Agent Readiness

"The agent is not broken. The environment is." — Factory.ai

Measure how well a repository supports autonomous AI coding agents, and report what to fix first. Based on Factory.ai's Agent Readiness framework — 9 pillars, ~80 criteria, scored as a pass-rate and mapped to 5 gated maturity levels. The criterion catalog in references/pillar-briefs.md is reverse-engineered from Factory's public reports (factory.ai/agent-readiness/fastapi_fastapi, cockroachdb_cockroach, …).

This is an investigation, not a checklist run. A score from file-existence alone is shallow — a linter nobody runs, a stale .env.example, or snapshot-only tests all "exist" yet leave the environment broken for an agent. So you delegate a deep, qualitative investigation of each pillar to a dedicated subagent, then you (the orchestrator) cross-reference their reports into a single, defensible score.

Why fan out: each pillar needs real reading — is the linter wired into CI and pre-commit, or just a dangling config? Are the docs accurate against the code, or stale? Do tests assert behavior, or are they filler? One agent can't hold nine deep investigations at once. Subagents keep each one thorough and independent; you stay the synthesizer.

• Framework background (pillars, failure modes, levels): references/factory-framework.md
• Per-pillar investigation briefs (what each subagent must dig into): references/pillar-briefs.md

Workflow

Step 0 — (optional) fast inventory

Run the bundled helper for a quick map of which configs/files exist: