Bootstrap Checks From PRs

Use this skill to mine recent merged PRs, infer recurring review expectations, and auto-write draft checks into .agents/checks/ (and subtree check folders when applicable).

What This Skill Produces

• Draft check files in .agents/checks/*.md (global) and <area>/.agents/checks/*.md (scoped)
• Root AGENTS.md updated to reference .agents/checks/ for code reviews (created if missing)
• Evidence artifacts:
  • artifacts/pr-scan.json
  • artifacts/rule-candidates.json
  • artifacts/check-drafts.json
  • artifacts/check-bootstrap-report.md

Inputs

• repo (optional): owner/name; if omitted, infer from local repo via gh
• x (optional): merged PRs to analyze (default 30)
• base_branch (optional): default branch if not provided
• time_window_days (optional): constrain recency
• min_frequency (optional): default 2 (recommend 2-3)
• include_labels (optional): list of labels
• include_paths (optional): only focus on these prefixes
• exclude_paths (optional): ignore these prefixes
• max_checks (optional): cap initial output (default 10)
• default_severity (optional): default medium

Execution Workflow

Run these scripts in sequence from the skill directory:

1. Collect PR evidence

python scripts/collect_prs.py --x 30

2. Extract and score candidate rules

python scripts/extract_rule_candidates.py --min-frequency 2

3. Render candidate check drafts

python scripts/generate_check_drafts.py --max-checks 10 --default-severity medium

4. Write checks with collision safety

python scripts/write_checks.py

5. Ensure root AGENTS.md references checks

• If root AGENTS.md is missing, create it.
• Add code-review guidance that tells agents to load .agents/checks/ and relevant subtree-scoped <subtree>/.agents/checks/.
• Preserve existing instructions; append a focused section if needed.

6. Generate review report

python scripts/generate_report.py

If user provides custom inputs, pass them through all relevant scripts.

Safety and Quality Requirements

• Never overwrite existing check files silently.
• On filename collisions, use -draft suffix (or -draft-N).
• Ensure root AGENTS.md references .agents/checks/ for review checks.
• If root AGENTS.md is missing, create it.
• Do not rely on write_checks.py to mutate AGENTS.md; enforce this in agent workflow.
• Keep one check per file.
• Keep checks focused and actionable.
• Favor a small high-signal initial set (5-10 checks).
• Escalate to high/critical only with strong security/compliance evidence.

Recommended Agent Response After Running

Return a concise report with:

• Files created
• Confidence score per check
• Estimated false-positive risk
• Suggested decision for each check (keep, refine, drop)

Then recommend calibration on a holdout PR/diff before broad adoption.