review-loop

name: review-loop description: Submit code for automated review via Command Center. Triggers build verification, quality checks, and merge readiness analysis. Iterates on feedback until merge-ready. argument-hint: [optional description of what the code does]

Review Loop Skill

You are an autonomous coding agent running a review loop. You trigger Command Center's review pipeline, wait for results, fix any blocking issues yourself, and repeat until the PR is merge-ready.

IMPORTANT: This is a loop. You MUST keep going until the review passes or max attempts are exhausted. Do NOT stop after receiving feedback — fix the issues and re-trigger.

Phase 1: Setup & Context Detection

1. Resolve configuration. Check these sources in order for each value:

   APP_URL (Command Center endpoint):

   • Default: https://command-center.aigora.ai
   • Override: CC_APP_URL env var, or APP_URL in .env.local

   API_SECRET (service-to-service auth):

   • Shell env var: CC_API_SECRET
   • Fallback: INTERNAL_API_SECRET in .env.local
   • If neither exists, tell the user to set CC_API_SECRET in their shell profile and stop.

   # Read CC_API_SECRET from env, fall back to .env.local
   echo "${CC_API_SECRET:-$(grep INTERNAL_API_SECRET .env.local 2>/dev/null | cut -d= -f2-)}"
   

2. Detect repo and branch from git:

   git remote get-url origin 2>/dev/null | sed 's|.*github.com[:/]||;s|\.git$||'
   

   git branch --show-current
   

3. Find the PR number:

   gh pr view --json number -q .number 2>/dev/null
   

   If no PR exists, tell the user to open a PR first and stop.

4. Build the prompt text. Check these sources in order:

   • If the user provided $ARGUMENTS, use that as the prompt.
   • Otherwise, look for a plan file in docs/plans/ or .ai-docs/plans/ that mentions the branch name.
   • Otherwise, read the PR body: gh pr view --json body -q .body
   • If nothing useful is found, use a generic prompt: "Review the code changes on this branch for quality and merge readiness."

Phase 2: Trigger the Review

Call the trigger API using curl. Use python3 -c "import sys,json; ..." for JSON parsing (jq may not be available).

curl -s -X POST "${APP_URL}/api/orchestration/trigger" \
  -H "Content-Type: application/json" \
  -H "x-internal-api-secret: ${API_SECRET}" \
  -d '{"action":"start","repo":"REPO","branch":"BRANCH","prNumber":PR_NUM,"prompt":"PROMPT_TEXT"}'

Extract sessionId from the JSON response using python3. If the response contains an error, show it and stop.

Tell the user: "Review triggered (session: SESSION_ID). Waiting for results..."

Phase 3: Poll for Results

Poll the status endpoint. Wait 30 seconds between polls. Use sleep 30 between each curl call.

curl -s "${APP_URL}/api/orchestration/status?repo=REPO&sessionId=SESSION_ID&orgId=legacy-default" \
  -H "x-internal-api-secret: ${API_SECRET}"

Parse the JSON response with python3. Check state.phase:

• completed → Go to Phase 4 (success)
• failed → Go to Phase 4 (failure)
• executing AND the logs mention "waiting for fix" → Go to Phase 5 (fix issues)
• Anything else → Show the current phase and latest log message, then poll again after 30s

Keep polling until you reach one of the above terminal/actionable states. Do NOT give up after a few polls.

Phase 4: Terminal States

Success (phase=completed)

Tell the user:

• The review passed
• Show the PR URL
• Show any non-blocking warnings from state.lastMergeResult.warnings
• The PR is ready for human review and merge

Failure (phase=failed)

Tell the user:

• Show state.error
• Show what's still failing from state.lastQualityResult and state.lastMergeResult
• Suggest manual fixes if max rework attempts were exhausted

Phase 5: Fix Blocking Issues (THE CORE LOOP)

This is the most important phase. You are an autonomous agent — fix the issues yourself.

1. Extract findings from the status response:

   • state.lastMergeResult.blockingIssues — array of blocking issue descriptions
   • state.lastMergeResult.summary — detailed markdown summary with findings
   • state.lastQualityResult.findings — quality check findings text

2. Read and understand each blocking issue. Common issue types:

   • Code bugs (e.g., case-sensitivity, missing error handling) → Fix the code
   • Documentation updates (e.g., "TODO.md needs update", "CLAUDE.md needs update") → Update the docs
   • Skeleton regeneration → Run pnpm regen-skeleton if available
   • Test failures → Fix the failing tests

3. Fix each issue using your normal code editing tools (Read, Edit, Write). Do thorough fixes — don't just add comments or TODOs.

4. Commit and push the fixes:

   git add <specific-files-you-changed>
   

   git commit -m "fix: address review feedback - <brief description>"
   

   git push
   

5. Wait 3 minutes for CI and bot reviews to process the new commit. Bot reviewers on the PR need time to analyze the push before Command Center re-reviews:

   sleep 180
   

6. Nudge the orchestrator to re-review:

   curl -s -X POST "${APP_URL}/api/orchestration/trigger" \
     -H "Content-Type: application/json" \
     -H "x-internal-api-secret: ${API_SECRET}" \
     -d '{"action":"fix_pushed","sessionId":"SESSION_ID"}'
   

7. Go back to Phase 3 (poll again). The orchestrator will re-run build verification, quality check, and merge readiness on your new code.

Repeat Phase 3→5 until the review passes or fails permanently.

Important Notes

• Do NOT use jq — it may not be available. Use python3 -c "import sys,json; data=json.load(sys.stdin); print(data['key'])" for JSON parsing.
• Do NOT run long-lived bash loops — poll by making individual curl calls with sleep 30 between them.
• Always push before nudging — the orchestrator checks the latest commit on the branch.
• Be thorough with fixes — superficial fixes will just fail the next review cycle.
• Max 3 rework cycles — after that the orchestrator gives up. Make each fix count.