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The scorecard grades a GitHub repository on agent legibility: how easily a coding agent can bootstrap, navigate, and validate work in it. Run it at twill.ai/score — paste a public repo URL, or install the GitHub App for private repos (analyzed with a short-lived, scoped token). Analysis is static — no dependencies installed, no code executed. It’s based on OpenAI’s agentic legibility work and runs in a sandboxed container.

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What it measures

Seven metrics, each scored 0–3 (max 21), with letter grades A (85%+), B (70%+), C (50%+), D below: A higher score means agents — Twill’s included — waste less time rediscovering your setup and produce better-verified work. The report includes concrete fixes for each low metric.