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A Claude Code skill can make code reviews more consistent by giving Claude a focused checklist for inspecting changes and reporting actionable risks. Create a SKILL.md with a precise description and evidence-based review instructions, then evaluate its results on real changes in your repository. Anthropic documents how to structure and invoke skills, but does not publish a measured improvement in review quality from custom review skills.
What a code-review skill can—and cannot—do
A skill is a directory whose required entry point is a SKILL.md file. It contains YAML frontmatter followed by Markdown instructions. Claude Code uses the skill’s name as its command and its description to help determine when the skill should load. See the Claude Code skills documentation.
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A carefully scoped skill can encourage a repeatable review: inspect changed code and relevant context, connect potential defects to specific failure conditions and impacts, and leave out unsupported findings. That is a design goal, not a demonstrated guarantee. Anthropic’s reviewed documentation does not report a benchmark or percentage improvement for custom code-review skills, so assess usefulness against your own repository and pull requests.
Create the skill in the right location
Choose its location according to who should use the review instructions. Project skills apply to sessions in that repository; personal skills are available across that user’s projects on the machine. Anthropic also documents enterprise-managed, nested, additional-directory, and plugin locations for other scopes.
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| Scope | Documented location or mechanism | Use it when |
|---|---|---|
| Project | .claude/skills/<skill-name>/SKILL.md |
Review criteria belong to one repository and should travel with it. |
| Personal | ~/.claude/skills/<skill-name>/SKILL.md |
You want reusable personal review preferences across projects on that machine. |
| Enterprise-managed | Enterprise-managed skill location; exact path is not stated here. See Anthropic’s skills documentation. | Standards should be managed centrally for an organization. |
For a repository-specific skill, create a directory and file such as .claude/skills/review-changes/SKILL.md. Put broader project conventions, preferred patterns, and rules that should guide Claude Code work beyond code review in the repository’s CLAUDE.md, as recommended in the Claude Code GitHub Actions documentation.
Write a focused SKILL.md
Use valid YAML frontmatter between --- delimiters, then give the skill practical instructions in Markdown. The opening delimiter must be the first line; malformed YAML can prevent metadata such as the description from being recognized, and unknown fields are ignored. Anthropic recommends the description among optional frontmatter fields. Its wording should put the key use case first and say when the skill applies.
Here is a starting point to adapt to your team’s review conventions. The checklist is editorial guidance, not an Anthropic-prescribed rubric or a tested universal prompt.
---
name: review-changes
description: Review a proposed code change for actionable correctness, security, and regression risks. Use when asked to review a diff or pull request.
---
# Review changes
1. Inspect the changed files and relevant surrounding code before reaching conclusions.
2. Check whether each possible finding is supported by the diff, repository behavior, or a reproducible test. Do not invent findings.
3. Report only actionable issues. For each, give severity, file and line, the failure condition, and the concrete impact.
4. Separate confirmed defects from questions or suggestions. If no actionable issue is supported, say so and note the scope reviewed.Keep the entry-point file concise: Anthropic’s skills documentation says to keep SKILL.md under 500 lines. Put long examples, domain-specific checklists, or reference material in separate files and link to them from the skill so they can be consulted when needed.
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By default, both the user and Claude can invoke a skill. The description helps Claude decide whether to load it automatically. Set invocation metadata only when the desired behavior calls for it; details are in the skills reference.
| Choice | Effect | When it fits |
|---|---|---|
| Default behavior | Both user and Claude can invoke the skill; Claude can use its description to assess whether it applies. | You want the option of explicit use and automatic selection when the request matches. |
disable-model-invocation: true |
Restricts use to explicit user invocation and removes the description from the listing used for automatic selection. | Review should run only when someone deliberately calls the skill. |
user-invocable: false |
The user cannot run the skill directly, but Claude can invoke it. | The instructions are background knowledge rather than a user-run command. |
For a review skill, explicit invocation gives maintainers control over when a review starts; default behavior can suit teams that want Claude to select it for matching review requests. Neither choice by itself establishes better review accuracy.
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Evaluate review quality with real changes
Judge the skill by whether its output helps maintainers, not by how many findings it produces. Try a small, representative set of real pull requests: include changes with known bugs, changes with no defects, and changes that touch important project conventions. Track missed real issues, unsupported findings, clarity, and usefulness; revise the instructions when the same failure pattern recurs.
- Check that each reported issue points to a relevant location and explains a concrete failure condition and impact.
- Check whether the skill avoids treating speculation or a suggestion as a confirmed defect.
- Check that clean changes do not prompt invented findings simply to fill a report.
- Record the scope reviewed when the skill finds no actionable issue, so a quiet result is not mistaken for proof that the change is defect-free.
Anthropic’s Claude prompting best practices discuss self-correction, investigating relevant files, and grounding responses in source material. These are general prompting practices; they do not show that an automated review can replace human review.
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For teams that want automated reviews, Anthropic’s GitHub Actions documentation describes a workflow that runs a review skill when a pull request is opened or updated, as well as a quick setup path using /install-github-app. The documentation distinguishes this workflow integration from the separate Code Review product.
Before adopting an example workflow, verify the current action version, permissions, authentication setup, and repository policy; these details can change. Put repository style rules, review criteria, and preferred patterns in CLAUDE.md when they should apply across the project, and review Claude’s changes before merging. Automation can initiate or assist a review, but the documented workflow is not evidence of an accuracy uplift.
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