Agent skill

Code Review

by s3s-project in s3s-project/s3s

Review a pull request or a proposed change to this repository.

Apache-2.0Auto-check passedDevelopment

Install Code Review

skills CLI
$ npx skills add s3s-project/s3s --skill code-review -a claude-code

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

GitHub CLI
$ gh skill install s3s-project/s3s 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/s3s-project/s3s.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/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
311
Token cost
~2k tokens
SKILL.md length
1,142 words
Files
1
Skills in repo
10
Repo updated
First seen
Licence
Apache-2.0

At a glance

Review a pull request or a proposed change to this repository.

  • Works in 6 steps: Name the object and the intent. State… → Walk the catalog family by family, and… → Cover the whole catalog for every pull… → …
  • Asked to review a pull request
  • SKILL.md covers Review flow, What settles a dimension, Dimension catalog and Calibration
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Code Review is an agent skill from s3s-project/s3s. Review a pull request or a proposed change to this repository. Use when asked to review a pull request, a diff, or a branch, and when a review finding needs evidence before it is reported.

Its SKILL.md is about 2k 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 and Pull requests. The licence is Apache-2.0.

When your agent uses it

  • Asked to review a pull request
  • When a review finding needs evidence before it is reported

Example prompts

  • “/code-review”

Workflow steps

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

  1. Name the object and the intent. State what the change claims and what would make it wrong.
  2. Walk the catalog family by family, and one dimension at a time inside a family: a single read-through lets the most visible change absorb…
  3. Cover the whole catalog for every pull request, whatever it changes: code, documentation, dependencies, build configuration, generated…
  4. Check the evidence. Recompute what can be recomputed: counts, commands, exit codes, file lists, tree hashes.
  5. Name the gaps and the conflicts. Tradeoffs between families, and every question the reviewed material does not answer.
  6. State the conclusion, with the artifact behind each problem it raises and an action for each of them.

What it can do on your machine

Read from SKILL.md and the folder at commit 1e1c52e. 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 2k tokens when it runs. Until then it costs about 50 tokens; SKILL.md has 1,142 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~50
When it runs · the whole SKILL.md, loaded when a task matches
~2k

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 s3s-project/s3s at commit 1e1c52e, republished under its Apache-2.0 licence (© s3s-project). 1,142 words, ~1,963 tokens.

Download SKILL.mdSave it as .claude/skills/code-review/SKILL.md (or your agent's skills folder).
name
code-review
description
Review a pull request or a proposed change to this repository. Use when asked to review a pull request, a diff, or a branch, and when a review finding needs evidence before it is reported.
license
Apache-2.0

Code review

This skill covers what to review and what counts as evidence and as a real problem. The standing instructions of the repository are background that always applies; do not repeat them here.

It does not prescribe how a review is presented: the structure, the wording and any severity labels of comments follow the conventions of the review system that runs the review.

Review flow

  1. Name the object and the intent. State what the change claims and what would make it wrong.
  2. Walk the catalog family by family, and one dimension at a time inside a family: a single read-through lets the most visible change absorb the attention and hides the rest.
  3. Cover the whole catalog for every pull request, whatever it changes: code, documentation, dependencies, build configuration, generated files, release metadata, or repository material. A dimension that does not apply is still accounted for, with the reason it does not apply; nothing is dropped silently.
  4. Check the evidence. Recompute what can be recomputed: counts, commands, exit codes, file lists, tree hashes.
  5. Name the gaps and the conflicts. Tradeoffs between families, and every question the reviewed material does not answer.
  6. State the conclusion, with the artifact behind each problem it raises and an action for each of them.

What settles a dimension

A dimension is settled by an artifact: command output, a file, a test, a hash, or a documented decision. A claim that cannot be checked against an artifact is not verified, and "looks fine" is not evidence.

When the artifact is missing, name the one that would settle the question and treat the question as open rather than deciding it.

Dimension catalog

Nine families, nineteen dimensions. Each dimension states a principle and the artifact that settles it; the concrete form of that artifact is whatever the repository under review documents.

A · Intent

  • 1 Scope and intent. The change does only what it claims, and every file it touches belongs to that claim; unrelated reformatting, drive-by refactors, moved files and dependency churn are problems to raise.

B · Correctness

  • 2 Behavioural correctness. The observable behaviour matches the modelled API and the reference implementation, including the alternative addressing forms a request may use; name the suite that covers the behaviour, and treat a behaviour change without one as a gap in the evidence.
  • 3 Error paths and failure modes. Empty input, missing resources, zero-length payloads, concurrent writers, timeouts, half-closed connections, resets and streams that end early; a silent fallback is a real problem, because reporting success while nothing happened is the worst failure mode.
  • 4 Wire format and specification compliance. Status codes, error codes, document shape, timestamp precision and date forms, framing and trailers, percent-encoding and query parsing follow the specification exactly; say which specification or RFC the behaviour is checked against.

C · Compatibility

  • 5 Public interface and versioning. Public interfaces and feature combinations keep their promises, generated output is identical after a regeneration, and the compatibility check of the project runs when a published surface changes.
  • 6 Toolchain and platform baseline. The toolchain baseline the project declares is respected, and the behaviour that differs per platform is stated for the platforms the project supports.
  • 7 Dependency surface structure. The default dependency set is an invariant: a new optional dependency must not appear without its feature, and a development dependency must not pull runtime components into a default build. State a dependency invariant on two bases, the node count and the enabled feature set, because a change can leave the node count identical while the feature set shrinks. An unused direct dependency is a real problem, not a harmless leftover.

D · Security

  • 8 Memory and cryptography, transport. Unsafe constructs are absent or justified, and transport security, certificate handling and signature verification use their primitives correctly.
  • 9 Input handling and amplification. Work stays linear in the input with no amplification and no unbounded buffers, and untrusted input is validated before it is used.
  • 10 Known vulnerabilities. The dependency set is checked for known advisories, and an accepted advisory is recorded with its rationale and its exposure.

E · Performance and resources

  • 11 Runtime performance and measurement validity. Measurements use valid input and are reproducible, and the baseline they are compared against is stated; timings from malformed input are robustness data, not design evidence.
  • 12 Memory streaming and build resources. Streaming stays bounded in memory with back pressure, and heavy builds respect the build resources of the environment.
Show full SKILL.md (401 more words)Show less

F · Verifiability

  • 13 Tests as evidence. The tests fail when the production change is reverted; a filtered suite is quantified as cases run of cases that exist; a check that accepts a good sample rejects a deliberately broken one.
  • 14 Gates and reproducibility. A command and its exit code per claim; the aggregate gate runs after the last commit and leaves a clean tree, because formatting and generation rewrite files. Require the check-only variants the project automation runs, and remember that an all-features build is blind to the default configuration.

G · Documentation and usability

  • 15 Documentation and usability. The documentation the project ships stays consistent with the change: names, flags, trust instructions, release order; documentation links follow the project style, examples run, and badges and version numbers match reality.

H · Maintainability and history

  • 16 Maintainability and history. Each commit is self-consistent, with no later commit repairing an earlier one, and after a rewrite the tree is identical to the previous tip; generated and hand-written files stay separated, and naming and comments describe behaviour rather than the session that produced them. An unreferenced declaration or a piece of dead code is a real problem, not a harmless leftover.

I · Delivery and compliance

  • 17 Public layer and disclosure. Repository content carries no material that only exists on the author machine: session or editor state paths, scratch and planning documents, local task identifiers, or notes that assume a private context; pull request bodies keep their required sections and their disclosure.
  • 18 Commit conventions. Commit messages follow the conventions the repository documents, including the scope it requires and the markers it asks for on a breaking change.
  • 19 Release and packaging. The packaging check accepts the manifest and its file list excludes local material; a component that gains a dependency is released after that dependency is available publicly, and versions and placeholders are consistent.

Calibration

Judge what the change touches and whether it is self-consistent, not how large it is: line counts, file counts and diff sizes are heuristics, and a size threshold is a preference rather than a defect.

A change in behaviour, in the evidence behind a claim, or in compatibility is a real problem to raise. Naming, wording and formatting are preferences, and a preference is never a reason to block a change. List the conflicts between dimensions and families explicitly, give every problem an action, and do not restate the diff.

© s3s-project, 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 .agents/skills/code-review of s3s-project/s3s.

Open the folder on GitHubat commit 1e1c52e

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 skills3s-project/s3s311—~2kAutomated safety check: PassApache-2.0
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Understand Diff AnalysisEgonex-AI/Understand-Anything85k1 repos~1.4kAutomated safety check: PassMIT
WooCommerce Code Reviewwoocommerce/woocommerce11k3 repos~1.1kAutomated safety check: PassCustom licence
Open Code Review CLIalibaba/open-code-review44k—~3.1kAutomated safety check: PassApache-2.0
GitHub Review Iterationprisma/orm48k—~2.2kAutomated safety check: PassApache-2.0

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Categories

Questions about Code Review

What does Code Review do?

Review a pull request or a proposed change to this repository. Code Review is an agent skill from s3s-project/s3s. Review a pull request or a proposed change to this repository.

When should I use Code Review?

Code Review fits situations like: asked to review a pull request; when a review finding needs evidence before it is reported.

How do I install Code Review in Claude Code?

Run `npx skills add s3s-project/s3s --skill code-review -a claude-code`. Or copy the skill folder (.agents/skills/code-review in s3s-project/s3s) 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 s3s-project/s3s --skill code-review -a codex`. Or copy the skill folder (.agents/skills/code-review in s3s-project/s3s) 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 s3s-project/s3s --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 (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Code Review use?

About 2k tokens (SKILL.md is roughly 7.9k 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), Understand Diff Analysis (Egonex-AI/Understand-Anything, 85k stars), WooCommerce Code Review (woocommerce/woocommerce, 11k stars) and Open Code Review CLI (alibaba/open-code-review, 44k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Code Review?

s3s-project (a GitHub organization) maintains it in s3s-project/s3s, which has 311 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on October 7, 2026.

Source: s3s-project/s3s on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.