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

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.

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.

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

Build optimal LLM context windows. Priority-based assembly, token budgeting, smart truncation (HEAD/TAIL/MIDDLE). Zero mandatory dependencies. Drop into any RAG pipeline in 3 lines.

Optimal context window selection for LLM coding tools. Treats context as a constrained optimization problem, not retrieval. Beats RAG, grep, and LLM-triage baselines on real GitHub issues.

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