greenlight-pr

name: greenlight-pr description: Greenlight a PR — fix CI failures, triage review comments, iterate until green. argument-hint: "[PR number or URL]" hooks: PostToolUse: - matcher: "*" hooks: - type: command command: 'python3 "$HOME/.claude/skills/skill-feedback/scripts/skill-event.py" --skill greenlight-pr --event skill_activated --agent-harness claude-code --quiet' timeout: 5

Greenlight PR

Drive a PR to green — fix CI, address AI code reviews, iterate until merge-ready.

You are the decision-maker, not the reviewer. AI review bots do the reviewing. You evaluate their feedback, decide what's worth fixing, fix it well, and iterate until clean.

Tool

python3 ~/.claude/skills/greenlight-pr/scripts/gl-snapshot.py [PR]

Returns structured JSON: CI status, review comments (with code context), and recommended actions. State persists in /tmp/gl-{repo}-pr{N}.json.

Code Review Skill Awareness

The code-review skill posts inline PR comments — just like CodeRabbit or any other bot. Greenlight-pr triages them all the same way.

The difference: code-review signals its status via HTML comment markers in PR comments:

• <!-- code-review-status: in_progress --> — review is running
• <!-- code-review-status: complete --> — review is done, findings posted

Whenever you are about to triage comments or wait for reviews, also check if a code-review is in progress. If it is, wait for it to finish before proceeding (poll every 30s, timeout 10min). This is in addition to the existing --wait-review polling for external bots — both must finish before you triage.

# Check if code-review skill is still running
COMMENTS=$(gh pr view [PR] --comments --json comments -q '.comments[].body')
if echo "$COMMENTS" | grep -q 'code-review-status: in_progress' && \
   ! echo "$COMMENTS" | grep -q 'code-review-status: complete'; then
  # Poll until complete
  for i in $(seq 1 20); do
    sleep 30
    COMMENTS=$(gh pr view [PR] --comments --json comments -q '.comments[].body')
    echo "$COMMENTS" | grep -q 'code-review-status: complete' && break
  done
fi

Terminal States

Main Loop

snapshot = gl-snapshot.py [PR]
actions = snapshot.actions

loop:
  if "stop_pr_closed" in actions:
    return "PR merged or closed"

  if "stop_exhausted_retries" in actions:
    return "CI retries exhausted — ask user"

  if "fix_ci" in actions:
    for each check in snapshot.ci.failed:
      if check.classification == "branch":
        read check.log_excerpt
        find the failure cause in the code
        fix it
    commit → push
    goto snapshot

  if "retry_ci" in actions:
    gl-snapshot.py --retry-failed
    gh pr checks [PR] --watch --fail-fast
    goto snapshot

  if "triage_comments" in actions:
    check for code-review in progress → wait if needed (see above)
    run TRIAGE PROCESS (see references/triage-process.md)
    push fixes
    gh pr checks [PR] --watch --fail-fast   # wait for CI first
    snapshot = gl-snapshot.py --wait-review  # polls with timeout; returns full snapshot
    check for code-review in progress → wait if needed
    actions = snapshot.actions               # may be stop_waiting_review_pending if timed out
    continue loop                            # re-evaluate from wait result

  if "wait_review" in actions:
    snapshot = gl-snapshot.py --wait-review   # polls with timeout; returns full snapshot
    check for code-review in progress → wait if needed
    actions = snapshot.actions                # may be stop_waiting_review_pending if timed out
    continue loop                            # re-evaluate — do NOT re-snapshot

  if "wait_ci" in actions:
    gh pr checks [PR] --watch --fail-fast
    goto snapshot

  if "stop_waiting_review_pending" in actions:
    return "CI green, no actionable comments yet, but external bot review still pending. Rerun later."

  if "done" in actions:
    return "CI green, no pending bot reviews, no new comments — merge-ready"

Happy Path Example

Concrete commands for the most common flow: bot posts comments → triage → fix → re-review.

# 1. Snapshot
python3 ~/.claude/skills/greenlight-pr/scripts/gl-snapshot.py 42
# → actions: ["triage_comments"], new_comments: [{id: "123", body: "...", code_context: "..."}]

# 2. Triage (see references/triage-process.md)
#    Read comments, spawn sub-agents, decide FIX/DISAGREE/DEFER
#    Fix the code...

# 3. Commit and push
git add -A && git commit -m "Address review: fix X, Y" && git push

# 4. Reply to each comment
gh api repos/owner/repo/pulls/42/comments/123/replies -f body="Fixed — description. See abc1234"

# 5. Post round summary
gh pr comment 42 --body "## Greenlight — Round 1
**Fixed (2):** X, Y
**Disagreed (1):** Z — reasoning"

# 6. Mark as seen
python3 ~/.claude/skills/greenlight-pr/scripts/gl-snapshot.py --mark-seen 123,456,789

# 7. Wait for bot re-review, then re-snapshot
gh pr checks 42 --watch --fail-fast
python3 ~/.claude/skills/greenlight-pr/scripts/gl-snapshot.py --wait-review
python3 ~/.claude/skills/greenlight-pr/scripts/gl-snapshot.py 42
# → new round: check actions again

What counts as a comment

The snapshot only returns inline review comments with code_context (the diff hunk). It ignores:

• Big walkthrough/summary comments that bots post at the top of the PR
• Issue-level comments (not attached to a line of code)
• Your own replies

If CodeRabbit auto-marks a comment as "Addressed in commit X", you don't need to reply again unless you want an audit trail.

Recovery after interruption

State persists in /tmp/gl-{repo}-pr{N}.json. If a session is interrupted, just re-run the snapshot — it picks up where you left off with all processed comment IDs intact.

Triage Process (overview)

The full process with sub-agent prompts and decision trees is in references/triage-process.md. Summary:

Phase 1 — EVALUATE
  spawn sub-agents to evaluate each comment
  each returns: verdict (FIX/DISAGREE/DEFER) + reasoning + confidence

Phase 2 — SYNTHESIZE
  collect sub-agent results
  resolve conflicts (agents may disagree)
  filter: only HIGH/MEDIUM confidence FIXes that pass quality check

Phase 3 — ACT
  implement fixes (one commit, grouped)
  reply to every comment individually
  post round summary as PR comment
  gl-snapshot.py --mark-seen <ids>

Guardrails

• Think before fixing. Don't blindly apply every bot suggestion.
• No workarounds. If you can't fix it properly, disagree or defer.
• No over-engineering. Push back on suggestions that add complexity without solving real problems.
• Always reply. Every inline comment gets a reply. Every round gets a summary.
• Wait for re-review. After every push, --wait-review then re-snapshot.
• Know when to stop. 3+ rounds of only nit/duplicate comments → done.
• Escalate. Product decisions → stop and ask user.

References

• references/triage-process.md — Sub-agent prompts, decision pseudocode, quality checks, reply templates
• references/ci-classification.md — Branch vs flaky heuristics
• references/known-bots.md — AI review bot catalog and re-review patterns

AZ Skill Feedback

After the run, if this skill was useful, confusing, broken, or missing context, submit 1-3 safe sentences. Include --agent-harness when known. Include --model-config only if the harness exposes the exact model/config; otherwise leave it as unknown:

python3 ~/.agents/skills/skill-feedback/scripts/skill-feedback.py --skill greenlight-pr --rating idea --text "..."

Never include secrets, private data, source code, long prompts, or stack traces.