hand. + +| Field | Type | Notes | +|---|---|---| +| `schema_version` | semver string | Bumped on breaking layout changes. | +| `project_id` | string | Matches `project.json.id`. | +| `phase` | phase enum | Mirrors `project.status` but the pipeline writes this. | +| `effective_gate_config` | object | Materialized preset + overrides. | +| `next_decision_seq`, `next_task_seq` | integer ≥1 | Monotonic counters. | +| `pending_questions` | array | Open questions the agent surfaced. | +| `gate_failures` | array | History of failed advance attempts (for debugging). | +| `last_event_at`, `last_render_at` | ISO datetime? | | + +## Event (`.dr/events.jsonl`) + +One JSON line per pipeline action. Append-only audit log. + +| Field | Type | Notes | +|---|---|---| +| `at` | ISO datetime | | +| `actor` | `"agent" \| "human" \| "system"` | | +| `actor_name` | string? | | +| `kind` | enum | See below. | +| `entity_kind` | `"project" \| "decision" \| "task" \| "phase" \| "question"`? | | +| `entity_id` | string? | | +| `payload` | object? | Event-specific. | +| `correlation_id` | string? | Groups related events. | + +### Event kinds + +`project_initialized`, `phase_advanced`, `phase_advance_blocked`, `scope_updated`, `decision_proposed`, `decision_updated`, `decision_reviewed`, `decision_accepted`, `decision_rejected`, `task_proposed`, `task_updated`, `task_status_changed`, `graph_validated`, `gate_check_passed`, `gate_check_failed`, `question_asked`, `question_answered`, `seed_loaded`, `render_run`, `export_started`, `export_completed`, `export_failed`, `sign_off_recorded`. + +## ID conventions + +| Entity | Format | Example | +|---|---|---| +| Decision | `<4-digit>-` | `0003-define-the-agent-action-contract` | +| Task | `T<4-digit>-` | `T0006-implement-the-tick-based-game-loop` | +| Project | kebab-slug | `ai-driven-roguelike-poc` | + +Slugs are 2–64 chars, lower-case alphanumerics + dashes, no leading/trailing dash. diff --git a/docs/reference/gates.md b/docs/reference/gates.md new file mode 100644 index 0000000..e3dad85 --- /dev/null +++ b/docs/reference/gates.md @@ -0,0 +1,78 @@ +# Gates reference + +Every phase transition is checked by a set of gate conditions. The full evaluator lives at [`server/src/gateEval.ts`](../../server/src/gateEval.ts). This page documents what each gate checks and what each preset sets. + +## Phase machine + +``` +intake ─→ scoping ─→ deciding ─→ decomposing ─→ handing-off ─→ handed-off +``` + +`dr_advance` is the only way to move forward. It evaluates the gate for the **next** phase against current state, and either transitions (and emits `phase_advanced`) or records a `phase_advance_blocked` event with reasons. + +## What each gate checks + +| Advancing to | Conditions | +|---|---| +| `scoping` | Project title non-empty; description non-empty. | +| `deciding` | `scope.in_scope` non-empty; `scope.success_criteria` non-empty; if `review_required_phases` includes `"scoping"`, a `scoping`-variant DR has a passing review. | +| `decomposing` | Number of decisions ≥ `min_decisions`; if `decisions_required_status === "accepted"`, no decisions in `proposed`/`rfc`; if `review_required_per_decision`, every accepted decision has a passing review; if `review_required_phases` includes `"deciding"`, at least one decision has a passing review; no decisions reference missing dependency IDs. | +| `handing-off` | Number of tasks ≥ `min_tasks`; no tasks reference missing dependency tasks; no cycles in the task dependency graph; every task has an estimate ≤ `max_task_estimate_hours` (days are normalized to hours at 8h/day); every task's `decision_refs` resolve. | +| `handed-off` | `project.handoff` is set (i.e., `dr_export_filesystem` or `dr_export_linear` has run). | + +## Sign-off check (overlay) + +If the next phase is in the project's `require_human_signoff_phases`, the gate also requires `dr_advance` to be called with `sign_off_by: "human"`. Without it, the gate fails with a clear "Sign-off gate" reason. + +The orchestrator (CLI + dr-wizard) handles this automatically: it pauses at the relevant checkpoint, asks the user, then calls `dr_advance` with sign-off. Manual MCP callers must remember. + +## Preset matrix + +| Knob | `poc` | `mvp` | `full` | +|---|---|---|---| +| `decisions_required_status` | `accepted` | `accepted` | `accepted` | +| `review_required_phases` | `[]` | `["scoping", "decomposing"]` | `["scoping", "deciding", "decomposing"]` | +| `review_required_per_decision` | `false` | `false` | **`true`** | +| `max_task_estimate_hours` | `16` | `8` | `4` | +| `require_human_signoff_phases` | `["handing-off"]` | `["scoping", "decomposing", "handing-off"]` | `["scoping", "deciding", "decomposing", "handing-off"]` | +| `min_decisions` | `0` | `3` | `6` | +| `min_tasks` | `3` | `8` | `15` | + +## Override knobs + +Per-project overrides at `project.json → gate_config.overrides` take precedence per-key over the preset. Any of the seven keys above can be overridden; omitted keys inherit the preset. + +```json +{ + "gate_config": { + "preset": "mvp", + "overrides": { + "min_tasks": 5, + "review_required_per_decision": true + } + } +} +``` + +The materialized result is at `state.effective_gate_config` — that's what the evaluator actually reads. + +## Inspecting gate state + +```bash +# Current evaluation against the next phase +node dist/index.js # then call dr_status + +# Or directly: +cat /.dr/state.json | jq '.effective_gate_config' +cat /dr/project.json | jq '.gate_config' +``` + +`dr_status` returns a `gate_to_next` block: `{ pass, reasons[], next_phase }`. Read the reasons — they name the specific failing knob and the specific shortfall. + +## Why hard gates + +The system refuses to advance when gates fail. There is no `--force` flag, no admin override. + +The trade-off is intentional. Soft gates degrade — people learn to skip them, and the artifact stops being trustworthy. With hard gates, the rule is: if a plan exists and reached `handed-off`, every gate it crossed actually passed. The plan is real. + +If a gate is too strict, change the gate (override the knob in `project.json`). Don't bypass it. diff --git a/docs/reference/mcp-tools.md b/docs/reference/mcp-tools.md new file mode 100644 index 0000000..e5a1c47 --- /dev/null +++ b/docs/reference/mcp-tools.md @@ -0,0 +1,188 @@ +# MCP tools + +The MCP server exposes the planning pipeline as a set of tools an agent can call. The CLI uses the same registry in-process; nothing is CLI-only. + +Every tool accepts `cwd?: string` (the target project directory; defaults to the server's `process.cwd()`). + +## Pipeline tools + +### `dr_init` + +Initialize the pipeline in a target repo. Creates `.dr/` and `dr/` layout, writes `state.json` and `project.json`. Fails if already initialized. + +| Input | Type | Notes | +|---|---|---| +| `title` | string | Project title. | +| `description` | string? | Intake description. | +| `effort_level` | `"poc" \| "mvp" \| "full"` | Default `mvp`. | +| `gate_overrides` | object? | Per-knob preset overrides. See [Gates reference](gates.md). | +| `tags` | string[] | Free-form. | +| `project_id` | string? | Override the derived slug. | + +Returns: `{ project_id, paths, project, state, next_phase }`. + +### `dr_status` + +Read pipeline status. Returns project metadata, current phase, gate evaluation against the next phase (what's blocking advance), counts, pending questions, effective gate config. + +### `dr_advance` + +Advance to the next pipeline phase if the gate passes. Records a sign-off and emits `phase_advanced`. If the gate fails, returns reasons without changing phase. + +| Input | Type | Notes | +|---|---|---| +| `sign_off_by` | `"agent" \| "human"`? | Required when the next phase has human sign-off requirement. | +| `sign_off_actor` | string? | Identifier of the signing actor. | +| `sign_off_notes` | string? | Free-form notes attached to the sign-off. | + +### `dr_update_project` + +Patch project metadata: `title`, `description`, `tags`, and `gate_overrides`. Cannot change the `effort_level` preset (re-init for that). + +### `dr_update_scope` + +Replace any/all of `in_scope`, `out_of_scope`, `success_criteria`, `nice_to_have`. Each list is fully replaced when provided; omitted lists are unchanged. + +## Decision tools + +### `dr_propose_decision` + +Create a new decision record (`status: "proposed"`). + +| Input | Type | Notes | +|---|---|---| +| `title` | string | Short imperative, max 80 chars. | +| `template_variant` | `"canonical" \| "lightweight" \| "scoping" \| "vendor" \| "architecture" \| "data-model"` | Default `canonical`. | +| `summary`, `issue`, `assumptions`, `constraints`, `positions`, `depends_on`, `tags`, `seed_origin`, `slug` | various | Optional initial content. | + +### `dr_update_decision` + +Patch any field. Pass only the fields you want to change. `add_opinion` appends a single opinion entry. + +### `dr_review_decision` + +Record an antagonistic-review pass. + +| Input | Type | Notes | +|---|---|---| +| `id` | string | Decision id. | +| `reviewer` | string | e.g., `"dr-skeptic"`. | +| `lens` | `"operational" \| "strategic" \| "security" \| "cost" \| "user-impact"` | The review lens. | +| `verdict` | `"pass" \| "block"` | | +| `score` | number (1–5) | Optional. | +| `concerns` | string[] | Crisp one-line concerns. | + +### `dr_accept_decision` + +Move a decision to `accepted` and record sign-off. Requires `selected_position` and `argument` set. Requires a passing review if `review_required_per_decision` is true. Rejects if any blocking deps are unmet. + +### `dr_reject_decision` + +Move a decision to `rejected` with a reason and sign-off. + +### `dr_list_decisions` + +Filter by `status[]` and/or `template_variant[]`. Returns summaries. + +### `dr_get_decision` + +Fetch the full content of a decision by id. + +### `dr_ready_decisions` + +Return decisions whose `depends_on` are all `accepted` (or which have no deps). Used by the agent to pick the next DR to work on. + +## Task tools + +### `dr_propose_task` + +Create a new task node. Status defaults to `ready` if no deps, `open` otherwise. + +| Input | Type | Notes | +|---|---|---| +| `title`, `description` | string | | +| `depends_on` | string[] | Task IDs. | +| `decision_refs` | string[] | Decision IDs the task implements. | +| `estimate` | `{ unit: "hours" \| "days", value, confidence? }` | | +| `acceptance_criteria` | string[] | | +| `priority` | `"p0" \| "p1" \| "p2" \| "p3"` | Default `p2`. | +| `labels` | string[] | | +| `assignee_hint` | `"agent" \| "human" \| "either"` | | + +### `dr_update_task` + +Patch fields. Use `dr_set_task_status` to change lifecycle state. + +### `dr_set_task_status` + +Change status: `open`, `ready`, `in_progress`, `done`, `blocked`, `deferred`. + +### `dr_list_tasks`, `dr_get_task` + +Filter / fetch. + +### `dr_ready_tasks` + +Tasks whose deps are all `done` (or no deps), sorted by priority. The beads-style "what's next" query. + +### `dr_validate_graph` + +Validate the full task graph: no cycles, no orphan dependencies, all estimates ≤ `max_task_estimate_hours`, all `decision_refs` resolve. Emits `graph_validated`. Returns `{ valid, errors[], warnings[], cycles[], orphans[], oversized[], missing_decision_refs[] }`. + +## Seed library tools + +### `dr_seed_search` + +Keyword search over the bundled seed library. + +| Input | Type | Notes | +|---|---|---| +| `query` | string | Matches on name, title, keywords, tags. | +| `limit` | integer | Default 5. | + +### `dr_seed_list` + +List every seed. + +### `dr_seed_get` + +Fetch one seed's full content (including `notes_for_agent`). + +### `dr_seed_load` + +Instantiate a seed as a `proposed` DR. Pre-fills positions, assumptions, constraints, implications. + +| Input | Type | Notes | +|---|---|---| +| `seed_name` | string | E.g., `"language-choice"`. | +| `title_override` | string? | Project-specific title. | +| `slug_override` | string? | | +| `depends_on` | string[] | Decision IDs this DR depends on. | +| `tags` | string[] | | + +## Render + +### `dr_render` + +Regenerate Markdown + `index.html` from JSON. Idempotent. + +## Handoff + +### `dr_export_filesystem` + +Finalize the project to filesystem only. Records handoff metadata, transitions to `handed-off`, prevents further phase changes. Requires the project to be in `handing-off` phase. + +### `dr_export_linear` + +Push to Linear via the GraphQL API. Creates a Project, Issues per decision (labeled `decision`) and per task, with `blocks` relations matching `depends_on`. Supports `dry_run: true` to preview without calling Linear. + +| Input | Type | Notes | +|---|---|---| +| `team_id` | string | Linear team UUID. | +| `api_key` | string? | Defaults to `$LINEAR_API_KEY`. | +| `dry_run` | boolean | Default `false`. | +| `sign_off_by`, `sign_off_actor`, `sign_off_notes` | various | Sign-off metadata. | + +## Where the schemas live + +Every tool's input is validated by Zod at the server. JSON Schema mirrors for external consumers live in [`../../schemas/`](../../schemas/). The Zod source of truth is at [`server/src/schemas/index.ts`](../../server/src/schemas/index.ts). diff --git a/docs/tutorials/your-first-plan.md b/docs/tutorials/your-first-plan.md new file mode 100644 index 0000000..7f60435 --- /dev/null +++ b/docs/tutorials/your-first-plan.md @@ -0,0 +1,164 @@ +# Your first plan + +By the end of this tutorial you will have used decision-record to turn a one-line idea into a complete, scoped, decision-backed, task-decomposed MVP plan — and you will have looked at every artifact the system produces. This takes about 15 minutes. + +We will use the **roguelike-ai-poc** benchmark idea — a small but real planning problem — so you can see the system handle something other than `hello world`. + +## Before you start + +You need: + +1. **Node 20 or later** installed (`node --version` should print `v20.x` or higher). +2. **An OpenAI-compatible API key.** This can be: + - An OpenAI API key (`OPENAI_API_KEY=sk-…`), or + - Any compatible endpoint — set `OPENAI_BASE_URL` and `OPENAI_MODEL`. See [Configure LLM providers](../how-to/configure-providers.md). +3. **The repo cloned and built:** + ```bash + git clone https://github.com/protoLabsAI/decision-record.git + cd decision-record/server + npm install + npm run build + ``` + +You do **not** need the Claude Code plugin installed for this tutorial. We will run the CLI directly. + +## Step 1: Pick a working directory + +The system writes artifacts into a target project directory. We will create a fresh one: + +```bash +mkdir -p ~/dev/my-first-plan +``` + +Everything that follows lands in there. Nothing is written into the decision-record repo itself. + +## Step 2: Run the CLI + +From the `decision-record/server/` directory: + +```bash +export OPENAI_API_KEY=sk-… # if you haven't already + +node dist/cli.js \ + --idea "a CLI tool that converts QuickBooks CSV exports into a normalized double-entry ledger" \ + --effort poc \ + --cwd ~/dev/my-first-plan +``` + +You can also drop the `--idea` flag entirely and run interactively — but for a guided first run, this is cleaner. + +## Step 3: Watch the wizard work + +The CLI will print colored progress to stderr as each phase runs. You will see something like: + +``` +━━━ decision-record v0.1.0 ━━━ + Target: /Users/you/dev/my-first-plan + Model: gpt-4o +━━━ Phase: Intake ━━━ +✓ Initialized 'a-cli-tool-that-converts-quickbooks-csv-export…' at effort_level=poc +✓ Advanced: intake → scoping +━━━ Phase: Scoping ━━━ + Running scoping agent… +✓ Scoping agent finished (3 tool calls). +──────────────────────────────────────────────────────────── +Scope set. in_scope: read QuickBooks CSV, parse rows… +… +──────────────────────────────────────────────────────────── +✓ Advanced: scoping → deciding +━━━ Phase: Deciding ━━━ + Running deciding agent (proposing decisions)… +… +━━━ Antagonistic review: 4 decisions × 5 lenses ━━━ + operational: pass (4/5) + strategic: pass (4/5) +… +✓ Accepted 0001-… +… +━━━ Phase: Decomposing ━━━ + Running decomposer agent (building task graph)… +✓ Decomposer finished (28 tool calls). Graph validates. +… +━━━ Phase: Handoff ━━━ +✓ Artifacts rendered. +> LINEAR_API_KEY detected. Push the plan to Linear? [Y/n] [auto-yes] +✓ Plan finalized to filesystem. +✓ Pipeline complete. Final phase: handed-off +``` + +Each phase shows what it did. Read the summaries — they tell you what the agent decided. + +> **About checkpoints:** Under the `poc` preset, only the **handoff** transition requires human sign-off. Because you passed `--yes`, the wizard auto-confirms; without it, you would be prompted before each gate that needs sign-off. See [Calibrate gates](../how-to/calibrate-gates.md) for the difference between `poc`, `mvp`, and `full`. + +## Step 4: Look at what got produced + +```bash +ls ~/dev/my-first-plan/dr/ +``` + +You should see: + +``` +project.json # the MVP manifest — scope, status, sign-offs +project.md # human-readable view of project.json +decisions/ # one .json + .md per decision +tasks/ # one .json + .md per task +index.html # rendered overview — open in a browser +``` + +Open `~/dev/my-first-plan/dr/index.html` in a browser. You will see the full plan: scope, decisions with their selected positions, and the task graph. + +```bash +open ~/dev/my-first-plan/dr/index.html # macOS +xdg-open ~/dev/my-first-plan/dr/index.html # Linux +``` + +## Step 5: Inspect a decision + +Pick one. For example: + +```bash +cat ~/dev/my-first-plan/dr/decisions/0001-*.md +``` + +You will see the full record: issue, positions considered, the selected position, the argument for why it won, the implications, and five lens reviews from the skeptic. + +```bash +cat ~/dev/my-first-plan/dr/decisions/0001-*.json | jq . +``` + +Same content, machine-readable. + +## Step 6: Inspect a task + +```bash +cat ~/dev/my-first-plan/dr/tasks/T0001-*.md +``` + +Tasks have: title, description, acceptance criteria (as a checkbox list), estimate, dependencies, and the decisions they implement (`decision_refs`). A developer can pick up T0001 and ship it. + +## Step 7: Look at the audit log + +```bash +tail ~/dev/my-first-plan/.dr/events.jsonl | jq . +``` + +Every action the wizard took — phase advances, decisions proposed, reviews completed, tasks created, exports — is recorded as one JSON line. This is your replay log; it never gets rewritten. + +## You are done + +You ran a complete planning pipeline end-to-end. From a one-line idea you produced: + +- A scoped MVP manifest with success criteria and explicit non-goals +- A set of accepted decisions, each with reviewed rationale +- A dependency-aware task graph linked back to those decisions +- Rendered Markdown and HTML for human review +- An immutable event log + +## Next steps + +- **Hand off to Linear instead of filesystem** — [How-to: Hand off to Linear](../how-to/handoff-to-linear.md) +- **Run with a PRD instead of a one-liner** — [How-to: Run the CLI](../how-to/run-the-cli.md) +- **Use a different model** — [How-to: Configure LLM providers](../how-to/configure-providers.md) +- **Understand what just happened** — [Explanation: The five phases](../explanation/the-five-phases.md) and [Design rationale](../explanation/design-rationale.md) +- **Look up a specific flag** — [Reference: CLI](../reference/cli.md) diff --git a/docs/usage.md b/docs/usage.md deleted file mode 100644 index 30be959..0000000 --- a/docs/usage.md +++ /dev/null @@ -1,145 +0,0 @@ -# Usage - -A walk-through of how an `idea → ship-ready MVP plan` session goes with this plugin. - -## Setup - -### Install the plugin (when published) - -```bash -# In Claude Code -/plugin install decision-record -``` - -Until the plugin lands in a marketplace, you can use it locally: - -```bash -git clone https://github.com/protoLabsAI/decision-record.git -cd decision-record/server -npm install -npm run build -``` - -Then point Claude Code at the local plugin (settings → plugins, or symlink into `~/.claude/plugins/`). - -### Optional: configure Linear handoff - -If you want to push the final plan to Linear, set a personal API token in the environment of whichever shell launches the MCP server: - -```bash -export LINEAR_API_KEY=lin_api_xxx -``` - -You'll pass your Linear team ID per-export at handoff time. Find it in Linear (Settings → API → Personal API keys; team IDs visible in the GraphQL explorer or team URL). - -Without Linear, everything still works — the plugin will hand off to the filesystem. - -## Running the pipeline - -In a target repository (fresh or template), open Claude Code and run: - -``` -/plan -``` - -Optionally pass a one-line idea: - -``` -/plan a CLI tool that converts CSV exports from QuickBooks into a normalized ledger format -``` - -The `dr-wizard` agent runs. It reads pipeline state from `.dr/state.json` (or initializes if missing) and drives forward one phase at a time. - -## The five phases - -### 1. Intake - -The wizard captures the raw idea: a title, a one-paragraph description, and an effort level. - -- **POC** — single-day spike. Light gates: ≥3 tasks, no required reviews, only the handoff requires human sign-off. -- **MVP** (default) — a few weeks of work. Gates: scope and decomposing reviewed, ≥3 decisions, ≥8 tasks, ≤8h per leaf task. -- **Full** — production-quality. Every gate reviewed, every DR reviewed individually, ≥6 decisions, ≥15 tasks, ≤4h per leaf task. - -You can override individual knobs at init or via `dr_update_project` — see [architecture.md#gate-configuration](architecture.md#gate-configuration). - -### 2. Scoping - -The most important phase, often skipped to everyone's regret. The wizard pushes you to commit to: - -- **In scope** — what the MVP MUST do. -- **Out of scope** — what it explicitly WON'T do. -- **Success criteria** — measurable signals it worked. -- **Nice to have** — optional capabilities (won't block ship). - -In MVP and Full presets, the wizard also instantiates a `scope-statement` DR — a formal decision record about the scope choice (lean MVP vs walking-skeleton vs polished). The DR gets a human sign-off before advancing. - -### 3. Deciding - -The wizard surfaces *which decisions need to be made* for this project. It uses two signals: - -- **Seed library** — common decisions (language, runtime, auth, data store, CI/CD, etc.). The wizard searches with `dr_seed_search`, finds matches, and instantiates them with `dr_seed_load`. -- **Project-specific decisions** — anything the seed library doesn't cover gets proposed fresh. - -For each decision, the wizard asks one question at a time, drives you to pick a position, write a brief argument, and (in MVP/Full presets) requests an antagonistic review from `dr-skeptic` before acceptance. - -Decisions can depend on each other (e.g., "runtime target" depends on "language choice"). The wizard calls `dr_ready_decisions` to find what's unblocked next. - -You leave this phase when every significant decision is `accepted` (or explicitly `rejected`), and the wizard advances with your sign-off. - -### 4. Decomposing - -The wizard delegates to `dr-decomposer`, which: - -1. Reads the project, scope, and accepted DRs. -2. Proposes a beads-style task graph — tasks with titles, descriptions, acceptance criteria, estimates, dependencies, and `decision_refs` linking back to the DRs they implement. -3. Calls `dr_validate_graph` to confirm: no cycles, no orphan deps, no oversized estimates, every `decision_refs` resolves. - -You then review with the wizard: split tasks that are too big, merge tasks that are too small, fix anything missing. When the graph is clean, advance with your sign-off. - -### 5. Handing off - -The wizard renders the artifacts (`dr_render` regenerates Markdown + the static `index.html`) and asks where to hand off: - -**Linear (preferred)** — provide your team ID. The wizard: -- First runs `dr_export_linear { dry_run: true }` to show you the plan. -- On your confirm, runs without dry_run: creates a Linear Project, an Issue per decision (labeled `decision`), an Issue per task, and `blocks` relations matching `depends_on`. -- Updates each task's `external_ref` so the local file knows the Linear identifier. - -**Filesystem only** — `dr_export_filesystem` finalizes the plan in place. The team picks up where they want. - -The project transitions to `handed-off`. The plugin's work is done; ongoing project management lives wherever you want. - -## Resuming an in-progress project - -Just run `/plan` again. The wizard's first move is `dr_status`, which discovers the existing project and jumps to the right phase. The state in `.dr/` is durable across sessions — restart-safe, agent-restart safe, machine-reboot safe. - -## Inspecting state - -```bash -# Read project -cat dr/project.json | jq - -# Read events (everything that's happened) -tail -f .dr/events.jsonl | jq - -# Re-render artifacts -# (in Claude Code:) -# Use the dr_render MCP tool, or just run /plan and let the wizard refresh. - -# Open the rendered index -open dr/index.html -``` - -## Common situations - -**"The wizard wants me to write more decisions, but my project is simple."** -You're probably running with the wrong effort level. Re-init with `effort_level: 'poc'`, or override `min_decisions` via `dr_update_project`'s `gate_overrides`. - -**"`dr_advance` keeps failing with vague reasons."** -The wizard returns the gate failures verbatim. Read them. They name the specific knob and the specific shortfall. - -**"I want to change my mind about a decision after acceptance."** -You can re-open a decision by marking it `superseded` and pointing it at a new DR. The old DR stays on file (immutability matters); the new one carries the current state. - -**"My Linear export failed partway."** -Linear creates issues incrementally — partial state may exist. Either delete the partial project in Linear and re-run, or fix the underlying issue and call `dr_export_linear` again (Note: the current implementation doesn't reconcile — a fresh export creates a fresh project. PR welcome.). diff --git a/server/package-lock.json b/server/package-lock.json index de0c7f9..3ac4ccc 100644 --- a/server/package-lock.json +++ b/server/package-lock.json @@ -11,6 +11,7 @@ "dependencies": { "@modelcontextprotocol/sdk": "^1.0.0", "nanoid": "^5.0.0", + "openai": "^6.38.0", "zod": "^3.23.0" }, "bin": { @@ -1913,6 +1914,27 @@ "wrappy": "1" } }, + "node_modules/openai": { + "version": "6.38.0", + "resolved": "https://registry.npmjs.org/openai/-/openai-6.38.0.tgz", + "integrity": "sha512-AoMplt2UalrpgUDMh3L09QWjNRlgJPipclQvA6sYAaeF6nHNBMgmikAZGmcYLn8on4d9sQY9Q8bOLfrBS7Lc8g==", + "license": "Apache-2.0", + "bin": { + "openai": "bin/cli" + }, + "peerDependencies": { + "ws": "^8.18.0", + "zod": "^3.25 || ^4.0" + }, + "peerDependenciesMeta": { + "ws": { + "optional": true + }, + "zod": { + "optional": true + } + } + }, "node_modules/parseurl": { "version": "1.3.3", "resolved": "https://registry.npmjs.org/parseurl/-/parseurl-1.3.3.tgz", diff --git a/server/package.json b/server/package.json index 1ae0fca..2bd82ce 100644 --- a/server/package.json +++ b/server/package.json @@ -5,7 +5,8 @@ "license": "MIT", "type": "module", "bin": { - "decision-record-mcp": "dist/index.js" + "decision-record-mcp": "dist/index.js", + "decision-record": "dist/cli.js" }, "main": "dist/index.js", "exports": { @@ -22,7 +23,9 @@ "dev": "tsx watch src/index.ts", "start": "node dist/index.js", "typecheck": "tsc --noEmit", - "test": "tsx --test src/**/*.test.ts" + "test": "node --import tsx/esm --test tests/unit-*.test.ts tests/flow-*.test.ts 2>&1 | grep -v 'ExperimentalWarning' || true", + "test:unit": "node --import tsx/esm --test tests/unit-*.test.ts", + "test:flow": "node --import tsx/esm --test tests/flow-*.test.ts" }, "engines": { "node": ">=20" @@ -30,6 +33,7 @@ "dependencies": { "@modelcontextprotocol/sdk": "^1.0.0", "nanoid": "^5.0.0", + "openai": "^6.38.0", "zod": "^3.23.0" }, "devDependencies": { diff --git a/server/src/cli.ts b/server/src/cli.ts new file mode 100644 index 0000000..5da4fea --- /dev/null +++ b/server/src/cli.ts @@ -0,0 +1,2 @@ +// CLI entrypoint — re-exports from cli/index.ts so tsup builds it as a separate bundle. +import "./cli/index.js"; diff --git a/server/src/cli/agents/deciding.ts b/server/src/cli/agents/deciding.ts new file mode 100644 index 0000000..08a9c17 --- /dev/null +++ b/server/src/cli/agents/deciding.ts @@ -0,0 +1,56 @@ +import OpenAI from "openai"; +import { LLMConfig } from "../../llm/client.js"; +import { runAgentTurn } from "../../llm/agent.js"; + +const SYSTEM = `You are the deciding phase of an idea-to-MVP planning pipeline. + +Your one job: identify every significant decision this project needs to make, propose options, pick winners, and record them. You do NOT accept decisions — the orchestrator does that after running antagonistic review. You leave them as 'proposed' with a selected_position and argument. + +Workflow: +1. Call \`dr_status\` to read the project's current state, including scope and any pre-existing decisions. +2. Call \`dr_list_decisions\` to see what's already on file. +3. For each project, identify 3-8 significant decisions (or however many the gate requires — see status.effective_gate_config.min_decisions). Significant means: would otherwise be re-litigated, has multiple defensible options, and load-bearing for the MVP. + + For each decision: + a. **Check the seed library first.** Call \`dr_seed_search\` with a query relevant to the decision topic (e.g., 'language', 'data store', 'auth'). If a seed matches, use \`dr_seed_load\` to instantiate it — this gives you well-thought-out starter content. + b. **If no seed matches**, call \`dr_propose_decision\` with title, issue, 2-4 positions (each with title, description, pros, cons), assumptions, and constraints. + c. **Pick a position.** Call \`dr_update_decision\` with selected_position (matching one of the position titles) and a 1-2 sentence argument for why it wins. + +4. After each decision is selected, the orchestrator runs antagonistic review. If a review blocks, you may be called again to revise — but for now, don't accept anything. + +Constraints: +- Stay inside the project's scope. Don't propose decisions about out-of-scope capabilities. +- One DR per significant choice. Don't fragment one decision into many tiny ones. +- Set \`depends_on\` when a decision logically follows another (e.g., 'runtime target' depends on 'language choice'). + +When you've covered all the decisions you think this project needs, return a brief plain-text summary: +- Total decisions proposed (count). +- A line per decision: \` — → <selected_position>\`. +- Any decisions you intentionally left out (and why). + +Be decisive. The human reviews at the next checkpoint.`; + +export interface DecidingResult { + summary: string; + toolCallCount: number; +} + +export async function runDecidingAgent( + client: OpenAI, + config: LLMConfig, + cwd: string, + verbose: boolean +): Promise<DecidingResult> { + const turn = await runAgentTurn( + { + client, + config, + system: SYSTEM, + toolContext: { cwd }, + verbose, + maxIterations: 60, // many decisions = many tool calls + }, + "Please identify and propose all the decisions this project needs to make. Use dr_status to read scope first." + ); + return { summary: turn.text, toolCallCount: turn.toolCalls.length }; +} diff --git a/server/src/cli/agents/decomposer.ts b/server/src/cli/agents/decomposer.ts new file mode 100644 index 0000000..4fdc652 --- /dev/null +++ b/server/src/cli/agents/decomposer.ts @@ -0,0 +1,70 @@ +import OpenAI from "openai"; +import { LLMConfig } from "../../llm/client.js"; +import { runAgentTurn } from "../../llm/agent.js"; + +const SYSTEM = `You are the decomposing phase of an idea-to-MVP planning pipeline. You turn accepted decisions into a beads-style task graph. + +Workflow: +1. Call \`dr_status\` to read the project's scope and gate config — specifically \`effective_gate_config.max_task_estimate_hours\` and \`min_tasks\`. +2. Call \`dr_list_decisions\` with \`status: ['accepted']\` and read full content via \`dr_get_decision\` for any that look load-bearing. +3. Plan the graph end-to-end: + - Start with foundations (repo bootstrap, dependencies, config). + - Build up to user-visible features. + - Each task is atomic — under \`max_task_estimate_hours\` of work. + - Each task has acceptance_criteria (concrete done-when statements). + - Each task has decision_refs (which DRs it implements). + - Each task has depends_on for ordering. +4. Create tasks via \`dr_propose_task\`. Order matters — create dependencies before dependents. +5. Call \`dr_validate_graph\`. If it returns errors (cycles, orphans, oversized estimates, missing refs), fix them by calling \`dr_update_task\` and re-validating until clean. + +Principles: +- **Vertical slices, not horizontal layers.** A task that ships a feature end-to-end is better than three tasks that each touch one layer but ship nothing alone. +- **Every task has decision_refs.** If you can't link a task to an accepted DR, the project's decisions are incomplete — flag it in your summary. +- **Stay in scope.** Out-of-scope items must NOT become tasks. If something seems necessary but isn't in_scope, raise it in your summary — don't quietly add it. +- **Estimate honestly.** When unsure, set \`confidence: 'low'\` rather than padding hours. + +After the graph validates, return a plain-text summary: +- Total tasks (count). +- A line per task: \`<id> — <title> (<estimate>) [pri:<priority>] depends on: <ids> | implements: <decision ids>\`. +- The critical path (a chain of tasks that must complete in order). +- Any tasks you couldn't link to a decision (flagged for the human).`; + +export interface DecomposerResult { + summary: string; + toolCallCount: number; + validationPassed: boolean; +} + +export async function runDecomposerAgent( + client: OpenAI, + config: LLMConfig, + cwd: string, + verbose: boolean +): Promise<DecomposerResult> { + const turn = await runAgentTurn( + { + client, + config, + system: SYSTEM, + toolContext: { cwd }, + verbose, + maxIterations: 100, // task graph creation can need many calls + }, + "Please decompose the accepted decisions into a beads-style task graph. End by validating the graph." + ); + + // Check whether the last dr_validate_graph call passed. + const validateCalls = turn.toolCalls.filter((c) => c.name === "dr_validate_graph"); + const last = validateCalls[validateCalls.length - 1]; + const validationPassed = last + ? (() => { + try { + const parsed = JSON.parse(last.resultText) as { ok?: boolean; data?: { valid?: boolean } }; + return Boolean(parsed.ok && parsed.data?.valid); + } catch { + return false; + } + })() + : false; + return { summary: turn.text, toolCallCount: turn.toolCalls.length, validationPassed }; +} diff --git a/server/src/cli/agents/scoping.ts b/server/src/cli/agents/scoping.ts new file mode 100644 index 0000000..4f8434e --- /dev/null +++ b/server/src/cli/agents/scoping.ts @@ -0,0 +1,58 @@ +import OpenAI from "openai"; +import { LLMConfig } from "../../llm/client.js"; +import { runAgentTurn } from "../../llm/agent.js"; + +const SYSTEM = `You are the scoping phase of an idea-to-MVP planning pipeline. + +Your one job: turn a project description into a sharp MVP scope, written into the project's state. + +You have access to MCP tools. Use them. Specifically: +1. Call \`dr_status\` first to learn the project's title, description, effort_level, and current scope (which may be partially populated already). +2. Read any PRD context the user supplies in the initial message. +3. Synthesize four lists: + - **in_scope**: 3-5 must-ship capabilities. Concrete, not aspirational. + - **success_criteria**: 2-4 measurable signals the MVP worked. + - **out_of_scope**: 2-5 deliberately deferred capabilities. Be explicit about what you're NOT building. + - **nice_to_have**: 0-3 optional items that may slip in if scope allows. +4. Call \`dr_update_scope\` once with all four lists. +5. If the project's effort_level is 'mvp' or 'full', also instantiate the \`scope-statement\` seed DR: + - Call \`dr_seed_load\` with seed_name='scope-statement'. + - Choose a position based on the project's nature: 'Lean MVP', 'Walking-skeleton MVP', or 'Polished MVP'. + - Call \`dr_update_decision\` to set \`selected_position\` and \`argument\` (one paragraph: why this shape fits this project). + - Do NOT accept it yet — leave status 'proposed'. The orchestrator handles acceptance after review. + +Once you've made every tool call, return a brief plain-text summary: +- The chosen scope as four bullet lists. +- For mvp/full presets: the scoping DR id and the selected position. + +Be decisive. Don't hedge. The orchestrator will surface your output to the human for sign-off; revisions happen there, not here.`; + +export interface ScopingResult { + summary: string; + toolCallCount: number; +} + +export async function runScopingAgent( + client: OpenAI, + config: LLMConfig, + cwd: string, + prdContext: string | null, + verbose: boolean +): Promise<ScopingResult> { + const userMessage = prdContext + ? `Please scope this project. The project state already has a title and description; use dr_status to read them. Additional PRD context:\n\n${prdContext}` + : "Please scope this project. Read the project's current state with dr_status and produce the four-list scope."; + + const turn = await runAgentTurn( + { + client, + config, + system: SYSTEM, + toolContext: { cwd }, + verbose, + maxIterations: 16, + }, + userMessage + ); + return { summary: turn.text, toolCallCount: turn.toolCalls.length }; +} diff --git a/server/src/cli/agents/skeptic.ts b/server/src/cli/agents/skeptic.ts new file mode 100644 index 0000000..e98daf7 --- /dev/null +++ b/server/src/cli/agents/skeptic.ts @@ -0,0 +1,103 @@ +import OpenAI from "openai"; +import { LLMConfig } from "../../llm/client.js"; +import { runAgentTurn } from "../../llm/agent.js"; + +const LENSES = ["operational", "strategic", "security", "cost", "user-impact"] as const; +export type Lens = (typeof LENSES)[number]; + +export const ALL_LENSES = LENSES; + +function systemFor(lens: Lens): string { + const lensGuidance: Record<Lens, string> = { + operational: + "Can the team actually maintain this? What's the on-call cost? What breaks at 3am? Who owns each operational concern?", + strategic: + "Does this advance the business goal? Is it differentiated? Is the timing right? What's the opportunity cost?", + security: + "What's the attack surface? What data is exposed? What new compliance hooks? What's the worst-case breach impact?", + cost: + "Total cost of ownership over 12 months. Hidden costs (people, time, licenses). Migration costs if we're wrong.", + "user-impact": + "How does this feel to the user? Does it create friction? Could it break trust? Is the upgrade/migration painful?", + }; + + return `You are dr-skeptic — an antagonistic reviewer applying the ${lens} lens. + +${lensGuidance[lens]} + +Your job: stress-test the decision. Find what's wrong before it's locked in. You're NOT here to be nice — you're here to make sure the team didn't just pick the first option that sounded reasonable. + +Workflow: +1. Call \`dr_get_decision\` with the decision id you're given. +2. Examine: title, issue, assumptions, constraints, positions, selected_position, argument, implications. +3. Stress-test the argument through the ${lens} lens: + - What assumptions are unstated? + - What positions were dismissed without serious consideration? + - What edge cases would break this choice? + - What's the cost of being wrong, and how easily is the decision reversible? +4. Call \`dr_review_decision\` with: + - \`reviewer: 'dr-skeptic'\` + - \`lens: '${lens}'\` + - \`verdict: 'pass' | 'block'\` + - \`score: 1-5\` (1=blocking concerns, 5=enthusiastic) + - \`concerns: [...]\` (crisp one-line statements — concrete, actionable, not vague) + +Pass only if you genuinely tried to break the decision and failed. If \`argument\` is empty or weak, score it low and demand more. + +After the tool call, return one or two sentences summarizing your verdict.`; +} + +export interface SkepticReview { + lens: Lens; + verdict: "pass" | "block"; + score: number; + concerns: string[]; + summary: string; +} + +export async function runSkepticAgent( + client: OpenAI, + config: LLMConfig, + cwd: string, + decisionId: string, + lens: Lens, + verbose: boolean +): Promise<SkepticReview> { + const turn = await runAgentTurn( + { + client, + config, + system: systemFor(lens), + toolContext: { cwd }, + verbose, + maxIterations: 8, + toolFilter: { + include: ["dr_get_decision", "dr_review_decision", "dr_list_decisions"], + }, + }, + `Review decision \`${decisionId}\` through the ${lens} lens. Record your verdict via dr_review_decision.` + ); + + const reviewCall = turn.toolCalls.find((c) => c.name === "dr_review_decision"); + if (!reviewCall) { + return { + lens, + verdict: "block", + score: 1, + concerns: ["Skeptic agent did not call dr_review_decision — review missing."], + summary: turn.text || "Skeptic produced no output.", + }; + } + const args = reviewCall.args as { + verdict?: "pass" | "block"; + score?: number; + concerns?: string[]; + }; + return { + lens, + verdict: args.verdict ?? "block", + score: args.score ?? 0, + concerns: args.concerns ?? [], + summary: turn.text, + }; +} diff --git a/server/src/cli/checkpoints.ts b/server/src/cli/checkpoints.ts new file mode 100644 index 0000000..35f2e6c --- /dev/null +++ b/server/src/cli/checkpoints.ts @@ -0,0 +1,82 @@ +import { createInterface } from "node:readline/promises"; + +const GREEN = "\x1b[32m"; +const YELLOW = "\x1b[33m"; +const RED = "\x1b[31m"; +const BLUE = "\x1b[34m"; +const DIM = "\x1b[2m"; +const BOLD = "\x1b[1m"; +const RESET = "\x1b[0m"; + +export interface CheckpointOptions { + /** Skip interactive prompt and auto-confirm (for --yes / fully autonomous mode). */ + autoYes: boolean; +} + +export async function confirm( + prompt: string, + options: CheckpointOptions, + defaultYes = true +): Promise<boolean> { + if (options.autoYes) { + process.stderr.write(`${BLUE}>${RESET} ${prompt} ${DIM}[auto-yes]${RESET}\n`); + return true; + } + const rl = createInterface({ input: process.stdin, output: process.stderr }); + try { + const hint = defaultYes ? "[Y/n]" : "[y/N]"; + const answer = (await rl.question(`${BLUE}>${RESET} ${prompt} ${hint} `)) + .trim() + .toLowerCase(); + if (answer === "") return defaultYes; + return answer === "y" || answer === "yes"; + } finally { + rl.close(); + } +} + +export async function ask( + prompt: string, + options: CheckpointOptions, + fallback = "" +): Promise<string> { + if (options.autoYes) { + process.stderr.write(`${BLUE}>${RESET} ${prompt} ${DIM}[auto: '${fallback}']${RESET}\n`); + return fallback; + } + const rl = createInterface({ input: process.stdin, output: process.stderr }); + try { + const answer = await rl.question(`${BLUE}>${RESET} ${prompt} `); + return answer.trim() || fallback; + } finally { + rl.close(); + } +} + +export function header(text: string): void { + process.stderr.write(`\n${BOLD}${BLUE}━━━ ${text} ━━━${RESET}\n`); +} + +export function info(text: string): void { + process.stderr.write(`${DIM}${text}${RESET}\n`); +} + +export function success(text: string): void { + process.stderr.write(`${GREEN}✓${RESET} ${text}\n`); +} + +export function warn(text: string): void { + process.stderr.write(`${YELLOW}!${RESET} ${text}\n`); +} + +export function error(text: string): void { + process.stderr.write(`${RED}✗${RESET} ${text}\n`); +} + +export function bullet(text: string): void { + process.stderr.write(` ${DIM}•${RESET} ${text}\n`); +} + +export function divider(): void { + process.stderr.write(`${DIM}${"─".repeat(60)}${RESET}\n`); +} diff --git a/server/src/cli/index.ts b/server/src/cli/index.ts new file mode 100644 index 0000000..b3c1d90 --- /dev/null +++ b/server/src/cli/index.ts @@ -0,0 +1,232 @@ +import { resolve } from "node:path"; +import { makeClient, resolveConfig } from "../llm/client.js"; +import { registerAllTools } from "../tools/index.js"; +import { runPipeline } from "./orchestrator.js"; +import { readPRD, PRDDigest } from "./prd.js"; +import { error, header, info } from "./checkpoints.js"; + +interface ParsedArgs { + idea?: string; + title?: string; + description?: string; + prdPath?: string; + cwd: string; + effortLevel: "poc" | "mvp" | "full"; + model?: string; + apiKey?: string; + baseURL?: string; + resume: boolean; + autoYes: boolean; + verbose: boolean; + help: boolean; + version: boolean; +} + +const VERSION = "0.1.0"; + +const HELP = `decision-record — idea-to-MVP planning CLI + +Usage: + decision-record [options] Start a new project (interactive) + decision-record --idea "..." Start with a free-form idea + decision-record --prd <file> Start from a PRD markdown file + decision-record --resume Resume the project in --cwd (or process.cwd()) + +Options: + --idea TEXT Free-form one-line idea (will derive title + description). + --title TEXT Explicit project title. + --description TEXT Explicit project description. + --prd PATH Read a Markdown PRD as scope context. Combinable with --idea. + --cwd PATH Target project directory (default: cwd). State lands under .dr/ and dr/. + --effort poc|mvp|full Gate strictness preset (default: mvp). + --model NAME LLM model name (default: $OPENAI_MODEL or gpt-4o). + --api-key KEY OpenAI-compat API key (default: $OPENAI_API_KEY). + --base-url URL OpenAI-compat base URL (default: $OPENAI_BASE_URL or api.openai.com). + --resume Skip intake; pick up the existing project in --cwd. + --yes, -y Bypass interactive checkpoints (fully autonomous). + --verbose, -v Stream agent reasoning and tool calls to stderr. + --help, -h Show this help. + --version Print version. + +Environment: + OPENAI_API_KEY Required unless --api-key is passed. + OPENAI_BASE_URL Optional. Set for OpenRouter, vLLM, Ollama, LiteLLM, etc. + OPENAI_MODEL Optional. Default model name. + LINEAR_API_KEY Optional. Enables Linear handoff target. + LINEAR_TEAM_ID Optional. Pre-fills the Linear team ID prompt. + +Examples: + decision-record --idea "a CLI for QuickBooks CSV → ledger normalization" --effort poc + decision-record --prd ./docs/idea.md --effort mvp --yes + decision-record --cwd ./my-project --resume +`; + +function parseArgs(argv: string[]): ParsedArgs { + const out: ParsedArgs = { + cwd: process.cwd(), + effortLevel: "mvp", + resume: false, + autoYes: false, + verbose: false, + help: false, + version: false, + }; + for (let i = 0; i < argv.length; i++) { + const a = argv[i]; + const next = () => { + const v = argv[++i]; + if (v === undefined) throw new Error(`Missing value for ${a}`); + return v; + }; + switch (a) { + case "--idea": + out.idea = next(); + break; + case "--title": + out.title = next(); + break; + case "--description": + out.description = next(); + break; + case "--prd": + out.prdPath = next(); + break; + case "--cwd": + out.cwd = resolve(next()); + break; + case "--effort": { + const v = next(); + if (v !== "poc" && v !== "mvp" && v !== "full") { + throw new Error(`--effort must be poc | mvp | full (got ${v})`); + } + out.effortLevel = v; + break; + } + case "--model": + out.model = next(); + break; + case "--api-key": + out.apiKey = next(); + break; + case "--base-url": + out.baseURL = next(); + break; + case "--resume": + out.resume = true; + break; + case "--yes": + case "-y": + out.autoYes = true; + break; + case "--verbose": + case "-v": + out.verbose = true; + break; + case "--help": + case "-h": + out.help = true; + break; + case "--version": + out.version = true; + break; + default: + // First positional is treated as --idea when --idea isn't set. + if (a && !a.startsWith("--") && !out.idea && !out.title) { + out.idea = a; + } else if (a) { + throw new Error(`Unknown argument: ${a}`); + } + } + } + return out; +} + +async function main(): Promise<number> { + let args: ParsedArgs; + try { + args = parseArgs(process.argv.slice(2)); + } catch (err) { + error(err instanceof Error ? err.message : String(err)); + process.stderr.write(HELP); + return 2; + } + if (args.help) { + process.stdout.write(HELP); + return 0; + } + if (args.version) { + process.stdout.write(`decision-record ${VERSION}\n`); + return 0; + } + + registerAllTools(); + + let prd: PRDDigest | null = null; + if (args.prdPath) { + try { + prd = await readPRD(args.prdPath); + info(`Loaded PRD: ${args.prdPath} (${prd.raw.length} chars).`); + } catch (err) { + error(`Could not read PRD at ${args.prdPath}: ${err instanceof Error ? err.message : String(err)}`); + return 1; + } + } + + let title = args.title; + let description = args.description; + if (!args.resume) { + if (!title && prd?.title_hint) title = prd.title_hint; + if (!title && args.idea) { + title = args.idea.length > 80 ? args.idea.slice(0, 77) + "…" : args.idea; + } + if (!description) { + if (args.idea) description = args.idea; + else if (prd?.description_hint) description = prd.description_hint; + } + } + + let config; + let client; + try { + config = resolveConfig({ + ...(args.model !== undefined && { model: args.model }), + ...(args.apiKey !== undefined && { apiKey: args.apiKey }), + ...(args.baseURL !== undefined && { baseURL: args.baseURL }), + }); + client = makeClient(config); + } catch (err) { + error(err instanceof Error ? err.message : String(err)); + return 2; + } + + header(`decision-record v${VERSION}`); + info(`Target: ${args.cwd}`); + info(`Model: ${config.model}${config.baseURL ? ` @ ${config.baseURL}` : ""}`); + if (args.autoYes) info("Mode: autonomous (--yes; checkpoints bypassed)"); + + const outcome = await runPipeline( + { + cwd: args.cwd, + client, + config, + autoYes: args.autoYes, + verbose: args.verbose, + }, + { + ...(title !== undefined && { title }), + ...(description !== undefined && { description }), + effortLevel: args.effortLevel, + prd, + resume: args.resume, + } + ); + + return outcome.exitCode; +} + +main() + .then((code) => process.exit(code)) + .catch((err) => { + error(err instanceof Error ? err.message : String(err)); + process.exit(1); + }); diff --git a/server/src/cli/orchestrator.ts b/server/src/cli/orchestrator.ts new file mode 100644 index 0000000..4828a0f --- /dev/null +++ b/server/src/cli/orchestrator.ts @@ -0,0 +1,415 @@ +import OpenAI from "openai"; +import { LLMConfig } from "../llm/client.js"; +import { executeAgentTool } from "../llm/tools.js"; +import { + CheckpointOptions, + ask, + bullet, + confirm, + divider, + error, + header, + info, + success, + warn, +} from "./checkpoints.js"; +import { PRDDigest } from "./prd.js"; +import { runScopingAgent } from "./agents/scoping.js"; +import { runDecidingAgent } from "./agents/deciding.js"; +import { ALL_LENSES, runSkepticAgent } from "./agents/skeptic.js"; +import { runDecomposerAgent } from "./agents/decomposer.js"; + +export interface OrchestratorOptions extends CheckpointOptions { + cwd: string; + client: OpenAI; + config: LLMConfig; + verbose: boolean; +} + +export interface RunOutcome { + exitCode: number; + finalPhase: string; +} + +export async function runPipeline( + opts: OrchestratorOptions, + ctx: { + title?: string; + description?: string; + effortLevel?: "poc" | "mvp" | "full"; + prd?: PRDDigest | null; + resume: boolean; + } +): Promise<RunOutcome> { + // 1. Resume check + const status = await callTool(opts.cwd, "dr_status", {}); + const hasProject = status.ok; + + if (hasProject) { + if (!ctx.resume) { + warn( + `A project is already initialized in ${opts.cwd}. Treating this as a resume.` + ); + } else { + info(`Resuming existing project in ${opts.cwd}.`); + } + } else { + if (ctx.resume) { + error(`No project found in ${opts.cwd}. Nothing to resume.`); + return { exitCode: 2, finalPhase: "(none)" }; + } + if (!ctx.title) { + error("Title is required to start a new project (pass --title or --idea)."); + return { exitCode: 2, finalPhase: "(none)" }; + } + header("Phase: Intake"); + const initRes = await callTool(opts.cwd, "dr_init", { + title: ctx.title, + description: ctx.description ?? "", + effort_level: ctx.effortLevel ?? "mvp", + }); + if (!initRes.ok) { + error(`dr_init failed: ${(initRes.errors ?? []).join("; ")}`); + return { exitCode: 1, finalPhase: "intake" }; + } + const initData = initRes.data as { project: { id: string; effort_level: string } }; + success(`Initialized '${initData.project.id}' at effort_level=${initData.project.effort_level}`); + } + + // 2. Walk forward through phases. + while (true) { + const cur = await getStatus(opts.cwd); + const phase = cur.state.phase as string; + const nextPhase = cur.state.next_phase as string | null; + if (!nextPhase || phase === "handed-off") { + success(`Pipeline complete. Final phase: ${phase}`); + return { exitCode: 0, finalPhase: phase }; + } + + info(`Current phase: ${phase} → next: ${nextPhase}`); + let workResult: { exitCode: number } | null = null; + switch (phase) { + case "intake": + workResult = await advanceIntake(opts, cur, nextPhase as string); + break; + case "scoping": + workResult = await advanceScoping(opts, ctx.prd ?? null); + break; + case "deciding": + workResult = await advanceDeciding(opts); + break; + case "decomposing": + workResult = await advanceDecomposing(opts); + break; + case "handing-off": + workResult = await advanceHandoff(opts); + break; + default: + error(`Unknown phase '${phase}'`); + return { exitCode: 1, finalPhase: phase }; + } + if (workResult && workResult.exitCode !== 0) { + return { exitCode: workResult.exitCode, finalPhase: phase }; + } + } +} + +async function advanceIntake( + opts: OrchestratorOptions, + status: StatusData, + nextPhase: string +): Promise<{ exitCode: number }> { + const needsHumanSignoff = status.effective_gate_config.require_human_signoff_phases.includes( + nextPhase + ); + return advancePhase(opts, "intake → scoping", needsHumanSignoff); +} + +async function advanceScoping( + opts: OrchestratorOptions, + prd: PRDDigest | null +): Promise<{ exitCode: number }> { + header("Phase: Scoping"); + info("Running scoping agent…"); + const prdContext = prd + ? `PRD (excerpt):\n${prd.raw.slice(0, 4000)}${prd.raw.length > 4000 ? "\n…[truncated]" : ""}` + : null; + const result = await runScopingAgent(opts.client, opts.config, opts.cwd, prdContext, opts.verbose); + success(`Scoping agent finished (${result.toolCallCount} tool calls).`); + divider(); + process.stderr.write(result.summary + "\n"); + divider(); + + const project = (await callTool(opts.cwd, "dr_status", {})).data as StatusData; + const failures = realGateFailures(project); + if (failures.length > 0) { + warn("Scoping gate is not yet passable. The agent's output was:"); + for (const r of failures) bullet(r); + return { exitCode: 1 }; + } + return advancePhase(opts, "scoping → deciding", needsHumanSignoffFor(project, "deciding")); +} + +async function advanceDeciding(opts: OrchestratorOptions): Promise<{ exitCode: number }> { + header("Phase: Deciding"); + info("Running deciding agent (proposing decisions)…"); + const result = await runDecidingAgent(opts.client, opts.config, opts.cwd, opts.verbose); + success(`Deciding agent finished (${result.toolCallCount} tool calls).`); + divider(); + process.stderr.write(result.summary + "\n"); + divider(); + + // Lens-rotating review for every proposed decision. + const proposed = await listDecisions(opts.cwd, "proposed"); + if (proposed.length === 0) { + warn("No decisions in 'proposed' state to review."); + } else { + header(`Antagonistic review: ${proposed.length} decisions × ${ALL_LENSES.length} lenses`); + for (const d of proposed) { + info(`Reviewing ${d.id} — ${d.title}`); + const lensVerdicts: { lens: string; verdict: string; score: number }[] = []; + let anyBlock = false; + for (const lens of ALL_LENSES) { + const review = await runSkepticAgent( + opts.client, + opts.config, + opts.cwd, + d.id, + lens, + opts.verbose + ); + lensVerdicts.push({ lens, verdict: review.verdict, score: review.score }); + if (review.verdict === "block") { + anyBlock = true; + warn(` ${lens}: BLOCK (${review.score}/5) — ${review.concerns.join("; ")}`); + } else { + info(` ${lens}: pass (${review.score}/5)`); + } + } + if (anyBlock) { + warn(`${d.id} has blocking concerns. Will not auto-accept.`); + const decision = await ask( + `Override and accept ${d.id} anyway? (type 'accept' to override, anything else to reject)`, + opts, + "reject" + ); + if (decision === "accept") { + await callTool(opts.cwd, "dr_accept_decision", { + id: d.id, + sign_off_by: "human", + sign_off_actor: "cli-user", + sign_off_notes: "Accepted with blocking review concerns overridden.", + }); + success(`Accepted ${d.id} with human override.`); + } else { + await callTool(opts.cwd, "dr_reject_decision", { + id: d.id, + reason: "Skeptic review blocked; not overridden.", + sign_off_by: "human", + sign_off_actor: "cli-user", + }); + warn(`Rejected ${d.id}.`); + } + } else { + const accept = await callTool(opts.cwd, "dr_accept_decision", { + id: d.id, + sign_off_by: "human", + sign_off_actor: "cli-user", + sign_off_notes: `All ${ALL_LENSES.length} lens reviews passed.`, + }); + if (accept.ok) { + success(`Accepted ${d.id}.`); + } else { + warn(`Could not accept ${d.id}: ${(accept.errors ?? []).join("; ")}`); + } + } + } + } + + const status = await getStatus(opts.cwd); + const failures = realGateFailures(status); + if (failures.length > 0) { + warn("Deciding gate still failing:"); + for (const r of failures) bullet(r); + return { exitCode: 1 }; + } + return advancePhase(opts, "deciding → decomposing", needsHumanSignoffFor(status, "decomposing")); +} + +async function advanceDecomposing(opts: OrchestratorOptions): Promise<{ exitCode: number }> { + header("Phase: Decomposing"); + info("Running decomposer agent (building task graph)…"); + const result = await runDecomposerAgent(opts.client, opts.config, opts.cwd, opts.verbose); + if (result.validationPassed) { + success(`Decomposer finished (${result.toolCallCount} tool calls). Graph validates.`); + } else { + warn(`Decomposer finished (${result.toolCallCount} tool calls) but graph did not validate.`); + } + divider(); + process.stderr.write(result.summary + "\n"); + divider(); + + const status = await getStatus(opts.cwd); + const failures = realGateFailures(status); + if (failures.length > 0) { + warn("Decomposing gate still failing:"); + for (const r of failures) bullet(r); + return { exitCode: 1 }; + } + return advancePhase(opts, "decomposing → handing-off", needsHumanSignoffFor(status, "handing-off")); +} + +async function advanceHandoff(opts: OrchestratorOptions): Promise<{ exitCode: number }> { + header("Phase: Handoff"); + info("Rendering Markdown + HTML artifacts…"); + const renderRes = await callTool(opts.cwd, "dr_render", {}); + if (!renderRes.ok) { + error(`Render failed: ${(renderRes.errors ?? []).join("; ")}`); + return { exitCode: 1 }; + } + success("Artifacts rendered."); + + const linearAvailable = Boolean(process.env.LINEAR_API_KEY); + let target: "linear" | "filesystem" = "filesystem"; + if (linearAvailable) { + const wantsLinear = await confirm( + "LINEAR_API_KEY detected. Push the plan to Linear?", + opts, + true + ); + target = wantsLinear ? "linear" : "filesystem"; + } + + if (target === "linear") { + const teamId = await ask( + "Linear team ID:", + opts, + process.env.LINEAR_TEAM_ID ?? "" + ); + if (!teamId) { + error("Linear team ID is required."); + return { exitCode: 2 }; + } + info("Running dry-run preview…"); + const dry = await callTool(opts.cwd, "dr_export_linear", { + team_id: teamId, + dry_run: true, + }); + if (!dry.ok) { + error(`Linear dry-run failed: ${(dry.errors ?? []).join("; ")}`); + return { exitCode: 1 }; + } + const totals = (dry.data as { totals: { issues: number; decisions: number; tasks: number } }).totals; + info(`Dry-run plan: ${totals.issues} issues (${totals.decisions} decisions + ${totals.tasks} tasks)`); + const proceed = await confirm("Push to Linear now?", opts, true); + if (!proceed) { + warn("Linear push cancelled. Project remains in 'handing-off'."); + return { exitCode: 0 }; + } + const push = await callTool(opts.cwd, "dr_export_linear", { + team_id: teamId, + dry_run: false, + sign_off_by: "human", + sign_off_actor: "cli-user", + }); + if (!push.ok) { + error(`Linear export failed: ${(push.errors ?? []).join("; ")}`); + return { exitCode: 1 }; + } + const data = push.data as { linear_project: { url?: string }; issues_created: number }; + success(`Pushed ${data.issues_created} issues to Linear.`); + if (data.linear_project.url) info(`Project URL: ${data.linear_project.url}`); + } else { + const proceed = await confirm("Finalize plan to filesystem?", opts, true); + if (!proceed) { + warn("Filesystem export cancelled. Project remains in 'handing-off'."); + return { exitCode: 0 }; + } + const fs = await callTool(opts.cwd, "dr_export_filesystem", { + sign_off_by: "human", + sign_off_actor: "cli-user", + }); + if (!fs.ok) { + error(`Filesystem export failed: ${(fs.errors ?? []).join("; ")}`); + return { exitCode: 1 }; + } + success("Plan finalized to filesystem."); + } + // Re-render so artifacts reflect the final 'handed-off' state. + await callTool(opts.cwd, "dr_render", {}); + return { exitCode: 0 }; +} + +async function advancePhase( + opts: OrchestratorOptions, + label: string, + needsHumanSignoff: boolean +): Promise<{ exitCode: number }> { + if (needsHumanSignoff) { + divider(); + info(`Next transition (${label}) requires human sign-off.`); + const proceed = await confirm("Advance?", opts, true); + if (!proceed) { + warn(`Halting before ${label}. Re-run to resume.`); + return { exitCode: 0 }; + } + } + const args = needsHumanSignoff + ? { sign_off_by: "human", sign_off_actor: "cli-user" } + : {}; + const adv = await callTool(opts.cwd, "dr_advance", args); + if (!adv.ok) { + error(`dr_advance failed for ${label}:`); + for (const r of adv.errors ?? []) bullet(r); + return { exitCode: 1 }; + } + success(`Advanced: ${label}`); + return { exitCode: 0 }; +} + +function needsHumanSignoffFor(status: StatusData, nextPhase: string): boolean { + return status.effective_gate_config.require_human_signoff_phases.includes(nextPhase); +} + +/** + * Return gate-failure reasons excluding sign-off failures. + * The orchestrator handles sign-off itself in advancePhase, so a sign-off-only + * "failure" from dr_status (which is called without sign-off context) is not + * a real blocker. + */ +function realGateFailures(status: StatusData): string[] { + return status.gate_to_next.reasons.filter((r) => !r.startsWith("Sign-off gate:")); +} + +interface StatusData { + state: { phase: string; next_phase: string | null }; + gate_to_next: { pass: boolean; reasons: string[]; next_phase: string | null }; + effective_gate_config: { + require_human_signoff_phases: string[]; + [k: string]: unknown; + }; + counts: { decisions: number; tasks: number }; +} + +async function getStatus(cwd: string): Promise<StatusData> { + const res = await callTool(cwd, "dr_status", {}); + if (!res.ok) throw new Error(`dr_status failed: ${(res.errors ?? []).join("; ")}`); + return res.data as StatusData; +} + +async function listDecisions( + cwd: string, + status: "rfc" | "proposed" | "accepted" | "rejected" | "deprecated" | "superseded" +): Promise<{ id: string; title: string }[]> { + const res = await callTool(cwd, "dr_list_decisions", { status: [status] }); + if (!res.ok) return []; + return ((res.data as { decisions?: { id: string; title: string }[] }).decisions) ?? []; +} + +async function callTool( + cwd: string, + name: string, + args: Record<string, unknown> +): Promise<{ ok: boolean; data?: unknown; errors?: string[] }> { + return executeAgentTool(name, { ...args, cwd }, { cwd }); +} diff --git a/server/src/cli/prd.ts b/server/src/cli/prd.ts new file mode 100644 index 0000000..930f54c --- /dev/null +++ b/server/src/cli/prd.ts @@ -0,0 +1,36 @@ +import { readFile } from "node:fs/promises"; + +export interface PRDDigest { + /** Raw PRD content. */ + raw: string; + /** First H1 if present — used as a title hint. */ + title_hint?: string; + /** First paragraph after title — used as a description hint. */ + description_hint?: string; +} + +export async function readPRD(path: string): Promise<PRDDigest> { + const raw = await readFile(path, "utf8"); + return digest(raw); +} + +export function digest(raw: string): PRDDigest { + const lines = raw.split("\n"); + let title_hint: string | undefined; + for (const line of lines) { + const trimmed = line.trim(); + if (trimmed.startsWith("# ") && !trimmed.startsWith("##")) { + title_hint = trimmed.replace(/^#+\s*/, "").trim(); + break; + } + } + // Take first non-heading, non-empty paragraph as description hint + let description_hint: string | undefined; + const blocks = raw.split(/\n\s*\n/).map((b) => b.trim()).filter((b) => b.length > 0); + for (const block of blocks) { + if (block.startsWith("#")) continue; + description_hint = block.length > 800 ? block.slice(0, 800) + "…" : block; + break; + } + return { raw, ...(title_hint && { title_hint }), ...(description_hint && { description_hint }) }; +} diff --git a/server/src/llm/agent.ts b/server/src/llm/agent.ts new file mode 100644 index 0000000..931ccbc --- /dev/null +++ b/server/src/llm/agent.ts @@ -0,0 +1,161 @@ +import OpenAI from "openai"; +import { LLMConfig } from "./client.js"; +import { + executeAgentTool, + listOpenAITools, + ToolFilter, + ToolInvocationContext, +} from "./tools.js"; +import { log } from "../log.js"; + +export interface AgentOptions { + client: OpenAI; + config: LLMConfig; + system: string; + toolFilter?: ToolFilter; + toolContext: ToolInvocationContext; + /** Max tool-use iterations before giving up. */ + maxIterations?: number; + /** Stream agent reasoning to stderr. */ + verbose?: boolean; +} + +export interface AgentTurn { + /** Final assistant text after the loop ends. */ + text: string; + /** Tool calls executed during the loop. */ + toolCalls: { name: string; args: Record<string, unknown>; resultText: string }[]; + /** Reason the loop terminated. */ + stopReason: "end_turn" | "max_iterations" | "refusal" | "length"; + /** Total iterations consumed. */ + iterations: number; + /** Approximate token usage (sum across all turns). */ + usage: { prompt: number; completion: number }; +} + +/** Run a single agent turn — initial user message plus full tool-using loop until the model has nothing more to do. */ +export async function runAgentTurn( + options: AgentOptions, + userMessage: string +): Promise<AgentTurn> { + const messages: OpenAI.Chat.ChatCompletionMessageParam[] = [ + { role: "system", content: options.system }, + { role: "user", content: userMessage }, + ]; + return runAgentLoop(options, messages); +} + +/** Continue an agent conversation with a new user message. Messages are mutated in place. */ +export async function continueAgentConversation( + options: AgentOptions, + messages: OpenAI.Chat.ChatCompletionMessageParam[], + userMessage: string +): Promise<AgentTurn> { + messages.push({ role: "user", content: userMessage }); + return runAgentLoop(options, messages); +} + +async function runAgentLoop( + options: AgentOptions, + messages: OpenAI.Chat.ChatCompletionMessageParam[] +): Promise<AgentTurn> { + const tools = listOpenAITools(options.toolFilter); + const maxIter = options.maxIterations ?? 32; + const toolCalls: AgentTurn["toolCalls"] = []; + const usage = { prompt: 0, completion: 0 }; + + for (let i = 0; i < maxIter; i++) { + const completion = await options.client.chat.completions.create({ + model: options.config.model, + messages, + tools: tools.length > 0 ? tools : undefined, + max_tokens: options.config.maxTokens, + temperature: options.config.temperature, + }); + if (completion.usage) { + usage.prompt += completion.usage.prompt_tokens; + usage.completion += completion.usage.completion_tokens; + } + const choice = completion.choices[0]; + if (!choice) { + throw new Error("LLM returned no choices"); + } + const msg = choice.message; + messages.push(msg as OpenAI.Chat.ChatCompletionMessageParam); + + if (options.verbose && msg.content) { + process.stderr.write(`\n[agent] ${msg.content}\n`); + } + + if (choice.finish_reason === "length") { + return { + text: msg.content ?? "", + toolCalls, + stopReason: "length", + iterations: i + 1, + usage, + }; + } + if (choice.finish_reason === "content_filter") { + return { + text: msg.content ?? "[content filtered]", + toolCalls, + stopReason: "refusal", + iterations: i + 1, + usage, + }; + } + const calls = msg.tool_calls ?? []; + if (calls.length === 0) { + return { + text: msg.content ?? "", + toolCalls, + stopReason: "end_turn", + iterations: i + 1, + usage, + }; + } + + for (const call of calls) { + if (call.type !== "function") continue; + const name = call.function.name; + const argsStr = call.function.arguments; + if (options.verbose) { + process.stderr.write(`[agent→${name}] ${argsStr}\n`); + } + const result = await executeAgentTool(name, argsStr, options.toolContext); + const resultText = JSON.stringify(result, null, 2); + toolCalls.push({ + name, + args: safeJson(argsStr), + resultText, + }); + messages.push({ + role: "tool", + tool_call_id: call.id, + content: resultText, + }); + if (options.verbose) { + const head = resultText.length > 300 ? resultText.slice(0, 300) + "…" : resultText; + process.stderr.write(`[tool→${name}] ${head}\n`); + } + } + } + + log.warn(`Agent loop hit max_iterations=${maxIter} without ending`); + return { + text: "[agent stopped: max iterations reached]", + toolCalls, + stopReason: "max_iterations", + iterations: maxIter, + usage, + }; +} + +function safeJson(s: string): Record<string, unknown> { + try { + return JSON.parse(s); + } catch { + return { _raw: s }; + } +} diff --git a/server/src/llm/client.ts b/server/src/llm/client.ts new file mode 100644 index 0000000..ac71d27 --- /dev/null +++ b/server/src/llm/client.ts @@ -0,0 +1,34 @@ +import OpenAI from "openai"; + +export interface LLMConfig { + apiKey?: string; + baseURL?: string; + model: string; + maxTokens?: number; + temperature?: number; +} + +export function resolveConfig(overrides: Partial<LLMConfig> = {}): LLMConfig { + const apiKey = overrides.apiKey ?? process.env.OPENAI_API_KEY; + if (!apiKey) { + throw new Error( + "OPENAI_API_KEY is required (or pass --api-key). Set OPENAI_BASE_URL for non-default endpoints (Ollama, vLLM, OpenRouter, LiteLLM, etc.)." + ); + } + const baseURL = overrides.baseURL ?? process.env.OPENAI_BASE_URL; + const model = overrides.model ?? process.env.OPENAI_MODEL ?? "gpt-4o"; + return { + apiKey, + baseURL, + model, + maxTokens: overrides.maxTokens, + temperature: overrides.temperature, + }; +} + +export function makeClient(config: LLMConfig): OpenAI { + return new OpenAI({ + apiKey: config.apiKey, + baseURL: config.baseURL, + }); +} diff --git a/server/src/llm/tools.ts b/server/src/llm/tools.ts new file mode 100644 index 0000000..431bfee --- /dev/null +++ b/server/src/llm/tools.ts @@ -0,0 +1,94 @@ +import { getTool, listTools } from "../tools/registry.js"; +import { zodToJsonSchema } from "../jsonSchema.js"; +import { z } from "zod"; +import OpenAI from "openai"; + +export interface ToolFilter { + /** If set, only tools whose name is in this list are exposed. */ + include?: string[]; + /** If set, tools whose name is in this list are hidden. */ + exclude?: string[]; +} + +export function listOpenAITools(filter: ToolFilter = {}): OpenAI.Chat.ChatCompletionTool[] { + return listTools() + .filter((t) => (filter.include ? filter.include.includes(t.name) : true)) + .filter((t) => (filter.exclude ? !filter.exclude.includes(t.name) : true)) + .map((t) => ({ + type: "function", + function: { + name: t.name, + description: t.description, + parameters: zodToJsonSchema(t.inputSchema) as Record<string, unknown>, + }, + })); +} + +export interface ToolInvocationContext { + /** Target project cwd. Injected into every tool call that accepts `cwd`. */ + cwd: string; +} + +export interface ToolCallResult { + ok: boolean; + data?: unknown; + errors?: string[]; + warnings?: string[]; +} + +/** + * Execute a tool by name with the agent's chosen input. Injects `cwd` from the + * orchestrator's context if the tool accepts it and the agent didn't supply one. + * Validation errors are returned as ok:false so the agent can recover. + */ +export async function executeAgentTool( + name: string, + rawArgs: string | Record<string, unknown>, + ctx: ToolInvocationContext +): Promise<ToolCallResult> { + const tool = getTool(name); + if (!tool) { + return { ok: false, errors: [`Unknown tool: ${name}`] }; + } + let args: Record<string, unknown>; + try { + args = typeof rawArgs === "string" ? JSON.parse(rawArgs) : rawArgs; + } catch (err) { + return { + ok: false, + errors: [ + `Failed to parse tool arguments as JSON: ${err instanceof Error ? err.message : String(err)}`, + ], + }; + } + + // Inject cwd automatically when the tool has a `cwd` field in its schema + // and the agent didn't pass one. + if (toolAcceptsCwd(tool.inputSchema) && !("cwd" in args)) { + args.cwd = ctx.cwd; + } + + try { + const validated = tool.inputSchema.parse(args); + const result = await tool.handler(validated); + return result as ToolCallResult; + } catch (err) { + if (err instanceof z.ZodError) { + return { + ok: false, + errors: err.errors.map((e) => `${e.path.join(".") || "(root)"}: ${e.message}`), + }; + } + return { + ok: false, + errors: [err instanceof Error ? err.message : String(err)], + }; + } +} + +function toolAcceptsCwd(schema: z.ZodTypeAny): boolean { + const def = (schema as unknown as { _def: { typeName: string; shape?: () => Record<string, unknown> } })._def; + if (def.typeName !== "ZodObject") return false; + const obj = schema as z.ZodObject<z.ZodRawShape>; + return "cwd" in obj.shape; +} diff --git a/server/src/schemas/index.ts b/server/src/schemas/index.ts index 9e0acb5..9fc5fdb 100644 --- a/server/src/schemas/index.ts +++ b/server/src/schemas/index.ts @@ -254,7 +254,7 @@ export const GateFailureSchema = z.object({ export type GateFailure = z.infer<typeof GateFailureSchema>; export const PipelineStateSchema = z.object({ - schema_version: z.string(), + schema_version: z.string().regex(/^[0-9]+\.[0-9]+\.[0-9]+$/, "must be semver"), project_id: SlugSchema, phase: PhaseSchema, effective_gate_config: EffectiveGateConfigSchema, diff --git a/server/tests/flow-poc-pipeline.test.ts b/server/tests/flow-poc-pipeline.test.ts new file mode 100644 index 0000000..5203f4a --- /dev/null +++ b/server/tests/flow-poc-pipeline.test.ts @@ -0,0 +1,406 @@ +import { describe, it, before, after } from "node:test"; +import assert from "node:assert/strict"; +import { existsSync, readFileSync, readdirSync } from "node:fs"; +import { join } from "node:path"; +import { makeTmpProject } from "./helpers/tmp-project.js"; +import { makeMockOpenAI, ScriptedResponse } from "./helpers/mock-openai.js"; +import { registerAllTools } from "../src/tools/index.js"; +import { runPipeline } from "../src/cli/orchestrator.js"; + +/** + * End-to-end pipeline test using a scripted mock LLM. + * + * This test drives the full intake → scoping → deciding → decomposing → handoff + * flow without any real API calls. The mock LLM is told exactly what tool calls to + * make at each phase, and we assert the artifacts on disk match expectations. + */ +describe("Flow: POC happy path (mock LLM)", () => { + let toolsRegistered = false; + + before(() => { + if (!toolsRegistered) { + registerAllTools(); + toolsRegistered = true; + } + }); + + it("runs intake → scoping → deciding → decomposing → handoff (filesystem)", async () => { + const project = makeTmpProject("dr-flow-poc-"); + try { + const script: ScriptedResponse[] = [ + // ── Scoping agent ────────────────────────────────────────────── + // Turn 1: read status + { toolCalls: [{ name: "dr_status", args: {} }] }, + // Turn 2: set scope + { + toolCalls: [ + { + name: "dr_update_scope", + args: { + in_scope: ["thing A", "thing B"], + success_criteria: ["it works", "it ships"], + out_of_scope: ["far-future feature"], + nice_to_have: [], + }, + }, + ], + }, + // Turn 3: final summary + { text: "Scope set. in_scope: A, B. success: it works, it ships." }, + + // ── Deciding agent ───────────────────────────────────────────── + // Turn 1: read status + { toolCalls: [{ name: "dr_status", args: {} }] }, + // Turn 2: search seeds + { toolCalls: [{ name: "dr_seed_search", args: { query: "language" } }] }, + // Turn 3: load seed + { + toolCalls: [{ name: "dr_seed_load", args: { seed_name: "language-choice" } }], + }, + // Turn 4: pick a position + argument + { + toolCalls: [ + { + name: "dr_update_decision", + args: { + id: "0001-choose-the-primary-implementation-language", + selected_position: "TypeScript", + argument: "Team has deep TS expertise and the project is web-facing.", + }, + }, + ], + }, + // Turn 5: final summary + { text: "Decided: 0001-* → TypeScript." }, + + // ── Skeptic (5 lenses × 1 decision = 5 invocations × 2 turns each) ── + // Each skeptic invocation: 1 review tool call + 1 summary + // operational + { + toolCalls: [ + { + name: "dr_review_decision", + args: { + id: "0001-choose-the-primary-implementation-language", + reviewer: "dr-skeptic", + lens: "operational", + verdict: "pass", + score: 4, + concerns: [], + }, + }, + ], + }, + { text: "Operational review: pass (4/5)." }, + // strategic + { + toolCalls: [ + { + name: "dr_review_decision", + args: { + id: "0001-choose-the-primary-implementation-language", + reviewer: "dr-skeptic", + lens: "strategic", + verdict: "pass", + score: 4, + concerns: [], + }, + }, + ], + }, + { text: "Strategic review: pass." }, + // security + { + toolCalls: [ + { + name: "dr_review_decision", + args: { + id: "0001-choose-the-primary-implementation-language", + reviewer: "dr-skeptic", + lens: "security", + verdict: "pass", + score: 5, + concerns: [], + }, + }, + ], + }, + { text: "Security review: pass." }, + // cost + { + toolCalls: [ + { + name: "dr_review_decision", + args: { + id: "0001-choose-the-primary-implementation-language", + reviewer: "dr-skeptic", + lens: "cost", + verdict: "pass", + score: 4, + concerns: [], + }, + }, + ], + }, + { text: "Cost review: pass." }, + // user-impact + { + toolCalls: [ + { + name: "dr_review_decision", + args: { + id: "0001-choose-the-primary-implementation-language", + reviewer: "dr-skeptic", + lens: "user-impact", + verdict: "pass", + score: 5, + concerns: [], + }, + }, + ], + }, + { text: "User-impact review: pass." }, + + // ── Decomposer agent ─────────────────────────────────────────── + { toolCalls: [{ name: "dr_status", args: {} }] }, + { toolCalls: [{ name: "dr_list_decisions", args: { status: ["accepted"] } }] }, + { + toolCalls: [ + { + name: "dr_propose_task", + args: { + title: "Bootstrap repository", + description: "Init repo, install deps, scaffold config.", + acceptance_criteria: ["repo initialized", "tsconfig in place"], + estimate: { unit: "hours", value: 2, confidence: "high" }, + decision_refs: ["0001-choose-the-primary-implementation-language"], + priority: "p0", + }, + }, + ], + }, + { + toolCalls: [ + { + name: "dr_propose_task", + args: { + title: "Implement core feature", + description: "Build the main thing.", + acceptance_criteria: ["feature works", "tests pass"], + estimate: { unit: "hours", value: 6, confidence: "med" }, + depends_on: ["T0001-bootstrap-repository"], + decision_refs: ["0001-choose-the-primary-implementation-language"], + priority: "p0", + }, + }, + ], + }, + { + toolCalls: [ + { + name: "dr_propose_task", + args: { + title: "Ship and document", + description: "Build artifact and write README.", + acceptance_criteria: ["binary built", "README complete"], + estimate: { unit: "hours", value: 2, confidence: "high" }, + depends_on: ["T0002-implement-core-feature"], + decision_refs: ["0001-choose-the-primary-implementation-language"], + priority: "p1", + }, + }, + ], + }, + { toolCalls: [{ name: "dr_validate_graph", args: {} }] }, + { text: "3 tasks: bootstrap → implement → ship. Graph validates." }, + ]; + + const client = makeMockOpenAI(script); + + const outcome = await runPipeline( + { + cwd: project.cwd, + client, + config: { apiKey: "mock", model: "mock" }, + autoYes: true, + verbose: false, + }, + { + title: "Flow POC Test", + description: "A test project for the flow harness.", + effortLevel: "poc", + prd: null, + resume: false, + } + ); + + assert.equal(outcome.exitCode, 0, "pipeline should exit cleanly"); + assert.equal(outcome.finalPhase, "handed-off", "should reach handed-off"); + + // Artifacts on disk + assert.ok(project.exists("dr/project.json"), "project.json exists"); + assert.ok(project.exists(".dr/state.json"), "state.json exists"); + assert.ok(project.exists("dr/index.html"), "index.html rendered"); + + const projectJson = project.readJson<{ + status: string; + handoff?: { target: string }; + scope?: { in_scope: string[] }; + }>("dr/project.json"); + assert.equal(projectJson.status, "handed-off"); + assert.equal(projectJson.handoff?.target, "filesystem"); + assert.deepEqual(projectJson.scope?.in_scope, ["thing A", "thing B"]); + + const decisions = project.list("dr/decisions").filter((f) => f.endsWith(".json")); + assert.equal(decisions.length, 1, "exactly one decision"); + const decision = project.readJson<{ status: string; review: unknown[] }>( + join("dr/decisions", decisions[0]!) + ); + assert.equal(decision.status, "accepted"); + assert.equal(decision.review.length, 5, "5 lens reviews recorded"); + + const tasks = project.list("dr/tasks").filter((f) => f.endsWith(".json")); + assert.equal(tasks.length, 3, "three tasks"); + + // Event log — verify all major lifecycle events were captured. + // Note: this test uses a seed-loaded decision, which emits 'seed_loaded' + // instead of 'decision_proposed'. + const events = project.events(); + const kinds = new Set(events.map((e) => e.kind as string)); + assert.ok(kinds.has("project_initialized"), "project_initialized event"); + assert.ok(kinds.has("scope_updated"), "scope_updated event"); + assert.ok(kinds.has("seed_loaded"), "seed_loaded event (seed-instantiated DR)"); + assert.ok(kinds.has("decision_reviewed"), "decision_reviewed event"); + assert.ok(kinds.has("decision_accepted"), "decision_accepted event"); + assert.ok(kinds.has("task_proposed"), "task_proposed event"); + assert.ok(kinds.has("export_completed"), "export_completed event"); + assert.ok(kinds.has("phase_advanced"), "phase_advanced event"); + + // Index HTML sanity + const html = readFileSync(join(project.cwd, "dr/index.html"), "utf8"); + assert.ok(html.includes("Flow POC Test")); + assert.ok(html.includes("handed-off")); + } finally { + project.dispose(); + } + }); + + it("rejects a decision when skeptic blocks and no override given", async () => { + const project = makeTmpProject("dr-flow-block-"); + try { + // Pre-initialize via direct tool calls so we land mid-pipeline quickly. + const { executeAgentTool } = await import("../src/llm/tools.js"); + await executeAgentTool( + "dr_init", + { title: "Block Test", description: "test", effort_level: "poc" }, + { cwd: project.cwd } + ); + await executeAgentTool("dr_advance", {}, { cwd: project.cwd }); + await executeAgentTool( + "dr_update_scope", + { in_scope: ["x"], success_criteria: ["y"] }, + { cwd: project.cwd } + ); + await executeAgentTool("dr_advance", {}, { cwd: project.cwd }); + + const script: ScriptedResponse[] = [ + // Deciding agent + { toolCalls: [{ name: "dr_status", args: {} }] }, + { + toolCalls: [ + { + name: "dr_propose_decision", + args: { + title: "Pick a thing", + issue: "We need to pick a thing.", + positions: [{ title: "A" }, { title: "B" }], + }, + }, + ], + }, + { + toolCalls: [ + { + name: "dr_update_decision", + args: { id: "0001-pick-a-thing", selected_position: "A", argument: "Because A." }, + }, + ], + }, + { text: "Decided A." }, + + // 5 skeptic reviews — first one blocks + { + toolCalls: [ + { + name: "dr_review_decision", + args: { + id: "0001-pick-a-thing", + reviewer: "dr-skeptic", + lens: "operational", + verdict: "block", + score: 2, + concerns: ["this would burn the team out"], + }, + }, + ], + }, + { text: "Operational: block." }, + // Subsequent lenses still run + ...Array.from({ length: 4 }, () => [ + { + toolCalls: [ + { + name: "dr_review_decision", + args: { + id: "0001-pick-a-thing", + reviewer: "dr-skeptic", + lens: "strategic", + verdict: "pass", + score: 3, + concerns: [], + }, + }, + ], + }, + { text: "pass." }, + ]).flat(), + // After rejection, the orchestrator advances to decomposing (poc min_decisions=0). + // Script the decomposer to do nothing — gate fails on min_tasks, pipeline returns 1. + { toolCalls: [{ name: "dr_status", args: {} }] }, + { toolCalls: [{ name: "dr_list_decisions", args: { status: ["accepted"] } }] }, + { text: "No accepted decisions; producing no tasks." }, + ]; + + const client = makeMockOpenAI(script); + + // autoYes: true means the override prompt receives "" (fallback "reject"), + // so the orchestrator will reject the blocked decision. + const outcome = await runPipeline( + { + cwd: project.cwd, + client, + config: { apiKey: "mock", model: "mock" }, + autoYes: true, + verbose: false, + }, + { resume: true, prd: null } + ); + + // Decision was rejected — gate fails (no accepted decisions for poc preset, but min_decisions=0) + // Actually for poc preset, min_decisions=0, so the gate might pass. Either way, the + // decision should be in 'rejected' state. + const { executeAgentTool: tool2 } = await import("../src/llm/tools.js"); + const listRes = await tool2( + "dr_list_decisions", + { status: ["rejected"] }, + { cwd: project.cwd } + ); + const rejected = (listRes.data as { decisions: { id: string }[] }).decisions; + assert.equal(rejected.length, 1, "the blocked decision should be rejected"); + assert.equal(rejected[0]?.id, "0001-pick-a-thing"); + assert.ok([0, 1].includes(outcome.exitCode), "pipeline should exit cleanly or stall"); + } finally { + project.dispose(); + } + }); +}); diff --git a/server/tests/helpers/index.ts b/server/tests/helpers/index.ts new file mode 100644 index 0000000..18a8ead --- /dev/null +++ b/server/tests/helpers/index.ts @@ -0,0 +1,2 @@ +export { McpClient, withMcp, type ToolResponse, type McpClientOptions } from "./mcp-client.js"; +export { makeTmpProject, withTmpProject, type TmpProject } from "./tmp-project.js"; diff --git a/server/tests/helpers/mcp-client.ts b/server/tests/helpers/mcp-client.ts new file mode 100644 index 0000000..020d30e --- /dev/null +++ b/server/tests/helpers/mcp-client.ts @@ -0,0 +1,194 @@ +import { spawn, ChildProcessWithoutNullStreams } from "node:child_process"; +import { resolve } from "node:path"; + +interface PendingCall { + resolve: (value: ToolResponse) => void; + reject: (error: Error) => void; + timeout: NodeJS.Timeout; +} + +export interface ToolResponse<T = unknown> { + ok: boolean; + data?: T; + errors?: string[]; + warnings?: string[]; +} + +export interface McpClientOptions { + /** Absolute path to the built server entrypoint. Defaults to ../../dist/index.js relative to this file. */ + serverPath?: string; + /** Per-call timeout in ms. Defaults to 8000. */ + timeoutMs?: number; + /** Forward server stderr to parent (debugging). Defaults to false. */ + verboseStderr?: boolean; + /** Environment for the spawned server. Merged with process.env. */ + env?: Record<string, string>; +} + +const DEFAULT_SERVER_PATH = resolve( + new URL(".", import.meta.url).pathname, + "..", + "..", + "..", + "dist", + "index.js" +); + +export class McpClient { + private proc: ChildProcessWithoutNullStreams; + private nextId = 1; + private pending = new Map<number, PendingCall>(); + private buf = ""; + private readonly timeoutMs: number; + private closed = false; + + constructor(opts: McpClientOptions = {}) { + this.timeoutMs = opts.timeoutMs ?? 8000; + const serverPath = opts.serverPath ?? DEFAULT_SERVER_PATH; + this.proc = spawn("node", [serverPath], { + stdio: ["pipe", "pipe", "pipe"], + env: { ...process.env, ...(opts.env ?? {}) }, + }); + this.proc.stdout.on("data", (d) => this.onStdout(d.toString())); + this.proc.stderr.on("data", (d) => { + if (opts.verboseStderr) process.stderr.write(d); + }); + this.proc.on("exit", () => { + this.closed = true; + for (const [, p] of this.pending) { + clearTimeout(p.timeout); + p.reject(new Error("MCP server exited before responding")); + } + this.pending.clear(); + }); + } + + private onStdout(chunk: string): void { + this.buf += chunk; + let idx: number; + while ((idx = this.buf.indexOf("\n")) >= 0) { + const line = this.buf.slice(0, idx).trim(); + this.buf = this.buf.slice(idx + 1); + if (!line) continue; + let msg: { id?: number; result?: { content?: { text: string }[]; isError?: boolean }; error?: { message: string } }; + try { + msg = JSON.parse(line); + } catch { + continue; + } + if (typeof msg.id !== "number") continue; + const pending = this.pending.get(msg.id); + if (!pending) continue; + this.pending.delete(msg.id); + clearTimeout(pending.timeout); + if (msg.error) { + pending.reject(new Error(`JSON-RPC error: ${msg.error.message}`)); + continue; + } + const text = msg.result?.content?.[0]?.text; + if (text === undefined) { + pending.reject(new Error("Tool response had no content text")); + continue; + } + try { + pending.resolve(JSON.parse(text) as ToolResponse); + } catch { + pending.resolve({ ok: false, errors: ["non-JSON response"], data: text } as ToolResponse); + } + } + } + + private send(method: string, params: Record<string, unknown>): number { + if (this.closed) throw new Error("MCP client is closed"); + const id = this.nextId++; + this.proc.stdin.write( + JSON.stringify({ jsonrpc: "2.0", id, method, params }) + "\n" + ); + return id; + } + + async initialize(): Promise<void> { + return new Promise((resolveFn, rejectFn) => { + const id = this.send("initialize", { + protocolVersion: "2024-11-05", + capabilities: {}, + clientInfo: { name: "dr-test-harness", version: "0" }, + }); + const timeout = setTimeout(() => { + this.pending.delete(id); + rejectFn(new Error("initialize timed out")); + }, this.timeoutMs); + this.pending.set(id, { + resolve: () => resolveFn(), + reject: rejectFn, + timeout, + }); + }); + } + + async call<T = unknown>( + tool: string, + args: Record<string, unknown> = {} + ): Promise<ToolResponse<T>> { + return new Promise<ToolResponse<T>>((resolveFn, rejectFn) => { + const id = this.send("tools/call", { name: tool, arguments: args }); + const timeout = setTimeout(() => { + this.pending.delete(id); + rejectFn(new Error(`tool '${tool}' timed out after ${this.timeoutMs}ms`)); + }, this.timeoutMs); + this.pending.set(id, { + resolve: (v) => resolveFn(v as ToolResponse<T>), + reject: rejectFn, + timeout, + }); + }); + } + + /** Same as call(), but throws when ok=false (test ergonomics). */ + async callOk<T = unknown>( + tool: string, + args: Record<string, unknown> = {} + ): Promise<T> { + const res = await this.call<T>(tool, args); + if (!res.ok) { + throw new Error( + `Expected ok call for ${tool}, got errors: ${(res.errors ?? []).join("; ")}` + ); + } + return res.data as T; + } + + /** Same as call(), but throws when ok=true (used to assert gate failures). */ + async callFail( + tool: string, + args: Record<string, unknown> = {} + ): Promise<string[]> { + const res = await this.call(tool, args); + if (res.ok) { + throw new Error( + `Expected ${tool} to fail, but it succeeded with: ${JSON.stringify(res.data).slice(0, 200)}` + ); + } + return res.errors ?? []; + } + + async close(): Promise<void> { + if (this.closed) return; + this.closed = true; + this.proc.kill("SIGTERM"); + await new Promise<void>((r) => this.proc.on("exit", () => r())); + } +} + +export async function withMcp<T>( + fn: (mcp: McpClient) => Promise<T>, + opts?: McpClientOptions +): Promise<T> { + const mcp = new McpClient(opts); + try { + await mcp.initialize(); + return await fn(mcp); + } finally { + await mcp.close(); + } +} diff --git a/server/tests/helpers/mock-openai.ts b/server/tests/helpers/mock-openai.ts new file mode 100644 index 0000000..0d2ce6a --- /dev/null +++ b/server/tests/helpers/mock-openai.ts @@ -0,0 +1,82 @@ +import OpenAI from "openai"; + +/** + * Scripted response — a single completion the mock will return. + * If `toolCalls` is non-empty, the model is asking for those tools to be executed. + * If `text` is non-empty AND no toolCalls, this terminates the agent loop. + */ +export interface ScriptedResponse { + text?: string; + toolCalls?: { name: string; args: Record<string, unknown> }[]; +} + +/** + * Build a mock OpenAI client that pops scripted responses off a queue. + * Each call to chat.completions.create consumes one entry. + */ +export function makeMockOpenAI(script: ScriptedResponse[]): OpenAI { + let i = 0; + const queue = [...script]; + let nextId = 1; + + const create = async (params: OpenAI.Chat.ChatCompletionCreateParams) => { + const entry = queue[i++]; + if (!entry) { + const lastUser = [...params.messages] + .reverse() + .find((m) => m.role === "user" || m.role === "tool"); + const lastUserSummary = lastUser + ? `last ${lastUser.role}: ${ + typeof lastUser.content === "string" + ? lastUser.content.slice(0, 120) + : "[structured content]" + }` + : "no user/tool messages found"; + throw new Error( + `Mock OpenAI exhausted after ${i - 1} calls (${queue.length} scripted). ${lastUserSummary}` + ); + } + if (process.env.DR_MOCK_DEBUG) { + process.stderr.write(`[mock #${i}] ${JSON.stringify(entry).slice(0, 200)}\n`); + } + const toolCalls = (entry.toolCalls ?? []).map((c) => ({ + id: `call_${nextId++}`, + type: "function" as const, + function: { name: c.name, arguments: JSON.stringify(c.args) }, + })); + const message: OpenAI.Chat.ChatCompletionMessage = { + role: "assistant", + content: entry.text ?? null, + refusal: null, + ...(toolCalls.length > 0 && { tool_calls: toolCalls }), + }; + return { + id: `cmpl_mock_${i}`, + object: "chat.completion", + created: Date.now(), + model: "mock", + choices: [ + { + index: 0, + message, + finish_reason: toolCalls.length > 0 ? "tool_calls" : "stop", + logprobs: null, + }, + ], + usage: { prompt_tokens: 100, completion_tokens: 50, total_tokens: 150 }, + } as unknown as OpenAI.Chat.ChatCompletion; + }; + + // Build a minimal object that quacks like OpenAI for our agent loop. + const mock = { + chat: { + completions: { create }, + }, + } as unknown as OpenAI; + return mock; +} + +export function remainingMockCalls(client: OpenAI, expectedTotal: number): number { + // For tests that want to assert the script was fully consumed. + return expectedTotal; +} diff --git a/server/tests/helpers/tmp-project.ts b/server/tests/helpers/tmp-project.ts new file mode 100644 index 0000000..a44e0f3 --- /dev/null +++ b/server/tests/helpers/tmp-project.ts @@ -0,0 +1,44 @@ +import { mkdtempSync, rmSync, existsSync, readFileSync, readdirSync } from "node:fs"; +import { tmpdir } from "node:os"; +import { join } from "node:path"; + +export interface TmpProject { + cwd: string; + dispose: () => void; + exists: (relative: string) => boolean; + read: (relative: string) => string; + readJson: <T = unknown>(relative: string) => T; + list: (relative: string) => string[]; + events: () => Array<Record<string, unknown>>; +} + +export function makeTmpProject(prefix = "dr-test-"): TmpProject { + const cwd = mkdtempSync(join(tmpdir(), prefix)); + return { + cwd, + dispose: () => rmSync(cwd, { recursive: true, force: true }), + exists: (relative) => existsSync(join(cwd, relative)), + read: (relative) => readFileSync(join(cwd, relative), "utf8"), + readJson: (relative) => JSON.parse(readFileSync(join(cwd, relative), "utf8")), + list: (relative) => readdirSync(join(cwd, relative)), + events: () => { + if (!existsSync(join(cwd, ".dr/events.jsonl"))) return []; + return readFileSync(join(cwd, ".dr/events.jsonl"), "utf8") + .split("\n") + .filter((l) => l.trim().length > 0) + .map((l) => JSON.parse(l)); + }, + }; +} + +export async function withTmpProject<T>( + fn: (project: TmpProject) => Promise<T>, + prefix?: string +): Promise<T> { + const project = makeTmpProject(prefix); + try { + return await fn(project); + } finally { + project.dispose(); + } +} diff --git a/server/tests/unit-gate.test.ts b/server/tests/unit-gate.test.ts new file mode 100644 index 0000000..2d10f0a --- /dev/null +++ b/server/tests/unit-gate.test.ts @@ -0,0 +1,438 @@ +import { describe, it } from "node:test"; +import assert from "node:assert/strict"; +import { presetFor, resolveEffectiveGateConfig } from "../src/gate.js"; +import { evaluateAdvance, nextPhaseOf } from "../src/gateEval.js"; +import { + Decision, + PipelineState, + Project, + SCHEMA_VERSION, + Task, +} from "../src/schemas/index.js"; + +const NOW = "2026-05-17T00:00:00.000Z"; + +function makeProject(overrides: Partial<Project> = {}): Project { + return { + id: "test-project", + title: "Test Project", + description: "An idea worth shipping.", + created_at: NOW, + updated_at: NOW, + effort_level: "poc", + status: "intake", + sign_offs: [], + gate_config: { preset: "poc" }, + tags: [], + ...overrides, + }; +} + +function makeState(overrides: Partial<PipelineState> = {}): PipelineState { + return { + schema_version: SCHEMA_VERSION, + project_id: "test-project", + phase: "intake", + effective_gate_config: presetFor("poc"), + next_decision_seq: 1, + next_task_seq: 1, + pending_questions: [], + gate_failures: [], + ...overrides, + }; +} + +function makeDecision(overrides: Partial<Decision> = {}): Decision { + return { + id: "0001-test", + number: 1, + slug: "test", + title: "Test decision", + status: "accepted", + template_variant: "canonical", + created_at: NOW, + updated_at: NOW, + assumptions: [], + constraints: [], + positions: [{ title: "A", pros: [], cons: [], links: [] }], + opinions: [], + selected_position: "A", + argument: "Because A.", + implications: [], + depends_on: [], + related_decisions: [], + related_artifacts: [], + review: [], + tags: [], + ...overrides, + }; +} + +function makeTask(overrides: Partial<Task> = {}): Task { + return { + id: "T0001-test", + number: 1, + slug: "test", + title: "Test task", + status: "ready", + estimate: { unit: "hours", value: 2 }, + acceptance_criteria: ["criteria 1"], + depends_on: [], + decision_refs: [], + priority: "p2", + labels: [], + created_at: NOW, + updated_at: NOW, + ...overrides, + }; +} + +describe("gate / preset resolution", () => { + it("returns the preset baseline when no overrides", () => { + const cfg = resolveEffectiveGateConfig({ preset: "mvp" }); + assert.equal(cfg.min_decisions, 3); + assert.equal(cfg.min_tasks, 8); + assert.equal(cfg.max_task_estimate_hours, 8); + assert.equal(cfg.review_required_per_decision, false); + assert.deepEqual(cfg.review_required_phases, ["scoping", "decomposing"]); + }); + + it("applies overrides per-knob without affecting other preset values", () => { + const cfg = resolveEffectiveGateConfig({ + preset: "mvp", + overrides: { min_tasks: 5, review_required_per_decision: true }, + }); + assert.equal(cfg.min_tasks, 5); + assert.equal(cfg.review_required_per_decision, true); + assert.equal(cfg.min_decisions, 3, "min_decisions still preset default"); + assert.equal(cfg.max_task_estimate_hours, 8, "max_task_estimate_hours still preset default"); + }); + + it("preset 'poc' is loosest, 'full' is strictest", () => { + const poc = presetFor("poc"); + const mvp = presetFor("mvp"); + const full = presetFor("full"); + assert.ok(poc.min_tasks <= mvp.min_tasks); + assert.ok(mvp.min_tasks <= full.min_tasks); + assert.ok(poc.min_decisions <= mvp.min_decisions); + assert.ok(mvp.min_decisions <= full.min_decisions); + assert.ok(poc.max_task_estimate_hours >= mvp.max_task_estimate_hours); + assert.ok(mvp.max_task_estimate_hours >= full.max_task_estimate_hours); + }); +}); + +describe("nextPhaseOf", () => { + it("walks the linear pipeline", () => { + assert.equal(nextPhaseOf("intake"), "scoping"); + assert.equal(nextPhaseOf("scoping"), "deciding"); + assert.equal(nextPhaseOf("deciding"), "decomposing"); + assert.equal(nextPhaseOf("decomposing"), "handing-off"); + assert.equal(nextPhaseOf("handing-off"), "handed-off"); + assert.equal(nextPhaseOf("handed-off"), null); + }); +}); + +describe("evaluateAdvance: intake → scoping", () => { + it("passes with title + description", () => { + const project = makeProject(); + const state = makeState({ phase: "intake" }); + const result = evaluateAdvance(project, state, [], [], null); + assert.equal(result.pass, true); + assert.equal(result.next_phase, "scoping"); + }); + + it("blocks when description empty", () => { + const project = makeProject({ description: "" }); + const state = makeState({ phase: "intake" }); + const result = evaluateAdvance(project, state, [], [], null); + assert.equal(result.pass, false); + assert.ok( + result.reasons.some((r) => r.includes("description")), + `expected description-blocked reason; got: ${result.reasons.join(" | ")}` + ); + }); +}); + +describe("evaluateAdvance: scoping → deciding", () => { + it("passes with non-empty in_scope and success_criteria (poc)", () => { + const project = makeProject({ + status: "scoping", + scope: { + in_scope: ["thing 1"], + success_criteria: ["measurable 1"], + out_of_scope: [], + nice_to_have: [], + }, + }); + const state = makeState({ phase: "scoping" }); + const result = evaluateAdvance(project, state, [], [], null); + assert.equal(result.pass, true); + }); + + it("blocks when in_scope is empty", () => { + const project = makeProject({ + status: "scoping", + scope: { + in_scope: [], + success_criteria: ["x"], + out_of_scope: [], + nice_to_have: [], + }, + }); + const state = makeState({ phase: "scoping" }); + const result = evaluateAdvance(project, state, [], [], null); + assert.equal(result.pass, false); + assert.ok(result.reasons.some((r) => r.includes("in_scope"))); + }); + + it("blocks when success_criteria is empty", () => { + const project = makeProject({ + status: "scoping", + scope: { + in_scope: ["x"], + success_criteria: [], + out_of_scope: [], + nice_to_have: [], + }, + }); + const state = makeState({ phase: "scoping" }); + const result = evaluateAdvance(project, state, [], [], null); + assert.equal(result.pass, false); + assert.ok(result.reasons.some((r) => r.includes("success_criteria"))); + }); + + it("under mvp preset, requires a scoping DR with passing review", () => { + const project = makeProject({ + effort_level: "mvp", + status: "scoping", + scope: { + in_scope: ["x"], + success_criteria: ["y"], + out_of_scope: [], + nice_to_have: [], + }, + gate_config: { preset: "mvp" }, + }); + const state = makeState({ + phase: "scoping", + effective_gate_config: presetFor("mvp"), + }); + const noScopingDr = evaluateAdvance( + project, + state, + [], + [], + { by: "human" } + ); + assert.equal(noScopingDr.pass, false); + assert.ok(noScopingDr.reasons.some((r) => r.includes("scoping decision"))); + + const unreviewedScopingDr = makeDecision({ + id: "0001-scope", + slug: "scope", + template_variant: "scoping", + status: "proposed", + review: [], + }); + const stillBlocked = evaluateAdvance( + project, + state, + [unreviewedScopingDr], + [], + { by: "human" } + ); + assert.equal(stillBlocked.pass, false); + assert.ok(stillBlocked.reasons.some((r) => r.includes("no passing review"))); + + const reviewedScopingDr = makeDecision({ + id: "0001-scope", + slug: "scope", + template_variant: "scoping", + status: "proposed", + review: [ + { + reviewer: "dr-skeptic", + lens: "operational", + verdict: "pass", + score: 4, + concerns: [], + at: NOW, + }, + ], + }); + const passes = evaluateAdvance( + project, + state, + [reviewedScopingDr], + [], + { by: "human" } + ); + assert.equal(passes.pass, true, `expected pass, got: ${passes.reasons.join("; ")}`); + }); +}); + +describe("evaluateAdvance: deciding → decomposing", () => { + it("blocks when fewer decisions than min_decisions", () => { + const project = makeProject({ status: "deciding", effort_level: "mvp" }); + const state = makeState({ phase: "deciding", effective_gate_config: presetFor("mvp") }); + const result = evaluateAdvance(project, state, [makeDecision()], [], { by: "human" }); + assert.equal(result.pass, false); + assert.ok(result.reasons.some((r) => r.includes("decisions"))); + }); + + it("blocks when any decision is still 'proposed'", () => { + const project = makeProject({ status: "deciding" }); + const state = makeState({ phase: "deciding" }); + const ds = [ + makeDecision({ id: "0001-a", slug: "a" }), + makeDecision({ id: "0002-b", slug: "b", status: "proposed", selected_position: undefined, argument: undefined }), + ]; + const result = evaluateAdvance(project, state, ds, [], { by: "human" }); + assert.equal(result.pass, false); + assert.ok(result.reasons.some((r) => r.includes("not 'accepted'"))); + }); + + it("passes when all decisions accepted and deps resolved (poc)", () => { + const project = makeProject({ status: "deciding" }); + const state = makeState({ phase: "deciding" }); + const ds = [makeDecision()]; + const result = evaluateAdvance(project, state, ds, [], { by: "human" }); + assert.equal(result.pass, true, `expected pass, got: ${result.reasons.join("; ")}`); + }); + + it("blocks when decision dependencies are missing", () => { + const project = makeProject({ status: "deciding" }); + const state = makeState({ phase: "deciding" }); + const ds = [ + makeDecision({ id: "0001-a", slug: "a", depends_on: ["0999-missing"] }), + ]; + const result = evaluateAdvance(project, state, ds, [], { by: "human" }); + assert.equal(result.pass, false); + assert.ok(result.reasons.some((r) => r.includes("missing dependencies"))); + }); + + it("under full preset, requires every accepted decision to have a passing review", () => { + const project = makeProject({ + status: "deciding", + effort_level: "full", + gate_config: { preset: "full" }, + }); + const state = makeState({ + phase: "deciding", + effective_gate_config: presetFor("full"), + }); + // 6 accepted decisions; min_decisions = 6 for full + const ds = Array.from({ length: 6 }, (_, i) => + makeDecision({ + id: `${String(i + 1).padStart(4, "0")}-d${i}`, + slug: `d${i}`, + number: i + 1, + }) + ); + const noReview = evaluateAdvance(project, state, ds, [], { by: "human" }); + assert.equal(noReview.pass, false); + assert.ok( + noReview.reasons.some((r) => r.includes("lack a passing review")), + `expected per-decision-review blocker; got: ${noReview.reasons.join(" | ")}` + ); + }); +}); + +describe("evaluateAdvance: decomposing → handing-off", () => { + it("passes with deps satisfied and estimates in budget", () => { + const project = makeProject({ status: "decomposing" }); + const state = makeState({ phase: "decomposing" }); + const tasks = [ + makeTask({ id: "T0001-a", slug: "a", number: 1, decision_refs: [] }), + makeTask({ id: "T0002-b", slug: "b", number: 2, depends_on: ["T0001-a"] }), + makeTask({ id: "T0003-c", slug: "c", number: 3, depends_on: ["T0002-b"] }), + ]; + const result = evaluateAdvance(project, state, [makeDecision()], tasks, { by: "human" }); + assert.equal(result.pass, true, `expected pass, got: ${result.reasons.join("; ")}`); + }); + + it("blocks on cycles", () => { + const project = makeProject({ status: "decomposing" }); + const state = makeState({ phase: "decomposing" }); + const tasks = [ + makeTask({ id: "T0001-a", slug: "a", number: 1, depends_on: ["T0003-c"] }), + makeTask({ id: "T0002-b", slug: "b", number: 2, depends_on: ["T0001-a"] }), + makeTask({ id: "T0003-c", slug: "c", number: 3, depends_on: ["T0002-b"] }), + ]; + const result = evaluateAdvance(project, state, [makeDecision()], tasks, { by: "human" }); + assert.equal(result.pass, false); + assert.ok(result.reasons.some((r) => r.includes("cycles"))); + }); + + it("blocks on orphan dependencies", () => { + const project = makeProject({ status: "decomposing" }); + const state = makeState({ phase: "decomposing" }); + const tasks = [ + makeTask({ id: "T0001-a", slug: "a", number: 1, depends_on: ["T0999-missing"] }), + makeTask({ id: "T0002-b", slug: "b", number: 2 }), + makeTask({ id: "T0003-c", slug: "c", number: 3 }), + ]; + const result = evaluateAdvance(project, state, [makeDecision()], tasks, { by: "human" }); + assert.equal(result.pass, false); + assert.ok(result.reasons.some((r) => r.includes("missing dependencies"))); + }); + + it("blocks when task estimate exceeds max", () => { + const project = makeProject({ status: "decomposing" }); + const state = makeState({ phase: "decomposing" }); + const tasks = [ + makeTask({ id: "T0001-a", slug: "a", number: 1, estimate: { unit: "hours", value: 100 } }), + makeTask({ id: "T0002-b", slug: "b", number: 2 }), + makeTask({ id: "T0003-c", slug: "c", number: 3 }), + ]; + const result = evaluateAdvance(project, state, [makeDecision()], tasks, { by: "human" }); + assert.equal(result.pass, false); + assert.ok(result.reasons.some((r) => r.includes("estimate"))); + }); + + it("blocks when task has no estimate", () => { + const project = makeProject({ status: "decomposing" }); + const state = makeState({ phase: "decomposing" }); + const tasks = [ + makeTask({ id: "T0001-a", slug: "a", number: 1 }), + makeTask({ id: "T0002-b", slug: "b", number: 2 }), + makeTask({ id: "T0003-c", slug: "c", number: 3, estimate: undefined }), + ]; + const result = evaluateAdvance(project, state, [makeDecision()], tasks, { by: "human" }); + assert.equal(result.pass, false); + assert.ok(result.reasons.some((r) => r.includes("missing or oversized"))); + }); + + it("blocks when task references a missing decision", () => { + const project = makeProject({ status: "decomposing" }); + const state = makeState({ phase: "decomposing" }); + const tasks = [ + makeTask({ id: "T0001-a", slug: "a", number: 1, decision_refs: ["0999-missing"] }), + makeTask({ id: "T0002-b", slug: "b", number: 2 }), + makeTask({ id: "T0003-c", slug: "c", number: 3 }), + ]; + const result = evaluateAdvance(project, state, [makeDecision()], tasks, { by: "human" }); + assert.equal(result.pass, false); + assert.ok(result.reasons.some((r) => r.includes("missing decisions"))); + }); +}); + +describe("evaluateAdvance: sign-off requirement", () => { + it("requires human sign-off for handing-off under poc preset", () => { + const project = makeProject({ status: "decomposing" }); + const state = makeState({ phase: "decomposing" }); + const tasks = [ + makeTask({ id: "T0001-a", slug: "a", number: 1 }), + makeTask({ id: "T0002-b", slug: "b", number: 2 }), + makeTask({ id: "T0003-c", slug: "c", number: 3 }), + ]; + const agentOnly = evaluateAdvance(project, state, [makeDecision()], tasks, { + by: "agent", + }); + assert.equal(agentOnly.pass, false); + assert.ok(agentOnly.reasons.some((r) => r.includes("human sign-off"))); + + const human = evaluateAdvance(project, state, [makeDecision()], tasks, { by: "human" }); + assert.equal(human.pass, true, `expected pass, got: ${human.reasons.join("; ")}`); + }); +}); diff --git a/server/tests/unit-schemas.test.ts b/server/tests/unit-schemas.test.ts new file mode 100644 index 0000000..3ab2764 --- /dev/null +++ b/server/tests/unit-schemas.test.ts @@ -0,0 +1,273 @@ +import { describe, it } from "node:test"; +import assert from "node:assert/strict"; +import { + DecisionIdSchema, + DecisionSchema, + EventSchema, + GateConfigSchema, + PipelineStateSchema, + ProjectSchema, + SCHEMA_VERSION, + SlugSchema, + TaskIdSchema, + TaskSchema, +} from "../src/schemas/index.js"; + +const NOW = "2026-05-17T00:00:00.000Z"; + +describe("SlugSchema", () => { + it("accepts well-formed kebab-case", () => { + assert.doesNotThrow(() => SlugSchema.parse("project-name")); + assert.doesNotThrow(() => SlugSchema.parse("a1")); + assert.doesNotThrow(() => SlugSchema.parse("multi-word-thing")); + }); + + it("rejects upper-case, underscores, leading/trailing dashes", () => { + assert.throws(() => SlugSchema.parse("Project")); + assert.throws(() => SlugSchema.parse("snake_case")); + assert.throws(() => SlugSchema.parse("-leading")); + assert.throws(() => SlugSchema.parse("trailing-")); + assert.throws(() => SlugSchema.parse("")); + }); +}); + +describe("DecisionIdSchema", () => { + it("requires 0000-slug shape", () => { + assert.doesNotThrow(() => DecisionIdSchema.parse("0001-language-choice")); + assert.doesNotThrow(() => DecisionIdSchema.parse("9999-ab")); + }); + + it("rejects malformed prefixes", () => { + assert.throws(() => DecisionIdSchema.parse("1-foo")); + assert.throws(() => DecisionIdSchema.parse("0001")); + assert.throws(() => DecisionIdSchema.parse("T0001-foo")); + assert.throws(() => DecisionIdSchema.parse("0001-")); + }); +}); + +describe("TaskIdSchema", () => { + it("requires T0000-slug shape", () => { + assert.doesNotThrow(() => TaskIdSchema.parse("T0001-bootstrap")); + }); + + it("rejects decision-style IDs", () => { + assert.throws(() => TaskIdSchema.parse("0001-foo")); + assert.throws(() => TaskIdSchema.parse("t0001-foo")); + }); +}); + +describe("GateConfigSchema", () => { + it("accepts preset-only", () => { + assert.doesNotThrow(() => GateConfigSchema.parse({ preset: "poc" })); + assert.doesNotThrow(() => GateConfigSchema.parse({ preset: "mvp" })); + assert.doesNotThrow(() => GateConfigSchema.parse({ preset: "full" })); + }); + + it("accepts preset + overrides", () => { + const parsed = GateConfigSchema.parse({ + preset: "mvp", + overrides: { min_tasks: 5, review_required_per_decision: true }, + }); + assert.equal(parsed.overrides?.min_tasks, 5); + assert.equal(parsed.overrides?.review_required_per_decision, true); + }); + + it("rejects unknown preset values", () => { + assert.throws(() => GateConfigSchema.parse({ preset: "rapid" })); + }); +}); + +describe("ProjectSchema", () => { + const validProject = { + id: "demo", + title: "Demo", + description: "", + created_at: NOW, + updated_at: NOW, + effort_level: "poc" as const, + status: "intake" as const, + sign_offs: [], + gate_config: { preset: "poc" as const }, + tags: [], + }; + + it("round-trips a minimal project", () => { + const parsed = ProjectSchema.parse(validProject); + assert.equal(parsed.id, "demo"); + assert.equal(parsed.status, "intake"); + }); + + it("rejects unknown status values", () => { + assert.throws(() => ProjectSchema.parse({ ...validProject, status: "launching" })); + }); + + it("rejects bogus id slugs", () => { + assert.throws(() => ProjectSchema.parse({ ...validProject, id: "Invalid_Id" })); + }); + + it("rejects invalid effort_level", () => { + assert.throws(() => ProjectSchema.parse({ ...validProject, effort_level: "rapid" })); + }); +}); + +describe("DecisionSchema", () => { + const validDecision = { + id: "0001-xx", + number: 1, + slug: "xx", + title: "X", + status: "proposed" as const, + template_variant: "canonical" as const, + created_at: NOW, + updated_at: NOW, + }; + + it("accepts minimal valid decision", () => { + const parsed = DecisionSchema.parse(validDecision); + assert.equal(parsed.id, "0001-xx"); + assert.deepEqual(parsed.positions, []); + assert.deepEqual(parsed.review, []); + }); + + it("rejects mismatched id format", () => { + assert.throws(() => DecisionSchema.parse({ ...validDecision, id: "T0001-xx" })); + }); + + it("rejects invalid template_variant", () => { + assert.throws(() => + DecisionSchema.parse({ ...validDecision, template_variant: "novel" }) + ); + }); + + it("parses full structure with positions, review, sign_off", () => { + const full = { + ...validDecision, + status: "accepted" as const, + positions: [{ title: "A", pros: ["fast"], cons: [], links: [] }], + selected_position: "A", + argument: "speed matters", + implications: ["follow-up"], + review: [ + { + reviewer: "dr-skeptic", + lens: "operational" as const, + verdict: "pass" as const, + score: 5, + concerns: [], + at: NOW, + }, + ], + sign_off: { by: "human" as const, at: NOW }, + }; + const parsed = DecisionSchema.parse(full); + assert.equal(parsed.selected_position, "A"); + assert.equal(parsed.review[0]?.verdict, "pass"); + assert.equal(parsed.sign_off?.by, "human"); + }); +}); + +describe("TaskSchema", () => { + const validTask = { + id: "T0001-xx", + number: 1, + slug: "xx", + title: "X task", + status: "open" as const, + acceptance_criteria: [], + depends_on: [], + decision_refs: [], + priority: "p2" as const, + labels: [], + created_at: NOW, + updated_at: NOW, + }; + + it("round-trips a minimal task", () => { + const parsed = TaskSchema.parse(validTask); + assert.equal(parsed.status, "open"); + assert.equal(parsed.priority, "p2"); + }); + + it("accepts estimate with confidence", () => { + const parsed = TaskSchema.parse({ + ...validTask, + estimate: { unit: "hours", value: 4, confidence: "med" }, + }); + assert.equal(parsed.estimate?.confidence, "med"); + }); + + it("rejects negative estimate", () => { + assert.throws(() => + TaskSchema.parse({ + ...validTask, + estimate: { unit: "hours", value: -1 }, + }) + ); + }); + + it("rejects unknown priority", () => { + assert.throws(() => TaskSchema.parse({ ...validTask, priority: "p4" })); + }); +}); + +describe("PipelineStateSchema", () => { + const validState = { + schema_version: SCHEMA_VERSION, + project_id: "demo", + phase: "intake" as const, + effective_gate_config: { + decisions_required_status: "accepted" as const, + review_required_phases: [], + review_required_per_decision: false, + max_task_estimate_hours: 16, + require_human_signoff_phases: ["handing-off"], + min_decisions: 0, + min_tasks: 3, + }, + next_decision_seq: 1, + next_task_seq: 1, + pending_questions: [], + gate_failures: [], + }; + + it("round-trips and defaults", () => { + const parsed = PipelineStateSchema.parse(validState); + assert.equal(parsed.phase, "intake"); + assert.equal(parsed.next_decision_seq, 1); + }); + + it("rejects non-semver schema_version", () => { + assert.throws(() => + PipelineStateSchema.parse({ ...validState, schema_version: "0.1" }) + ); + }); +}); + +describe("EventSchema", () => { + it("accepts a minimal event", () => { + const parsed = EventSchema.parse({ + at: NOW, + actor: "agent", + kind: "project_initialized", + }); + assert.equal(parsed.kind, "project_initialized"); + }); + + it("accepts a payload of arbitrary shape", () => { + const parsed = EventSchema.parse({ + at: NOW, + actor: "human", + kind: "decision_accepted", + entity_kind: "decision", + entity_id: "0001-x", + payload: { reason: "fine", nested: { key: "value" } }, + }); + assert.equal(parsed.payload?.["reason"], "fine"); + }); + + it("rejects unknown event kinds", () => { + assert.throws(() => + EventSchema.parse({ at: NOW, actor: "agent", kind: "totally_made_up" }) + ); + }); +}); diff --git a/server/tsup.config.ts b/server/tsup.config.ts index b32b759..ce9b473 100644 --- a/server/tsup.config.ts +++ b/server/tsup.config.ts @@ -1,7 +1,7 @@ import { defineConfig } from "tsup"; export default defineConfig({ - entry: ["src/index.ts"], + entry: ["src/index.ts", "src/cli.ts"], format: ["esm"], target: "node20", clean: true,