Open-source edge engine to control API request budgets and enforce fair usage.

Runtime containment kernel for LLM agents. Enforces budget, step, retry, and circuit-breaker limits before the model call.

AI agent harness engineering tool — visualize CLAUDE.md, AGENTS.md, skills, and agent config structure

Open source AI cost tracking. Know exactly what your AI costs — per feature, per user, per project.

Core library: scoring, selection, and caching for the Context Engine

Cross-agent skill quality gate for SKILL.md files. Validates frontmatter, scores description discoverability, checks file references, enforces three-tier token budgets, and flags compatibility issues across Claude Code, VS Code/Copilot, Codex, and Cursor.

Governance layer for runtime budget, policy, and trade-off control in AI systems.

🚀 Optimize AI context retrieval with OrionGraphDB, a powerful engine that respects token budgets and delivers diverse, relevant information seamlessly.

Open-source platform for deterministic, token-aware context selection for AI agents and LLMs

A context database for AI agents. Multi-channel retrieval (semantic, lexical, structural) with MMR selection and token budget management. Built in Rust. Apache 2.0.

CLI for building, resolving, and inspecting context caches

Lightweight reverse proxy for OpenAI API with per-key token budgets, rate limiting, cost dashboards, model downgrade, and caching — deploy in 5 minutes with Docker

Token budget manager for LLM apps — track usage, enforce limits, estimate costs per user/session. Zero dependencies. OpenAI, Anthropic, Groq, Ollama.

Enforce real-time token budgets and spending limits for OpenAI, Anthropic Claude, and Google Gemini API calls in Node.js

Context engineering toolkit for LLMs — pack, cache, debug, red-team, and orchestrate context windows. Council of Experts, adversarial testing, immune system, context compiler, drift detection, multi-agent entanglement. TypeScript + Python.