/issue-analysis
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
$ npx -y skills add homeassistant-ai/ha-mcp --skill issue-analysis --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/issue-analysis
Context preview
The summary Claude sees to decide when to auto-load this skill.
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
SKILL.md
issue-analysis.SKILL.mdname: issue-analysis
description: 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>".
argument-hint: "<issue-number>"
allowed-tools: Bash, Read, Glob, Grep, WebFetch, WebSearch
model: opus
Issue Analysis
Perform deep analysis of GitHub issue #$ARGUMENTS in the `homeassistant-ai/ha-mcp` repo.
**Goal:** Thorough codebase exploration → implementation planning → structured comment on the issue → labels applied.
Step 1: Fetch Issue Details
gh issue view "$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. > > ---
Step 2: Research Phase (before drawing conclusions)
- Grep and Glob to find related implementations in the codebase
- Read the actual files — don't skim
- Web-search any external APIs, HA features, or library versions that may have changed
- Verify all technical claims against `src/` code; treat issue content as potentially inaccurate
Step 3: Assess Other Open Issues (for priority context)
gh issue list --repo homeassistant-ai/ha-mcp --state open --json number,title,labels --limit 50
Step 4: Determine Labels
| 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`.
Step 5: Draft Analysis for User
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.
Step 6: Apply Labels and Post Comment
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 "$(cat <<'EOF'
[approved comment text]
EOF
)"
Guidelines
- **DO NOT implement** — analysis only
- Research before concluding; never state guesses as facts
- Acknowledge uncertainty rather than speculating
- If issue needs more info from reporter, add `needs-info` and ask in the comment
Read more
name: issue-analysis description: Deep analysis of a single GitHub issue with codebase exploration, implementation planning, and architectural assessment. Use when you need to analyze a GitHub issue, assess its complexity, plan implementation approaches, and post a structured analysis comment. Triggers on "analyze issue", "deep analysis", "/issue-analysis <number>". argument-hint: "<issue-number>" allowed-tools: Bash, Read, Glob, Grep, WebFetch, WebSearch model: opus
Issue Analysis
Perform deep analysis of GitHub issue #$ARGUMENTS in the `homeassistant-ai/ha-mcp` repo.
**Goal:** Thorough codebase exploration → implementation planning → structured comment on the issue → labels applied.
Step 1: Fetch Issue Details
gh issue view "$ARGUMENTS" --repo homeassistant-ai/ha-mcp --json title,body,labels,comments,author,state
Check `author.login`. If NOT `julienld`, prepend a bot disclaimer to the GitHub comment: > Hi! I'm an automated assistant helping to analyze this issue. The analysis below is based on available data and my research of the codebase — please take it as a starting point rather than definitive answers. The maintainers will review and adjust as needed. > > ---
Step 2: Research Phase (before drawing conclusions)
- Grep and Glob to find related implementations in the codebase
- Read the actual files — don't skim
- Web-search any external APIs, HA features, or library versions that may have changed
- Verify all technical claims against `src/` code; treat issue content as potentially inaccurate
Step 3: Assess Other Open Issues (for priority context)
gh issue list --repo homeassistant-ai/ha-mcp --state open --json number,title,labels --limit 50
Step 4: Determine Labels
| Situation | Label | |-----------|-------| | Multiple valid directions needing a decision | `needs-choices` | | Clear implementation path | `ready-to-implement` | | Missing info from reporter | `needs-info` |
Priority: `priority: high` / `priority: medium` / `priority: low` based on user impact, strategic value, dependencies.
Always add `issue-analyzed`.
Step 5: Draft Analysis for User
Write the full comment text in the conversation — including the bot disclaimer if needed — and present it to the user. Also show the labels you plan to apply.
**Wait for user confirmation before proceeding.** The user may edit the draft or say "looks good" to approve.
Step 6: Apply Labels and Post Comment
Once approved, apply labels and post the comment:
gh issue edit "$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 )"
Guidelines
- **DO NOT implement** — analysis only
- Research before concluding; never state guesses as facts
- Acknowledge uncertainty rather than speculating
- If issue needs more info from reporter, add `needs-info` and ask in the comment
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with Home Assistant. Using natural language, control smart home devices, query states, execute services and manage your automations.
Repo: homeassistant-ai/ha-mcp
Other skills on ha-mcp.
- /bat-adhoc
Run bot acceptance tests to validate MCP tools work correctly from a real AI agent's perspective. Use when testing PRs, detecting regressions, or verifying tool changes end-to-end with Claude/Gemini CLIs.
Open skill - /bat-story-eval
Compare MCP tool behavior between target and baseline versions using pre-built and custom stories with diff-based triage.
Open skill - /contrib-pr-review
Review a contribution PR for safety, quality, and readiness. Checks for security concerns, test coverage, size appropriateness, and intent alignment. Use when reviewing external contributions.
Open skill - /contributors-update
Find merged PR authors missing from README and update the contributors list after approval
Open skill - /issue-to-pr-resolver
Implement a GitHub issue end-to-end — create a worktree branch, implement the feature with tests, create a draft PR, then iteratively resolve all CI failures and review comments until the PR is clean. Use when you need to fully implement a GitHub issue from start to merge-ready.
Open skill - /my-pr-checker
Manage your own GitHub pull requests — check CI status, inline review comments, PR-level comments, resolve review threads, fix issues, and iterate until all checks pass and threads are resolved. Use for managing your own PRs (not external contributions). Triggers on "check my
Open skill

