zosma-qa

Project overview

agent-skills-eval tests an Agent Skill against the same prompts in two modes: with the skill loaded and without it as a baseline. A judge model grades both outputs against defined assertions, producing JSON and JSONL artifacts plus a static HTML report that shows measurable lift, failures, timing, and tool-call behavior. The project includes a command-line runner and a TypeScript SDK, supports OpenAI-compatible chat backends and custom providers, and can run in CI. Users supply both the target model and the judge model.

Project overview

Skill Conductor manages the lifecycle of an AI skill from design through distribution, requiring authors to choose an architecture pattern before writing `SKILL.md`. It supports creation, improvement, validation, third-party review, trigger-description optimization, and packaging, combining deterministic checks with benchmark tasks and evidence-backed binary quality questions. It is aimed at systematic skill authoring and review rather than a one-off prompt test.