Zero-Entropy Lab

"Restraint is the ultimate form of digital violence."

A standard-library research laboratory for deterministic state, evidence, reliability boundaries, and edge-native execution.

Status

The Python runtime uses the standard library and keeps generated state reproducible from explicit ledgers.

Zero dependency is an implementation constraint. It is not a claim that inputs, network access, external sources, local state, or generated results are automatically trusted.

Architecture

1. Core (src/kernel/): SQLite-backed memory and deterministic state processing.
2. Protocol (src/kernel/protocol/): Local protocol experiments, transition declarations, and lifecycle commands.
3. Sensory and data inputs (src/kernel/sensory/, data/inputs/): Explicit source profiles, bounded ingestion, and archive handling.
4. Reasoning (src/kernel/cognitive/): Graph-based structural analysis and local heuristics.
5. Portal (index.html): Independent presentation surface.

Research and Evidence Surfaces

The repository separates implementation, external-source evidence, local state, and research interpretation.

• aegis-cortex/README.md is the durable guide to the Aegis reliability/evidence research surface and separates its long-lived policy from time-scoped A1–A6 artifacts.
• aegis-cortex/EVIDENCE_POLICY.md defines the current reliability-evidence vocabulary and the boundary between external risk, local preventive records, local incidents, execution evidence, and unresolved state.
• data/inputs/ARCHIVE_AND_HARVESTER.md defines current snapshot, archive, ledger, cache, and ingestion semantics for repository-owned external inputs.
• SECURITY.md defines the private security-reporting route and supported disclosure boundary.
• RELEASE_POLICY.md, CITATION.cff, and codemeta.json describe the public software publication and citation surface.

Keep these distinctions explicit:

external risk != local incident
transition declaration != transition execution
hash or HMAC result != source truth or authorization
checker success != semantic validation
repository publication != runtime reproduction
archived publication != later main revision

Verification

python tests/run_tests.py

A passing run is evidence for the tested revision, interpreter, environment, and fixtures. It is not a universal reliability or security proof. Record the exact revision and environment when a result is used as reproducibility evidence.

Optional Local Server

The server is a local research interface. It is not required for the lifecycle workflow.

Generate an ephemeral API key before starting it:

export NEXUS_API_KEY="$(python -c 'import secrets; print(secrets.token_urlsafe(32))')"
python src/kernel/protocol/nexus.py serve

The default bind address is 127.0.0.1. API requests fail closed when NEXUS_API_KEY is missing.

A non-loopback bind requires explicit operator opt-in. Do not expose the native server directly to the public Internet. Use an authenticated TLS reverse proxy and network-level access controls when remote access is intentionally enabled.

Security Boundaries

• External documents and API requests remain untrusted inputs.
• Rate limiting is not authentication.
• SHA-256 fingerprints prove content identity, not authorship or authorization.
• Generated graph state must remain reproducible from validated ledgers.
• Local heuristic labels do not establish semantic truth or production guarantees.
• Security reports follow the private process in SECURITY.md.

External Synchronization

External documents are synchronized by src/kernel/sensory/harvester.py from explicit profiles in data/inputs/source_profiles.json.

Historical inputs remain byte-preserved under data/inputs/archive/legacy-through-2026-07-11-1340.

See data/inputs/ARCHIVE_AND_HARVESTER.md for the archive contract.

Citation and Publication Identity

The DOI above identifies an archived Zero-Entropy Lab software publication. Use an exact Git revision in addition to the DOI when a result depends on a specific implementation state.

A DOI is a stable publication identifier. It does not by itself establish scientific validity, local incident evidence, execution success, semantic equivalence with later main, or independent reproduction.

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