Analyze a GitHub issue by exploring related code, checking relevant external details, and assessing implementation complexity and architectural choices. The skill drafts a structured issue comment and recommends labels for maintainers to review.
Deep analysis of a single GitHub issue with codebase exploration, implementation planning, and architectural assessment. Use when you need to analyze a GitHub issue, assess its complexity, plan implementation approaches, and post a structured analysis comment. Triggers on "analyze issue", "deep analysis", "/issue-analysis <number>".
Run score Not tested
See how to installReview the instructions the agent will receive before you install.
Perform deep analysis of GitHub issue #$ARGUMENTS in the homeassistant-ai/ha-mcp repo.
Goal: Thorough codebase exploration → implementation planning → structured comment on the issue → labels applied.
gh issue view "$ARGUMENTS" --repo homeassistant-ai/ha-mcp --json title,body,labels,comments,author,state
Check author.login. If NOT julienld, prepend a bot disclaimer to the GitHub comment:
Hi! I'm an automated assistant helping to analyze this issue. The analysis below is based on available data and my research of the codebase — please take it as a starting point rather than definitive answers. The maintainers will review and adjust as needed.
src/ code; treat issue content as potentially inaccurategh issue list --repo homeassistant-ai/ha-mcp --state open --json number,title,labels --limit 50
| Situation | Label |
|---|---|
| Multiple valid directions needing a decision | needs-choices |
| Clear implementation path | ready-to-implement |
| Missing info from reporter | needs-info |
Priority: priority: high / priority: medium / priority: low based on user impact, strategic value, dependencies.
Always add issue-analyzed.
Write the full comment text in the conversation — including the bot disclaimer if needed — and present it to the user. Also show the labels you plan to apply.
Wait for user confirmation before proceeding. The user may edit the draft or say "looks good" to approve.
Once approved, apply labels and post the comment:
gh issue edit "$ARGUMENTS" --repo homeassistant-ai/ha-mcp \
--add-label "issue-analyzed,<classification>,<priority>"
gh issue comment "$ARGUMENTS" --repo homeassistant-ai/ha-mcp --body "$(cat <<'EOF'
[approved comment text]
EOF
)"
needs-info and ask in the commentNo reviews yet. Tell others what you thought.
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Design and run focused acceptance scenarios to check MCP tools through real agent CLIs such as Claude or Gemini. Review task completion, tool failures, and detailed run output, and compare branches when investigating a regression.
Compare MCP tool behavior in a target version with a released baseline. It selects relevant prebuilt scenarios, designs custom regression stories, runs them with agent CLIs, verifies outcomes, and reports behavior, tool usage, and cost trends.
Review an external GitHub pull request for security concerns, test coverage, change size, and alignment with its linked issue or stated purpose. It summarizes findings and drafts a constructive review comment for you to approve before posting.
Finds authors of merged pull requests who are missing from a README contributors list, drafts concise descriptions of their work, and updates the list only after the user approves the proposed additions.
Take a GitHub issue through implementation in a worktree, tests, and a draft pull request. The skill then checks CI results and review threads, applies fixes, and repeats the review cycle until the pull request is ready for maintainer review.
Manage your own GitHub pull request by checking CI results, review comments, and unresolved threads. Triage feedback, make code fixes, reply to comments, resolve threads, and recheck until outstanding issues are cleared.