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Groom a single GitHub issue — produce an implementation spec and optionally post the grooming summary as a GitHub comment. Standalone entry point for the grooming-agent.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Generate a bespoke issue-workflow for any target project. Phase 1 — a Claude Opus analyst reads the project deeply and produces a disposition report. Phase 2 — on approval, parallel writer agents transplant every Maestro workflow component, adapted to the target project's actual stack, test runner, dev environment, and conventions. Use when a project needs its own self-contained issue-workflow without taking a direct dependency on Maestro.
Show the Maestro command map — a quick reference to all available skills.
Adversarially review a grooming spec before implementation starts. Finds hidden risks, unvalidated assumptions, and missing dependencies. Standalone entry point for the challenger agent.
Run QA validation on a pull request — boots the local environment, tests acceptance criteria, and optionally posts the report as a PR comment. Standalone entry point for the qa-engineer agent.
Run a lead code review on the current branch or a given PR. Standalone entry point for the lead-reviewer agent.
Check a change against WordPress.org plugin rules and PHPCS standards.
| name | maestro:groom |
| description | Groom a single GitHub issue — produce an implementation spec and optionally post the grooming summary as a GitHub comment. Standalone entry point for the grooming-agent. |
| argument-hint | <issue-number> |
Standalone grooming for a single issue. Runs the full grooming analysis and writes the spec to disk. Posting to GitHub is your choice — you are prompted at the end.
Read .claude/maestro.json. Extract:
TEMP_ROOT = .ai.temp_rootREPO = .ai.repoEnsure the issue file exists at {TEMP_ROOT}/issues/<N>/issue.md. Run:
bash .claude/skills/issue-workflow/scripts/issue-sync.sh <N>
If the file already exists and git status shows it is less than 5 minutes old, skip the
sync and use the cached file.
Invoke the grooming-agent sub-agent with the following invocation context:
Issue number:
<N>complexity_signal: derive from the issue content yourselfSTANDALONE MODE — two differences from the normal pipeline run:
- Skip Step 5 (posting to GitHub). Instead, include the full comment body you would have posted in a section titled
## Grooming Comment Draftat the end of your response. Use exactly the same format the pipeline would post (including the<!-- ai-pipeline:grooming-plan -->marker), so it is ready to copy-paste or post as-is.- Skip Step 6 (StructuredOutput JSON). Return a short human-readable summary instead: effort, risk, complexity, and any open questions.
The spec file is still written to {TEMP_ROOT}/issues/<N>/spec.md as normal — that always happens.
After the agent responds, display its ## Grooming Comment Draft to the user, then ask:
Post this as a comment on issue #<N>? Reply
yesto post as-is,noto finish without posting, or paste edited text to post a modified version.
If yes — post using the exact body from the draft (including the HTML marker):
gh issue comment <N> --repo {REPO} --body "$(cat <<'EOF'
<!-- ai-pipeline:grooming-plan -->
[comment body here]
EOF
)"
Check for an existing grooming comment first (dedup):
EXISTING_ID=$(gh api repos/{REPO}/issues/<N>/comments \
--jq '[.[] | select(.body | contains("<!-- ai-pipeline:grooming-plan -->"))] | last | .id // empty')
If one exists, update it with PATCH instead of creating a new comment.
If no — confirm the spec was written to {TEMP_ROOT}/issues/<N>/spec.md and finish.
If edited — use the user-provided text as the comment body and post.