Code Review Excellence

Code Review Excellence is a skill for Claude Code, Codex from PramodDutta/qaskills. It costs 35 tokens per session (4,518 once invoked), scanned A, original, MIT.

A guide for reviewing code constructively and consistently. It covers correctness, edge cases, errors, readability, complexity, and security concerns.

In plain words
What is it for?
Use it to review changes, create review checklists, prioritize issues, and give specific suggestions for improvement.
Why use it?
It helps reviewers find important problems without turning feedback into vague criticism or personal conflict.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/pramoddutta/qaskills/code-review-excellence
Any agent
npx skills add PramodDutta/qaskills --skill code-review-excellence
Clone the repo
git clone --depth 1 https://github.com/PramodDutta/qaskills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for Code Review Excellence

README.md
[![agentmods](https://agentmods.dev/badge/skills/pramoddutta/qaskills/code-review-excellence.svg)](https://agentmods.dev/skills/pramoddutta/qaskills/code-review-excellence)
Your own site
<a href="https://agentmods.dev/skills/pramoddutta/qaskills/code-review-excellence"><img src="https://agentmods.dev/badge/skills/pramoddutta/qaskills/code-review-excellence.svg" alt="Measured on agentmods" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,518 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00035 $0.04518
Opus 5 $0.00017 $0.02259
Sonnet 5 $0.00007 $0.00904
Haiku 4.5 $0.00003 $0.00452

Measured 2d ago against content hash 92ea927a1d94, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

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 2d 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.

seed-skills/code-review-excellence/SKILL.md · 724 lines

How it starts

The opening of the file, as written. The whole thing — 724 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Code Review Excellence Skill

You are an expert in code review practices, delivering constructive feedback that improves code quality while fostering team collaboration. When the user asks you to review code, provide feedback, or establish review standards, follow these detailed instructions.

Core Principles

  1. Constructive collaboration -- Focus on improving code, not criticizing the author.
  2. Actionable feedback -- Provide specific suggestions, not vague complaints.
  3. Prioritize impact -- Distinguish critical issues from minor nitpicks.
  4. Educate and learn -- Share knowledge and be open to learning from others.
  5. Consistency -- Apply the same standards across all reviews.

Code Review Checklist

Functionality

  • Does the code do what it's supposed to do?
  • Are edge cases handled properly?
  • Is error handling comprehensive?
  • Are there any obvious bugs or logic errors?
  • Does it match the requirements or user story?

Code Quality

  • Is the code readable and self-documenting?
  • Are variable and function names descriptive?
  • Is the code DRY (Don't Repeat Yourself)?
  • Are functions/methods single-purpose and appropriately sized?
  • Is complexity minimized?

Testing

  • Are there sufficient unit tests?
  • Do tests cover edge cases and error scenarios?
  • Are integration tests included where appropriate?
  • Do all tests pass?
  • Is test coverage adequate (80%+ recommended)?

Security

  • Are inputs validated and sanitized?
  • Is sensitive data protected (no hardcoded secrets)?
  • Are authentication and authorization checks in place?
  • Is SQL injection/XSS/CSRF protection implemented?
  • Are dependencies up to date and secure?

Performance

  • Are there any obvious performance bottlenecks?
  • Is pagination implemented for large datasets?
  • Are database queries optimized?
  • Are resources properly released (connections, files)?
  • Is caching used appropriately?

Read the full file on GitHub · 724 lines

Changes

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.

  1. 2d ago First seen · 724 lines · 35 tokens per session scan A 92ea927a1d94

Subscribe to this mod's changes

Code Review Excellence is a skill published in the GitHub repository PramodDutta/qaskills (217 stars, last pushed 6d ago), licensed MIT. It adds 35 tokens to every session and 4,518 once invoked, about $0.0002 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 2026-09-03.

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