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Agent skill

Review

by juliepy in juliepy/AI-Engineer-from-scrach

Delegate the latest implementation diff to the code-reviewer sub-agent for a PASS/CONCERNS verdict against CLAUDE.md rules, then write the verdict to reports/<feature-review.md.

No licenceAuto-check passedAgent Workflows

Install Review

skills CLI
$ npx skills add juliepy/AI-Engineer-from-scrach --skill review -a claude-code

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

GitHub CLI
$ gh skill install juliepy/AI-Engineer-from-scrach 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/juliepy/AI-Engineer-from-scrach.git skills-src && mkdir -p .claude/skills && cp -r skills-src/06-harnes/harness-engineering-demo/.claude/skills/review .claude/skills/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
review
GitHub stars
436
Token cost
~417 tokens
SKILL.md length
176 words
Files
1
Skills in repo
15
Repo updated
First seen
Licence
None found

At a glance

Delegate the latest implementation diff to the code-reviewer sub-agent for a PASS/CONCERNS verdict against CLAUDE.md rules, then write the verdict to reports/<feature-review.md.

  • Works in 5 steps: Identify the implementation report → Gather the diff → Delegate to the code-reviewer sub-agent → …
  • Tasks that involve Code review
  • Calls git
  • Tasks that involve Subagents

What it does

Review is an agent skill from juliepy/AI-Engineer-from-scrach. Delegate the latest implementation diff to the code-reviewer sub-agent for a PASS/CONCERNS verdict against CLAUDE.md rules, then write the verdict to reports/<feature-review.md.

Its SKILL.md is about 420 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 Agent Workflows, covering Code review, Subagents and Agent instruction files.

When your agent uses it

  • Tasks that involve Code review
  • Tasks that involve Subagents
  • Tasks that involve Agent instruction files

Example prompts

  • “/review”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Identify the implementation report
  2. Gather the diff
  3. Delegate to the code-reviewer sub-agent
  4. Write the review report
  5. Report back

What it can do on your machine

Read from SKILL.md and the folder at commit d9e02cb. 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

    Shell commands in SKILL.md call:

    • git

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

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    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

Review loads about 417 tokens when it runs. Until then it costs about 46 tokens; SKILL.md has 176 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~46
When it runs · the whole SKILL.md, loaded when a task matches
~417

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

Without a licence we can't republish the file, so here is its outline and opening line. It has 176 words (~417 tokens).

“Usage: /review (run after /implement and before committing)”

— opening of SKILL.md by juliepy
name
review
disable-model-invocation
true

Read the full SKILL.md on GitHub

Files

Just SKILL.md in 06-harnes/harness-engineering-demo/.claude/skills/review of juliepy/AI-Engineer-from-scrach.

Open the folder on GitHubat commit d9e02cb

Compare with similar skills

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.

Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Review this skilljuliepy/AI-Engineer-from-scrach436—~417Automated safety check: PassNone
Ad ReviewCorridorTech/PoseCap224—~2.4kAutomated safety check: NotesApache-2.0
O2 Review Loopopenobserve/openobserve22k—~3.7kAutomated safety check: PassAGPL-3.0
Elvesaigorahub/elves222—~16kAutomated safety check: NotesMIT
Reviewmorpho-org/morpho-blue-liquidation-bot115—~703Automated safety check: PassMIT
Subagent-Driven DevelopmentHoangNguyen0403/agent-skills-standard571—~1.3kAutomated safety check: PassMIT

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More from juliepy/AI-Engineer-from-scrach

All 15 skills in this repo

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  • Implement

    juliepy/AI-Engineer-from-scrach

    Read a plan file, execute every task in dependency order with per-task validation, then write an implementation report to reports/<feature-slug-implementation-report.md.

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  • Plan

    juliepy/AI-Engineer-from-scrach

    Analyze a ticket or feature description, read the codebase, identify risks, and write a context-rich implementation plan to plans/<feature-slug-plan.md.

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  • Validate

    juliepy/AI-Engineer-from-scrach

    Run the full quality gate (ruff + mypy + pytest + tsc + vitest) and report PASS/FAIL for each command.

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Categories

Questions about Review

What does Review do?

Delegate the latest implementation diff to the code-reviewer sub-agent for a PASS/CONCERNS verdict against CLAUDE.md rules, then write the verdict to reports/<feature-review.md. Review is an agent skill from juliepy/AI-Engineer-from-scrach.md.

When should I use Review?

Review fits situations like: tasks that involve Code review; tasks that involve Subagents; tasks that involve Agent instruction files.

How do I install Review in Claude Code?

Run `npx skills add juliepy/AI-Engineer-from-scrach --skill review -a claude-code`. Or copy the skill folder (06-harnes/harness-engineering-demo/.claude/skills/review in juliepy/AI-Engineer-from-scrach) into .claude/skills/review in your project. Claude Code loads it when a task matches its description.

How do I install Review in Codex?

Run `npx skills add juliepy/AI-Engineer-from-scrach --skill review -a codex`. Or copy the skill folder (06-harnes/harness-engineering-demo/.claude/skills/review in juliepy/AI-Engineer-from-scrach) into .agents/skills/review in your project. Codex loads it when a task matches its description.

Can I use 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 juliepy/AI-Engineer-from-scrach --skill 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/review, .gemini/skills/review, .github/skills/review and .opencode/skills/review in your project.

What does Review need to run?

Going by SKILL.md and its folder, Review needs the command-line tools its instructions call (git).

Does Review access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is 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 Review use?

No licence was found for Review or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.

How many tokens does Review use?

About 417 tokens (SKILL.md is roughly 1.7k 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 Review?

Skills that share tags, products or a category with Review: Ad Review (CorridorTech/PoseCap, 224 stars), O2 Review Loop (openobserve/openobserve, 22k stars), Elves (aigorahub/elves, 222 stars) and Review (morpho-org/morpho-blue-liquidation-bot, 115 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Review?

juliepy (a GitHub user) maintains it in juliepy/AI-Engineer-from-scrach, which has 436 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on September 6, 2026.

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