Why my AI reviews were useless - formal inspection fixed it (Fagan Inspections using team of domain-expert sub agents)

Output example in Claude Code.

(Dev tool; posting per sub rules.)

Most vibe-coding failures aren’t “can’t build” - they’re unreviewed diffs: silent breakages, missed edge cases, test gaps.

A Fagan inspection is a formal review process (originally used in large teams) where you:

• define entry/exit criteria up front
• review with explicit roles/lenses (correctness, tests, security, etc.)
• produce a defect log with locations + evidence + verify steps
• rework + verify until exit criteria passes

Why this helps LLM reviews:

If you ask an LLM “check for errors,” it tends to be broad + agreeable.

If you force a Fagan workflow, it has to

1. restate intent,
2. inspect the diff through specific lenses,
3. log concrete defects (file/line + why + how to verify), and
4. confirm fixes against exit criteria.

The output becomes actionable (a defect list + verification), not vibes.

I turned that into a Claude Code / Codex CLI skill: https://github.com/45ck/fagan-inspection-skill

Optional: convert defects into Beads tasks.