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Agent skill

Code Review

by atomisticnet in atomisticnet/aenet

Review aenet commits, branches, diffs, or working-tree changes for correctness, numerical validity, compatibility, maintainability, and test quality.

MPL-2.0Auto-check passedDevelopment

Install Code Review

skills CLI
$ npx skills add atomisticnet/aenet --skill code-review -a claude-code

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

GitHub CLI
$ gh skill install atomisticnet/aenet 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/atomisticnet/aenet.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
129
Token cost
~537 tokens
SKILL.md length
229 words
Files
2 (incl. references)
Skills in repo
4
Repo updated
First seen
Licence
MPL-2.0

At a glance

Review aenet commits, branches, diffs, or working-tree changes for correctness, numerical validity, compatibility, maintainability, and test quality.

  • Tasks that involve Code review
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Code Review is an agent skill from atomisticnet/aenet. Review aenet commits, branches, diffs, or working-tree changes for correctness, numerical validity, compatibility, maintainability, and test quality. Reviews are read-only unless fixes are requested.

Its SKILL.md is about 540 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/review-checklist.md`).

It sits in Development, covering Code review. The repository describes itself as: Atomic interaction potentials based on artificial neural networks. The licence is MPL-2.0.

When your agent uses it

  • Tasks that involve Code review

Example prompts

  • “/code-review”

What it can do on your machine

Read from SKILL.md and the folder at commit 9403bc5. 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 537 tokens when it runs, and up to ~1.3k if it reads all its reference files. Until then it costs about 53 tokens; SKILL.md has 229 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~53
When it runs · the whole SKILL.md, loaded when a task matches
~537
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.3k

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 atomisticnet/aenet at commit 9403bc5, republished under its MPL-2.0 licence (© atomisticnet). 229 words, ~537 tokens.

Download SKILL.mdSave it as .claude/skills/code-review/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
code-review
description
Review aenet commits, branches, diffs, or working-tree changes for correctness, numerical validity, compatibility, maintainability, and test quality. Reviews are read-only unless fixes are requested.

Code Review

Follow AGENTS.md and read shared engineering standards.

Resolve the requested review boundary: commits, branch relative to merge base, staged/unstaged changes, or another explicit range. Include requested refinement commits. Read the complete scoped diff, governing tasks, relevant neighboring code, callers, tests, documentation, and build configuration. Do not silently reduce a history review to the final snapshot.

Apply the review checklist. Prioritize observable failures, numerical validity, API/ABI and format compatibility, MPI behavior, and meaningful test evidence. Evaluate simplicity: each new abstraction, option, fallback, or dependency should serve an actual contract. Do not report stylistic preferences as defects without concrete impact.

Use the build-test skill for relevant validation. Run checks in isolated build directories without changing reviewed sources or tests. Distinguish unavailable configurations from failed validation. Consult the documentation skill when maintained documentation or public interface comments are materially affected.

Report actionable findings first, ordered by severity. Give a precise file and line location, triggering scenario, and consequence for each finding:

  • P0: immediate catastrophic or security-critical impact.
  • P1: release-blocking correctness, data-loss, or major compatibility bug.
  • P2: substantive defect, missing requirement, or concrete regression risk.
  • P3: low-risk improvement with a demonstrated maintenance or usability benefit.

Separate findings from questions and assumptions. Summarize checks and remaining coverage gaps. State explicitly when there are no actionable findings; do not manufacture minor issues. Do not implement fixes or add a fix plan unless requested.

© atomisticnet, MPL-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

SKILL.md and 1 other file (references) in skills/code-review of atomisticnet/aenet.

  • SKILL.md
  • references/review-checklist.md

Open the folder on GitHubat commit 9403bc5

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 skillatomisticnet/aenet129—~537Automated safety check: PassMPL-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

Similar skills

  • PR Babysitter

    openinterpreter/openinterpreter

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    69k GitHub starsUsed in 3 repos~4.2k tokens
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  • Code Review Checklist

    shareAI-lab/learn-claude-code

    Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.

    78k GitHub starsUsed in 5 repos~1.1k tokens
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  • Backend Code Review

    langflow-ai/langflow

    Review backend code for quality, security, maintainability, and best practices based on established checklist rules.

    156k GitHub stars~3.5k tokensUpdated today
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  • Understand Diff Analysis

    Egonex-AI/Understand-Anything

    Reads your git changes or a pull request against a prebuilt knowledge graph of the project to explain what changed, which components are affected and what is risky.

    85k GitHub starsUsed in 1 repo~1.4k tokens
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    69k GitHub stars~2k tokensUpdated today
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  • Backend Code Review

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  • Build Test

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    129 GitHub stars~1k tokensUpdated 12 days ago
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  • Issue Workflow

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    Plan, implement, review, validate, and close aenet work tracked by shared or local issues, or explicitly linked GitHub issues.

    129 GitHub stars~980 tokensUpdated 12 days ago
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  • Documentation

    atomisticnet/aenet

    Create or substantially revise aenet maintained documentation, Fortran or C interface comments, CLI help, and runnable examples using the repository's current documentation sources.

    129 GitHub stars~654 tokensUpdated 12 days ago
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Categories

Questions about Code Review

What does Code Review do?

Review aenet commits, branches, diffs, or working-tree changes for correctness, numerical validity, compatibility, maintainability, and test quality. Code Review is an agent skill from atomisticnet/aenet. Review aenet commits, branches, diffs, or working-tree changes for correctness, numerical validity, compatibility, maintainability, and test quality.

When should I use Code Review?

Code Review fits situations like: tasks that involve Code review.

How do I install Code Review in Claude Code?

Run `npx skills add atomisticnet/aenet --skill code-review -a claude-code`. Or copy the skill folder (skills/code-review in atomisticnet/aenet) 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 atomisticnet/aenet --skill code-review -a codex`. Or copy the skill folder (skills/code-review in atomisticnet/aenet) 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 atomisticnet/aenet --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 MPL-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 537 tokens (SKILL.md is roughly 2.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 726 tokens, read only when the agent opens those files.

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?

atomisticnet (a GitHub organization) maintains it in atomisticnet/aenet, which has 129 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on September 25, 2026.

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