#evals

Agent control plane for governed AI coding: validate changes, enforce policy gates, track findings, proofs, and evals based on your habits.

Local LLM cost-tracking proxy for OpenAI, Anthropic, Gemini, and pinned OpenRouter calls with token usage, failure, and billing-integrity receipts.

Skill invocation runner: install an Agent Skill in a fresh fixture, invoke an agent harness headlessly, and report what actually reached the model, with transcript evidence.

Control plane for orchestrating, evaluating, and improving agent work across a company

While Python SDK (formerly zeroproof): trace ingest, agent simulations, grading, and training data for post-training

Low-level agentic design patterns. Turning old engineering wisdom into reflexes your agent reaches for on its own—on any agent.

Create, evaluate, and deploy workflows from your terminal. Agent-ready.

Hey LLM, you okay? — pyramid-ordered LLM testing CLI for CI/CD. One YAML for every layer, LLM-as-a-judge gates, and A/B triage that tells prompt regressions from model drift.