Agent skill

Requesting Code Review

by GanyuanRan in GanyuanRan/Aegis

A skill your agent uses when requesting independent code review, after implementation slices, before merging high-risk work, or when verification exposes evidence, baseline, architecture…

MITAuto-check passedDevelopment

Install Requesting Code Review

skills CLI
$ npx skills add GanyuanRan/Aegis --skill requesting-code-review -a claude-code

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

GitHub CLI
$ gh skill install GanyuanRan/Aegis 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/GanyuanRan/Aegis.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/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
1.3k
Used in
1 other repo
Token cost
~2.2k tokens
SKILL.md length
936 words
Files
2
Skills in repo
21
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when requesting independent code review, after implementation slices, before merging high-risk work, or when verification exposes evidence, baseline, architecture…

  • Works in 11 steps: What exact scope is being reviewed → What plan, requirement, or contract… → What Product / Requirement Baseline… → …
  • Requesting independent code review
  • SKILL.md covers When to Request Review, Required Outputs, How to Request and Example, plus 4 more sections
  • Calls git

What it does

Requesting Code Review is an agent skill from GanyuanRan/Aegis. Use when requesting independent code review, after implementation slices, before merging high-risk work, or when verification exposes evidence, baseline, architecture, compatibility, or retirement uncertainty.

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `code-reviewer.md`).

It sits in Development, covering Code review. The repository describes itself as: Make AI coding agents architecture-aware: baseline-first, evidence-verified, drift-checked, and safe across long tasks. The licence is MIT.

When your agent uses it

  • Requesting independent code review
  • After implementation slices
  • Before merging high-risk work
  • Verification exposes evidence

Example prompts

  • “/requesting-code-review”

Workflow steps

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

  1. What exact scope is being reviewed
  2. What plan, requirement, or contract defines success
  3. What Product / Requirement Baseline defines accepted behavior and non-goals
  4. What Architecture / Runtime Boundary Baseline defines the expected architecture state
  5. What fresh evidence already exists
  6. What compatibility boundary must still hold
  7. What old owner / fallback / patch stays, shrinks, or retires
  8. What the reviewer must specifically validate
  9. Whether the reviewer is providing advisory review only, or also any higher-level merge recommendation
  10. Aegis Visibility: why findings-first ordering, evidence sufficiency,
  11. Semantic context scope: which relevant canonical terms, deprecated

What it can do on your machine

Read from SKILL.md and the folder at commit 4edf34e. 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

Requesting Code Review loads about 2.2k tokens when it runs. Until then it costs about 58 tokens; SKILL.md has 936 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~58
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k

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 GanyuanRan/Aegis at commit 4edf34e, republished under its MIT licence (© GanyuanRan). 936 words, ~2,209 tokens.

Download SKILL.mdSave it as .claude/skills/requesting-code-review/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
requesting-code-review
description
Use when requesting independent code review, after implementation slices, before merging high-risk work, or when verification exposes evidence, baseline, architecture, compatibility, or retirement uncertainty.

Requesting Code Review

Dispatch a reviewer subagent using the canonical code-reviewer.md template to catch issues before they cascade. The reviewer gets precisely crafted context for evaluation — never your session's history. This keeps the reviewer focused on the work product, not your thought process, and preserves your own context for continued work.

This skill is the canonical review-request workflow for method-pack implementation work. Use it to request review only after you have enough evidence, enough context, and a clear authority boundary for what the reviewer is being asked to assess.

Core principle: Review early, review often.

Findings First: Reviews lead with concrete findings before summary. Use bugs first, risk first, tests first. Strengths and general assessment are still useful, but they must not bury correctness, evidence, architecture, or retirement problems.

Review readiness is not merge approval. A review can reduce uncertainty and recommend readiness, but it does not replace verification-before-completion and does not grant completion authority.

When to Request Review

Mandatory:

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

Optional but valuable:

  • When stuck (fresh perspective)
  • Before refactoring (baseline check)
  • After fixing complex bug

Required Outputs

Before you leave this workflow, you must be able to state:

  1. What exact scope is being reviewed
  2. What plan, requirement, or contract defines success
  3. What Product / Requirement Baseline defines accepted behavior and non-goals
  4. What Architecture / Runtime Boundary Baseline defines the expected architecture state
  5. What fresh evidence already exists
  6. What compatibility boundary must still hold
  7. What old owner / fallback / patch stays, shrinks, or retires
  8. What the reviewer must specifically validate
  9. Whether the reviewer is providing advisory review only, or also any higher-level merge recommendation
  10. Aegis Visibility: why findings-first ordering, evidence sufficiency, baseline alignment, compatibility, or retirement risk matters for this review request
  11. Semantic context scope: which relevant canonical terms, deprecated aliases, or public naming boundaries the review must preserve

Review in this method pack is advisory and evidence-oriented. It is not authoritative completion by itself.

How to Request

1. Gather minimum review inputs:

  • What was implemented
  • What requirement / plan / spec / ADR it should match
  • What baseline / current authority docs the diff must align with, including requirements/product alignment and architecture/current-authority alignment
  • What evidence already exists (tests, commands, logs, screenshots, diff summary)
  • What compatibility boundary or risk deserves reviewer attention
  • Whether there is any old path, fallback, duplicate owner, or temporary patch that should retire
  • Whether the diff contains durable architecture decisions that need ADR Auto Backfill or baseline sync findings
  • Whether recording-architecture-decisions was used, or should be used, when an ADR action or baseline sync closure is in scope
  • Relevant active CONTEXT.md language when public/domain naming is in scope; passive reading does not load active modeling

If you cannot answer these, stop and gather them before dispatching review.

2. Define the Git review scope:

bash
# Before the coordinator's task commit
REVIEW_SCOPE=working-tree
BASE_SHA=$(git rev-parse HEAD)

# Or for already committed work
REVIEW_SCOPE=committed-range
BASE_SHA=<known-start>
HEAD_SHA=$(git rev-parse HEAD)

For working-tree review, identify task-owned untracked paths explicitly. Do not stage merely to make them visible to a reviewer.

3. Dispatch reviewer subagent:

Use the Task tool with a general-purpose reviewer subagent. Fill the canonical template at requesting-code-review/code-reviewer.md; do not rely on a separate named agent prompt.

Placeholders:

  • {WHAT_WAS_IMPLEMENTED} - What you just built
  • {PLAN_OR_REQUIREMENTS} - What it should do
  • {EVIDENCE} - Fresh tests, commands, logs, or verification already available
  • {COMPATIBILITY_BOUNDARY} - What existing behavior or interfaces must not break
  • {RETIREMENT_NOTES} - Old owner / fallback / patch / duplicate branch and expected disposition
  • {REVIEW_SCOPE} - working-tree or committed-range
  • {BASE_SHA} - Starting commit
  • {HEAD_SHA} - Ending commit, or WORKTREE
  • {DESCRIPTION} - Brief summary

4. Act on feedback:

  • Fix Critical issues immediately
  • Fix Important issues before proceeding
  • Note Minor issues for later
  • Push back if reviewer is wrong (with reasoning)
  • If feedback reveals evidence gaps, run the missing verification instead of arguing from confidence
  • If feedback reveals Design Defect / Implementation Drift, stale logic, or a legacy alias such as architecture drift, decide explicitly whether to repair now, correct the baseline, or record retirement conditions
Show full SKILL.md (291 more words)Show less

Example

[Just completed Task 2: Add verification function]

You: Let me request code review before proceeding.

BASE_SHA=$(git log --oneline | grep "Task 1" | head -1 | awk '{print $1}')
HEAD_SHA=$(git rev-parse HEAD)

[Dispatch reviewer subagent using requesting-code-review/code-reviewer.md]
  WHAT_WAS_IMPLEMENTED: Verification and repair functions for conversation index
  PLAN_OR_REQUIREMENTS: Task 2 from docs/aegis/plans/deployment-plan.md
  EVIDENCE: pytest tests/index/test_verify.py -v -> 12 passed
  COMPATIBILITY_BOUNDARY: Existing index format and CLI flags must remain stable
  RETIREMENT_NOTES: Legacy repair fallback still exists in old helper; remove once new path covers all four issue types
  BASE_SHA: a7981ec
  HEAD_SHA: 3df7661
  DESCRIPTION: Added verifyIndex() and repairIndex() with 4 issue types

[Subagent returns]:
  Strengths: Clean architecture, real tests
  Issues:
    Important: Missing progress indicators
    Minor: Magic number (100) for reporting interval
  Assessment: Ready to proceed

You: [Fix progress indicators]
[Continue to Task 3]

Integration with Workflows

Subagent-Driven Development:

  • Review after EACH task
  • Catch issues before they compound
  • Fix before moving to next task

Executing Plans:

  • Review after each batch (3 tasks)
  • Get feedback, apply, continue

Ad-Hoc Development:

  • Review before merge
  • Review when stuck

What the Reviewer Must Check

The review request must prompt the reviewer to inspect at least:

  • Findings First: bugs first, risk first, tests first
  • evidence sufficiency
  • baseline / current authority alignment
  • requirements/product alignment against accepted problem, success evidence, and non-goals
  • architecture/current-authority alignment against owner, contract, source-of-truth, compatibility, and retirement boundaries
  • Design Defect / Implementation Drift classification with scope: requirements | architecture | both
  • legacy phrase mapping: baseline defect, architecture defect, and architecture drift must map back to Design Defect / Implementation Drift rather than becoming parallel result vocabularies
  • duplicate owner risk
  • compatibility boundary
  • missing ADR Auto Backfill or baseline sync findings for durable architecture decisions
  • missing recording-architecture-decisions handoff when ADR action or baseline sync closure is in scope
  • unverified claims or missing proof
  • old logic that should retire, stay temporarily, or converge
  • public-name drift, deprecated-term re-entry, or a semantic change recorded in code/docs without composing establishing-project-context

If the review only asks “is this code good?”, it is underspecified.

Red Flags

Never:

  • Skip review because "it's simple"
  • Ignore Critical issues
  • Proceed with unfixed Important issues
  • Argue with valid technical feedback
  • Treat reviewer approval as equivalent to authoritative completion
  • Ask for review without sharing what evidence already exists
  • Add new logic without telling the reviewer what happens to the old path

If reviewer wrong:

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

Review Boundaries

  • Review can recommend merge readiness, residual risk, and follow-up work
  • Review cannot grant authoritative completion by itself
  • Review should reduce uncertainty, not hide it

See template at: requesting-code-review/code-reviewer.md

© GanyuanRan, MIT. 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 in skills/requesting-code-review of GanyuanRan/Aegis.

  • SKILL.md
  • code-reviewer.md

Open the folder on GitHubat commit 4edf34e

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in GanyuanRan/Aegis, which our catalogue first saw on October 7, 2026.

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.

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Backend Code Reviewlangflow-ai/langflow156k—~3.5kAutomated 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 requesting independent code review, after implementation slices, before merging high-risk work, or when verification exposes evidence, baseline, architecture…. Requesting Code Review is an agent skill from GanyuanRan/Aegis. Use when requesting independent code review, after implementation slices, before merging high-risk work, or when verification exposes evidence, baseline, architecture, compatibility, or retirement uncertainty.

When should I use Requesting Code Review?

Requesting Code Review fits situations like: requesting independent code review; after implementation slices; before merging high-risk work; verification exposes evidence.

How do I install Requesting Code Review in Claude Code?

Run `npx skills add GanyuanRan/Aegis --skill requesting-code-review -a claude-code`. Or copy the skill folder (skills/requesting-code-review in GanyuanRan/Aegis) 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 GanyuanRan/Aegis --skill requesting-code-review -a codex`. Or copy the skill folder (skills/requesting-code-review in GanyuanRan/Aegis) 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 GanyuanRan/Aegis --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).

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 (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Requesting Code Review use?

About 2.2k tokens (SKILL.md is roughly 8.8k 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: 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, 86k 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?

GanyuanRan (a GitHub user) maintains it in GanyuanRan/Aegis, which has 1,327 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on October 3, 2026.

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