Borrowing it
Nothing to install: this file belongs to andrew-yangy/gru-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/andrew-yangy/gru-ai/main/.claude/skills/code-review-excellence/SKILL.mdgit clone --depth 1 https://github.com/andrew-yangy/gru-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/andrew-yangy/gru-ai/code-review-excellence)<a href="https://agentmods.dev/skills/andrew-yangy/gru-ai/code-review-excellence"><img src="https://agentmods.dev/badge/skills/andrew-yangy/gru-ai/code-review-excellence/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/andrew-yangy/gru-ai/code-review-excellence"><img src="https://agentmods.dev/badge/skills/andrew-yangy/gru-ai/code-review-excellence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00092 | $0.01837 |
| Opus 5 | $0.00046 | $0.00919 |
| Sonnet 5 | $0.00018 | $0.00367 |
| Haiku 4.5 | $0.00009 | $0.00184 |
Grade A, and why
code-review-excellence scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- code-review-excellence-hardened — 86% identical, 13 lines differ
How it starts
The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Excellence
Transform code reviews from gatekeeping to knowledge sharing through constructive feedback, systematic analysis, and collaborative improvement.
When to Use This Skill
- Reviewing pull requests and code changes
- Establishing code review standards for teams
- Mentoring junior developers through reviews
- Conducting architecture reviews
- Creating review checklists and guidelines
- Improving team collaboration
- Reducing code review cycle time
- Maintaining code quality standards
Core Principles
1. The Review Mindset
Goals of Code Review:
- Catch bugs and edge cases
- Ensure code maintainability
- Share knowledge across team
- Enforce coding standards
- Improve design and architecture
- Build team culture
Not the Goals:
- Show off knowledge
- Nitpick formatting (use linters)
- Block progress unnecessarily
- Rewrite to your preference
2. Effective Feedback
Good Feedback is:
- Specific and actionable
- Educational, not judgmental
- Focused on the code, not the person
- Balanced (praise good work too)
- Prioritized (critical vs nice-to-have)
❌ Bad: "This is wrong."
✅ Good: "This could cause a race condition when multiple users
access simultaneously. Consider using a mutex here."
❌ Bad: "Why didn't you use X pattern?"
✅ Good: "Have you considered the Repository pattern? It would
make this easier to test. Here's an example: [link]"
❌ Bad: "Rename this variable."
✅ Good: "[nit] Consider `userCount` instead of `uc` for
clarity. Not blocking if you prefer to keep it."
3. Review Scope
What to Review:
- Logic correctness and edge cases
- Security vulnerabilities
- Performance implications
- Test coverage and quality
- Error handling
- Documentation and comments
- API design and naming
- Architectural fit
What Not to Review Manually:
- Code formatting (use Prettier, Black, etc.)
- Import organization
- Linting violations
- Simple typos
Review Process
Phase 1: Context Gathering (2-3 minutes)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 199 lines · 92 tokens per session scan A 55bec5ed247c
code-review-excellence is a skill published in the GitHub repository andrew-yangy/gru-ai (153 stars, last pushed 6mo ago), licensed MIT. It adds 92 tokens to every session and 1,837 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
code-review
Two-mode skill: (1) adversarial review — spec compliance + code quality + security, confidence-scored findings with file:line evidence; (2) receiving review — verify-before- agreeing discipline for acting on external/human review feedback.
codebase-hygiene
Two-mode skill: (1) find semantic duplicates — functions doing the same thing under different names, invisible to copy-paste detectors; (2) deepen shallow modules — thin wrappers and pass-through layers that spread complexity. Advisory and read-only; changes route through BUILD with full gates.
generator-evaluator-loop
Orchestrate a Coder→Quality iteration loop against a story's Verification contract. Use when a story has a complete Verification section and is ready for execution with automated review.
review-before-commit
Run a behavioral self-check before persisting story results. Verifies diff simplicity, scope adherence, and verifiable completion against enso §10 behavioral principles. Use when a story's implementation is complete and ready to close.
comet-verify
Comet Phase 4: Verify and Close. Invoke with /comet-verify. Verify implementation matches design, handle development branch.
gsd-ns-review
Route to the appropriate quality / review skill based on the user's intent. gsd-code-review-fix was absorbed by gsd-code-review --fix in #2790.