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Agent skill

Requesting Code Review

by RedWoodOG in RedWoodOG/Hermes-Desktop

A skill your agent uses when completing tasks, implementing major features, or before merging.

MITAuto-check passedDevelopment

Install Requesting Code Review

skills CLI
$ npx skills add RedWoodOG/Hermes-Desktop --skill requesting-code-review -a claude-code

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

GitHub CLI
$ gh skill install RedWoodOG/Hermes-Desktop requesting-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/RedWoodOG/Hermes-Desktop.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/software-development/requesting-code-review .claude/skills/requesting-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
requesting-code-review
GitHub stars
177
Token cost
~1.5k tokens
SKILL.md length
464 words
Files
1
Skills in repo
62
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when completing tasks, implementing major features, or before merging.

  • Works in 4 steps: Self-Review First → Gather Context → Dispatch Reviewer Subagent → …
  • Completing tasks
  • SKILL.md covers Overview, When to Request Review, Review Process and Review Dimensions, plus 5 more sections
  • Calls git and pytest

What it does

Requesting Code Review is an agent skill from RedWoodOG/Hermes-Desktop. Use when completing tasks, implementing major features, or before merging. Validates work meets requirements through systematic review process.

Its SKILL.md is about 1.5k 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, Literature review and Subagents. The licence is MIT.

When your agent uses it

  • Completing tasks
  • Implementing major features

Example prompts

  • “/requesting-code-review”

Requirements

  • Python 3

Workflow steps

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

  1. Self-Review First
  2. Gather Context
  3. Dispatch Reviewer Subagent
  4. Act on Feedback

What it can do on your machine

Read from SKILL.md and the folder at commit be46b39. 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
    • pytest

    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

Requesting Code Review loads about 1.5k tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 464 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~42
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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 RedWoodOG/Hermes-Desktop at commit be46b39, republished under its MIT licence (© RedWoodOG). 464 words, ~1,535 tokens.

Download SKILL.mdSave it as .claude/skills/requesting-code-review/SKILL.md (or your agent's skills folder).
name
requesting-code-review
description
Use when completing tasks, implementing major features, or before merging. Validates work meets requirements through systematic review process.
version
1.1.0
author
Hermes Agent (adapted from obra/superpowers)
license
MIT

Requesting Code Review

Overview

Dispatch a reviewer subagent to catch issues before they cascade. Review early, review often.

Core principle: Fresh perspective finds issues you'll miss.

When to Request Review

Mandatory:

  • After each task in subagent-driven development
  • After completing a major feature
  • Before merge to main
  • After bug fixes

Optional but valuable:

  • When stuck (fresh perspective)
  • Before refactoring (baseline check)
  • After complex logic implementation
  • When touching critical code (auth, payments, data)

Never skip because:

  • "It's simple" — simple bugs compound
  • "I'm in a hurry" — reviews save time
  • "I tested it" — you have blind spots

Review Process

Step 1: Self-Review First

Before dispatching a reviewer, check yourself:

  • Code follows project conventions
  • All tests pass
  • No debug print statements left
  • No hardcoded secrets or credentials
  • Error handling in place
  • Commit messages are clear
bash
# Run full test suite
pytest tests/ -q

# Check for debug code
search_files("print(", path="src/", file_glob="*.py")
search_files("console.log", path="src/", file_glob="*.js")

# Check for TODOs
search_files("TODO|FIXME|HACK", path="src/")
Step 2: Gather Context
bash
# Changed files
git diff --name-only HEAD~1

# Diff summary
git diff --stat HEAD~1

# Recent commits
git log --oneline -5
Step 3: Dispatch Reviewer Subagent

Use delegate_task to dispatch a focused reviewer:

python
delegate_task(
    goal="Review implementation for correctness and quality",
    context="""
    WHAT WAS IMPLEMENTED:
    [Brief description of the feature/fix]

    ORIGINAL REQUIREMENTS:
    [From plan, issue, or user request]

    FILES CHANGED:
    - src/models/user.py (added User class)
    - src/auth/login.py (added login endpoint)
    - tests/test_auth.py (added 8 tests)

    REVIEW CHECKLIST:
    - [ ] Correctness: Does it do what it should?
    - [ ] Edge cases: Are they handled?
    - [ ] Error handling: Is it adequate?
    - [ ] Code quality: Clear names, good structure?
    - [ ] Test coverage: Are tests meaningful?
    - [ ] Security: Any vulnerabilities?
    - [ ] Performance: Any obvious issues?

    OUTPUT FORMAT:
    - Summary: [brief assessment]
    - Critical Issues: [must fix — blocks merge]
    - Important Issues: [should fix before merge]
    - Minor Issues: [nice to have]
    - Strengths: [what was done well]
    - Verdict: APPROVE / REQUEST_CHANGES
    """,
    toolsets=['file']
)
Step 4: Act on Feedback

Critical Issues (block merge):

  • Security vulnerabilities
  • Broken functionality
  • Data loss risk
  • Test failures
  • Action: Fix immediately before proceeding

Important Issues (should fix):

  • Missing edge case handling
  • Poor error messages
  • Unclear code
  • Missing tests
  • Action: Fix before merge if possible

Minor Issues (nice to have):

  • Style preferences
  • Refactoring suggestions
  • Documentation improvements
  • Action: Note for later or quick fix

If reviewer is wrong:

  • Push back with technical reasoning
  • Show code/tests that prove it works
  • Request clarification

Review Dimensions

Correctness
  • Does it implement the requirements?
  • Are there logic errors?
  • Do edge cases work?
  • Are there race conditions?
Code Quality
  • Is code readable?
  • Are names clear and descriptive?
  • Is it too complex? (Functions >20 lines = smell)
  • Is there duplication?
Testing
  • Are there meaningful tests?
  • Do they cover edge cases?
  • Do they test behavior, not implementation?
  • Do all tests pass?
Show full SKILL.md (178 more words)Show less
Security
  • Any injection vulnerabilities?
  • Proper input validation?
  • Secrets handled correctly?
  • Access control in place?
Performance
  • Any N+1 queries?
  • Unnecessary computation in loops?
  • Memory leaks?
  • Missing caching opportunities?

Review Output Format

Standard format for reviewer subagent output:

markdown
## Review Summary

**Assessment:** [Brief overall assessment]
**Verdict:** APPROVE / REQUEST_CHANGES

---

## Critical Issues (Fix Required)

1. **[Issue title]**
   - Location: `file.py:45`
   - Problem: [Description]
   - Suggestion: [How to fix]

## Important Issues (Should Fix)

1. **[Issue title]**
   - Location: `file.py:67`
   - Problem: [Description]
   - Suggestion: [How to fix]

## Minor Issues (Optional)

1. **[Issue title]**
   - Suggestion: [Improvement idea]

## Strengths

- [What was done well]

Integration with Other Skills

With subagent-driven-development

Review after EACH task — this is the two-stage review:

  1. Spec compliance review (does it match the plan?)
  2. Code quality review (is it well-built?)
  3. Fix issues from either review
  4. Proceed to next task only when both approve
With test-driven-development

Review verifies:

  • Tests were written first (RED-GREEN-REFACTOR followed?)
  • Tests are meaningful (not just asserting True)?
  • Edge cases covered?
  • All tests pass?
With writing-plans

Review validates:

  • Implementation matches the plan?
  • All tasks completed?
  • Quality standards met?

Red Flags

Never:

  • Skip review because "it's simple"
  • Ignore Critical issues
  • Proceed with unfixed Important issues
  • Argue with valid technical feedback without evidence

Quality Gates

Must pass before merge:

  • No critical issues
  • All tests pass
  • Review verdict: APPROVE
  • Requirements met

Should pass before merge:

  • No important issues
  • Documentation updated
  • Performance acceptable

Remember

Review early
Review often
Be specific
Fix critical issues first
Quality over speed

A good review catches what you missed.

© RedWoodOG, MIT. 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/software-development/requesting-code-review of RedWoodOG/Hermes-Desktop.

Open the folder on GitHubat commit be46b39

Compare with similar skills

Requesting 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.

Requesting Code Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Requesting Code Review this skillRedWoodOG/Hermes-Desktop177—~1.5kAutomated safety check: PassMIT
GitHub Review Iterationprisma/orm48k—~2.2kAutomated safety check: PassApache-2.0
Cherry Studio PR ReviewCherryHQ/cherry-studio52k—~3.9kAutomated safety check: PassAGPL-3.0
PR Reviewjaemk/self_update961—~1.5kAutomated safety check: NotesMIT
PR Reviewjaemk/cached2.1k—~2.5kAutomated safety check: NotesMIT
Cursor Composer Task DelegateChachamaru127/claude-code-harness3.2k—~4.4kAutomated safety check: NotesMIT

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Categories

Questions about Requesting Code Review

What does Requesting Code Review do?

A skill your agent uses when completing tasks, implementing major features, or before merging. Requesting Code Review is an agent skill from RedWoodOG/Hermes-Desktop. Use when completing tasks, implementing major features, or before merging.

When should I use Requesting Code Review?

Requesting Code Review fits situations like: completing tasks; implementing major features.

How do I install Requesting Code Review in Claude Code?

Run `npx skills add RedWoodOG/Hermes-Desktop --skill requesting-code-review -a claude-code`. Or copy the skill folder (skills/software-development/requesting-code-review in RedWoodOG/Hermes-Desktop) into .claude/skills/requesting-code-review in your project. Claude Code loads it when a task matches its description.

How do I install Requesting Code Review in Codex?

Run `npx skills add RedWoodOG/Hermes-Desktop --skill requesting-code-review -a codex`. Or copy the skill folder (skills/software-development/requesting-code-review in RedWoodOG/Hermes-Desktop) into .agents/skills/requesting-code-review in your project. Codex loads it when a task matches its description.

Can I use Requesting 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 RedWoodOG/Hermes-Desktop --skill requesting-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/requesting-code-review, .gemini/skills/requesting-code-review, .github/skills/requesting-code-review and .opencode/skills/requesting-code-review in your project.

What does Requesting Code Review need to run?

Going by SKILL.md and its folder, Requesting Code Review needs the command-line tools its instructions call (git and pytest). Our summary lists: Python 3.

Does Requesting Code 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 Requesting 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 Requesting Code Review use?

Requesting Code Review is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Requesting Code Review use?

About 1.5k tokens (SKILL.md is roughly 6.1k 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 Requesting Code Review?

Skills that share tags, products or a category with Requesting Code Review: GitHub Review Iteration (prisma/orm, 48k stars), Cherry Studio PR Review (CherryHQ/cherry-studio, 52k stars), PR Review (jaemk/self_update, 961 stars) and PR Review (jaemk/cached, 2.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Requesting Code Review?

RedWoodOG (a GitHub user) maintains it in RedWoodOG/Hermes-Desktop, which has 177 GitHub stars. The repository holds 62 skills in this directory. The repository was last updated on May 30, 2026.

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