Maestro:review

Review

Standalone code review for any PR. Runs the full lead-reviewer analysis against the spec and project standards. Posting inline comments and the summary to GitHub is your choice — you are prompted at the end.

Step 1 — Resolve the PR

If $ARGUMENTS is provided, use it as the PR number or URL.

Otherwise resolve from the current branch:

gh pr list --head "$(git branch --show-current)" --json number,url -q '.[0] | "\(.number) \(.url)"'

If no PR is found, tell the user and stop.

Step 2 — Read config and gather context

Read .claude/maestro.json. Extract:

• TEMP_ROOT = .ai.temp_root
• REPO = .ai.repo

Then gather from the PR:

gh pr view <PR_NUMBER> --json baseRefName,body -q '{base: .baseRefName, body: .body}'

Extract the base branch and the linked issue number (look for Fixes #N, Closes #N, or a GitHub issue URL in the PR body).

Step 3 — Locate the spec

If a linked issue number was found, check for a spec at: {TEMP_ROOT}/issues/<N>/spec.md

If the spec exists, pass its path to the agent. If it does not exist, inform the user: "No grooming spec found — the review will check against project standards only (spec compliance section will be skipped)."

Step 4 — Invoke the lead-reviewer agent

Invoke the lead-reviewer sub-agent with:

• Issue number (if known) and spec path (if found, else omit)
• Base branch from Step 2
• PR number
• CURRENT_MODEL: "standalone"
• session_learnings: read Section 13 of AGENTS.md if it exists, else pass empty string

STANDALONE MODE — two differences from the normal pipeline run:

1. Skip Step 5 (inline PR comments) and Step 5b (summary PR comment). Instead, output the full review report — findings table, blockers, nice-to-haves — as formatted Markdown in your response, in a section titled ## Review Report.
2. Skip Step 6 (StructuredOutput JSON). Return a short human-readable verdict summary instead: overall verdict, blocker count, and any open questions.

Step 5 — Offer to post

After the agent responds, display its ## Review Report and ask:

Post this review to PR #<PR_NUMBER>? Reply yes to post inline comments + summary, no to finish here.

If yes — the agent posts inline comments (Step 5) and the summary comment (Step 5b) using the normal dedup flow. Both respect the <!-- ai-pipeline:lead-review --> marker so a re-run later (via the pipeline) will update in place rather than duplicate.

If no — confirm the review is complete and finish.