Agent skill

Code Review

by sammcj in sammcj/agentic-coding

A skill your agent uses when the user asks for a code review of a change, branch or PR.

Apache-2.0Auto-check passedDevelopment

Install Code Review

skills CLI
$ npx skills add sammcj/agentic-coding --skill code-review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sammcj/agentic-coding code-review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sammcj/agentic-coding.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Skills/code-review .claude/skills/code-review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
code-review
GitHub stars
162
Token cost
~1.8k tokens
SKILL.md length
1,103 words
Files
1
Skills in repo
65
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when the user asks for a code review of a change, branch or PR.

  • Works in 3 steps: Spawn parallel sub-agents to critically… → Compile their findings into a concise… → Verify every finding against the actual…
  • The user asks for a code review of a change
  • SKILL.md covers Workflow, Applying Fixes, Review Axes and Calibration, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Code Review is an agent skill from sammcj/agentic-coding. Use when the user asks for a code review of a change, branch or PR.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Code review. The repository describes itself as: Agentic Coding Rules, Templates etc... The licence is Apache-2.0.

When your agent uses it

  • The user asks for a code review of a change
  • Tasks that involve Code review

Example prompts

  • “/code-review”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Spawn parallel sub-agents to critically review the changes, splitting the work by review axis (below) or by area of the codebase.
  2. Compile their findings into a concise numbered list, each tagged critical/medium/low.
  3. Verify every finding against the actual code before reporting or acting on it. Sub-agents report false positives, and acting on a phantom…

What it can do on your machine

Read from SKILL.md and the folder at commit 415ac71. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Code Review loads about 1.8k tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 1,103 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~20
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sammcj/agentic-coding at commit 415ac71, republished under its Apache-2.0 licence (© sammcj). 1,103 words, ~1,808 tokens.

Download SKILL.mdSave it as .claude/skills/code-review/SKILL.md (or your agent's skills folder).
name
code-review
description
Use when the user asks for a code review of a change, branch or PR.

Code Review After Completing Complex Software Development Tasks

Run a structured review over the changes in scope. Two modes:

  • Reviewing work you just completed, or told to fix - review, then apply and verify the fixes.
  • Asked only to review - stop at clear, actionable feedback and let the user decide what to act on. Don't start editing.

Workflow

  1. Spawn parallel sub-agents to critically review the changes, splitting the work by review axis (below) or by area of the codebase.
  2. Compile their findings into a concise numbered list, each tagged critical/medium/low.
  3. Verify every finding against the actual code before reporting or acting on it. Sub-agents report false positives, and acting on a phantom issue makes the code worse.

Applying Fixes

Fix mode only. If you were asked only to review, stop at step 3 and report your findings.

  1. Fix the confirmed issues.
  2. Re-run the project's lint/test/build pipeline.
  3. Read each fix to confirm it resolves its finding and didn't break the original task or introduce a new problem. A green pipeline proves mechanical correctness only.
  4. Stop after this single verification pass; don't recurse into a fresh full review.

If a finding is especially complex or keeps recurring, use the systematic-debugging skill to get to the root cause.

Review Axes

Direct sub-agents to evaluate the changes across these dimensions. The questions below are illustrative, not a fixed checklist. Apply the ones that fit and raise the concerns that actually matter for this codebase's language, domain, and conventions:

  • Correctness - Does it do what the task required? Are edge cases (null, empty, boundary) and error paths handled, not just the happy path? Do the tests actually exercise the new behaviour?
  • Readability - Are names and control flow clear to someone who didn't write this? Could it be simpler or shorter? Is each abstraction earning its complexity?
  • Architecture - Does it follow existing patterns and module boundaries, or introduce a new one without justification? Is there duplication that should be shared? A new dependency the existing stack already covers?
  • Security - Is untrusted input validated at boundaries? Any secrets in code or logs? Any injection (SQL, shell, path), missing authorisation checks, or external data used unsafely in logic or output?
  • Performance - What's costly for this kind of code: algorithmic complexity, repeated work or allocations in hot paths, N+1 queries, unbounded fetches, missing pagination, synchronous behaviour or blocking work on the critical path?

Create checklists or TODOs for yourself (or the sub-agents) to ensure your coverage is thorough.

Smell baseline

On top of whatever the repo documents, the Readability and Architecture axes always carry this fixed set of Fowler code smells (Refactoring, ch.3). It applies even when a repo documents no standards of its own. Two rules bind it:

  • The repo overrides. A documented repo standard always wins; where it endorses something the baseline would flag, suppress the smell.
  • Always a judgement call. Each smell is a labelled heuristic ("possible Feature Envy"), never a hard violation. Skip anything tooling already enforces.

Pass this list to the sub-agents verbatim - they have no other access to it. Each smell reads what it is → how to fix; match it against the diff and name the smell in the finding.

  • Mysterious Name - a function, variable, or type whose name doesn't reveal what it does or holds. → rename it; if no clear name comes, the design's murky.
  • Duplicated Code - the same logic shape appears in more than one hunk or file in the change. → extract the shared shape, call it from both.
  • Feature Envy - a method that reaches into another object's data more than its own. → move the method onto the data it envies.
  • Data Clumps - the same few fields or params keep travelling together (a type wanting to be born). → bundle them into one type, pass that.
  • Primitive Obsession - a primitive or string standing in for a domain concept that deserves its own type. → give the concept its own small type.
  • Repeated Switches - the same switch/if-cascade on the same type recurs across the change. → replace with polymorphism, or one map both sites share.
  • Shotgun Surgery - one logical change forces scattered edits across many files in the diff. → gather what changes together into one module.
  • Divergent Change - one file or module is edited for several unrelated reasons. → split so each module changes for one reason.
  • Speculative Generality - abstraction, parameters, or hooks added for needs the task doesn't have. → delete it; inline back until a real need shows.
  • Message Chains - long a.b().c().d() navigation the caller shouldn't depend on. → hide the walk behind one method on the first object.
  • Middle Man - a class or function that mostly just delegates onward. → cut it, call the real target direct.
  • Refused Bequest - a subclass or implementer that ignores or overrides most of what it inherits. → drop the inheritance, use composition.
Show full SKILL.md (307 more words)Show less

Calibration

  • The bar is "does this improve the codebase," not "is this how I would have written it." Don't invent problems just to have something to report, and don't rewrite working code over style preference.
  • Don't soften or rubber-stamp real problems either. State them plainly and quantify the impact where you can ("this N+1 adds ~50ms per row" beats "this might be slow").
  • Passing tests are necessary, not sufficient. They don't catch architecture, security, or readability problems, so review those regardless.

Dead Code

Refactors leave orphans. After changing code, list anything now unused (replaced functions, components, constants) and ask before removing it, rather than deleting silently or leaving it to rot.

Sub-Agent Guidelines

Where appropriate use sub-agents to parallelise your work and reduce context bloat in the main conversation.

  • Tell sub-agents to keep output concise, actionable, and focused on your changes, not minor style nitpicks.
  • Give them only the context they can't infer from the code itself.
  • Scope each agent to clear boundaries so they don't overlap or review unrelated code.

Reporting

The fixes, or the findings are the deliverable, so open with the (concise) outcome, not preamble or a description of your process.

  • Review-only: the findings ordered by severity, each as file:line, the problem, and a concrete fix. If nothing substantive turned up, say so in a line.
  • Fix mode: what you fixed, then what you didn't and why. List deferred or out-of-scope findings one line each so the user can decide, and note the pipeline result.

State real issues plainly and drop the hedging ("might want to consider", "could potentially"); tag anything optional as low and move on. Batch style nitpicks into a single note rather than scattering them. Don't close with a summary that restates the list. A short report flagging the few things that count beats a long one padded with the obvious.

© sammcj, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in Skills/code-review of sammcj/agentic-coding.

Open the folder on GitHubat commit 415ac71

Compare with similar skills

Code Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Code Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Code Review this skillsammcj/agentic-coding162—~1.8kAutomated safety check: PassApache-2.0
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT
Backend Code Reviewlangflow-ai/langflow156k—~3.5kAutomated safety check: NotesMIT
Understand Diff AnalysisEgonex-AI/Understand-Anything85k1 repos~1.4kAutomated safety check: PassMIT
Mole Bug Patternstw93/Mole69k—~2kAutomated safety check: PassGPL-3.0

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Categories

Questions about Code Review

What does Code Review do?

A skill your agent uses when the user asks for a code review of a change, branch or PR. Code Review is an agent skill from sammcj/agentic-coding. Use when the user asks for a code review of a change, branch or PR.

When should I use Code Review?

Code Review fits situations like: the user asks for a code review of a change; tasks that involve Code review.

How do I install Code Review in Claude Code?

Run `npx skills add sammcj/agentic-coding --skill code-review -a claude-code`. Or copy the skill folder (Skills/code-review in sammcj/agentic-coding) into .claude/skills/code-review in your project. Claude Code loads it when a task matches its description.

How do I install Code Review in Codex?

Run `npx skills add sammcj/agentic-coding --skill code-review -a codex`. Or copy the skill folder (Skills/code-review in sammcj/agentic-coding) into .agents/skills/code-review in your project. Codex loads it when a task matches its description.

Can I use Code Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sammcj/agentic-coding --skill code-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/code-review, .gemini/skills/code-review, .github/skills/code-review and .opencode/skills/code-review in your project.

What does Code Review need to run?

SKILL.md names no scripts, command-line tools or credentials: Code Review is instructions for the agent only.

Does Code Review access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Code Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Code Review use?

Code Review is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Code Review use?

About 1.8k tokens (SKILL.md is roughly 7.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Code Review?

Skills that share tags, products or a category with Code Review: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), Backend Code Review (langflow-ai/langflow, 156k stars) and Understand Diff Analysis (Egonex-AI/Understand-Anything, 85k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Code Review?

sammcj (a GitHub user) maintains it in sammcj/agentic-coding, which has 162 GitHub stars. The repository holds 65 skills in this directory. The repository was last updated on October 5, 2026.

Source: sammcj/agentic-coding on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.