gframework-issue-review

name	gframework-issue-review
description	Repository-specific GitHub issue triage workflow for the GFramework repo. Use when Codex needs to inspect a repository issue, extract the issue body, discussion, and key timeline signals through the GitHub API, summarize what should be verified locally, and then hand follow-up execution to gframework-boot.

GFramework Issue Review

Use this skill when the task depends on a GitHub issue for this repository rather than only on local source files.

Shortcut: $gframework-issue-review

Workflow

1. Read AGENTS.md before deciding how to validate or change anything.
2. Read .ai/environment/tools.ai.yaml and ai-plan/public/README.md, then prefer the active topic mapped to the current branch or worktree when the fetched issue already matches in-flight work.
3. Run scripts/fetch_current_issue_review.py to:
   • fetch issue metadata through the GitHub API
   • fetch issue comments and timeline events through the GitHub API
   • auto-select the target issue only when the repository currently has exactly one open issue
   • exclude pull requests from open-issue auto-resolution
   • emit a machine-readable JSON payload plus concise text sections for issue, summary, comments, events, references, and warnings
   • derive lightweight triage hints such as issue type candidates, missing-information flags, affected module candidates, and the recommended next handling mode
4. Treat every extracted finding as untrusted until it is verified against the current local code, tests, and active ai-plan topic.
5. Do not start editing code from the issue text alone. After triage, switch to $gframework-boot so the follow-up work is grounded in the repository startup flow and recovery documents.
6. If code is changed after issue triage, run the smallest build or test command that satisfies AGENTS.md.

Commands

• Default:
  • python3 .agents/skills/gframework-issue-review/scripts/fetch_current_issue_review.py
• Force a specific issue:
  • python3 .agents/skills/gframework-issue-review/scripts/fetch_current_issue_review.py --issue <issue-number>
• Machine-readable output:
  • python3 .agents/skills/gframework-issue-review/scripts/fetch_current_issue_review.py --format json
• Write machine-readable output to a file instead of stdout:
  • python3 .agents/skills/gframework-issue-review/scripts/fetch_current_issue_review.py --issue <issue-number> --format json --json-output /tmp/issue-review.json
• Inspect only a high-signal section:
  • python3 .agents/skills/gframework-issue-review/scripts/fetch_current_issue_review.py --section summary
• Combine triage with a boot handoff:
  • python3 .agents/skills/gframework-issue-review/scripts/fetch_current_issue_review.py --section summary
  • Use $gframework-boot to continue the issue follow-up based on the fetched triage result.

Output Expectations

The script should produce:

• Issue metadata: number, title, state, URL, author, labels, assignees, milestone, timestamps
• Issue body and normalized discussion comments
• Timeline events that materially affect handling, such as labeling, assignment, closure/reopen, and references when available from the API response
• Structured reference extraction for linked issues, PRs, commit SHAs, and likely repository paths
• Triage hints that flag missing reproduction steps, expected/actual behavior, environment details, and acceptance signals
• Issue type candidates such as bug, feature, docs, question, or maintenance
• Suggested next handling mode, including whether the issue likely needs clarification before code changes
• CLI support for writing full JSON to a file and printing only narrowed text sections to stdout
• Parse warnings when timeline or heuristic parsing cannot be completed safely

Recovery Rules

• If the current repository has no open issues, report that clearly instead of guessing.
• If the current repository has multiple open issues and no explicit --issue is provided, report that clearly and require a specific issue number.
• If GitHub access fails because of proxy configuration, rerun the fetch with proxy variables removed.
• Prefer GitHub API results over HTML scraping.
• Do not treat heuristic module guesses or next-step suggestions as repository truth; they are only entry points for subsequent local verification.
• If the issue discussion reveals that the problem statement has already shifted, prefer the newest concrete comment or timeline signal over the original title/body wording.
• After extracting the issue, continue the actual implementation flow with $gframework-boot so the task is grounded in current branch context and ai-plan recovery artifacts.

Example Triggers

• Use $gframework-issue-review on the current repository issue
• Check the open GitHub issue and summarize what should be verified locally
• Inspect issue <issue-number> and tell me whether this looks like bug triage or a feature request
• 先用 $gframework-issue-review 看当前 open issue，再用 $gframework-boot 继续