home-assistant/core

ha-review

Reviews Home Assistant code changes and provides constructive feedback. Should be used when a review is requested to provide a consistent review behavior and output format. This skill can be used for code reviews in general, not just for GitHub pull requests.

First seen Jul 4, 2026

Installation

$ npx skills add home-assistant/core --skill ha-review

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 90.3K
License LICENSE.md
Default branch dev
Open issues 2,615
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,167 B
  • docs SUMMARY.md 276 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 4 installs

SKILL.md

Review Code Changes

Scope:

  • Unless instructed otherwise, review the full changes (the ones from the branch plus uncommitted ones) against the target branch. Resolve the base to an available ref (prefer upstream/<base>, then origin/<base>, then local <base>) and review git diff "$(git merge-base "$BASE_REF" HEAD)"; use dev as the default base.

Analyze the code changes for:

  • Code quality and style consistency
  • Potential bugs or issues
  • Performance implications
  • Security concerns
  • Test coverage
  • Documentation updates if needed

Quality scale:

  • If the changes include a quality_scale.yaml file, run a subagent to verify all the added or modified rules, following the ha-quality-scale-verify skill.
  • Include the verification results in the final review comments.

Verification:

  • After the review, run parallel subagents for each finding to double-check it.
  • Spawn up to a maximum of 10 parallel subagents at a time.
  • Gather the results from the subagents and summarize them in the final review comments.

IMPORTANT:

  • Just review. DO NOT make any changes.
  • Be constructive and specific in your comments.
  • Suggest improvements where appropriate.
  • No need to run tests or linters, just review the code changes.
  • No need to highlight things that are already good.

Output format:

  • List specific comments for each file/line that needs attention.
  • In the end, summarize with an overall assessment (approve, request changes, or comment) and bullet point list of changes suggested, if any.

- Example output: `` Overall assessment: request changes. - [CRITICAL] sensor.py:143 - Memory leak - [PROBLEM] dataprocessing.py:87 - Inefficient algorithm - [SUGGESTION] testinit.py:45 - Improve x variable name `` - Make sure to include the file and line number when possible in the bullet points.