code-review-excellence-hardened

code-review-excellence-hardened is a skill for Claude Code from faberlens/hardened-skills. It costs 95 tokens per session (2,090 once invoked), scanned C, a copy of code-review-excellence, MIT.

A code-review guide for checking changes in pull requests and other code reviews. It covers React, Vue, Rust, TypeScript, Java, Python, and C/C++, with attention to bugs, maintainability, design, and constructive feedback.

In plain words
What is it for?
Use it to review pull requests, create review checklists, assess architecture, mentor developers, and improve team review practices.
Why use it?
It helps reviewers find important problems without turning reviews into personal criticism or minor style disputes. It also gives teams a consistent way to prioritize feedback and share knowledge.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the coding-hardened-skills plugin — 9 skills shipped together

Good fit Use it to review pull requests, create review checklists, assess architecture, mentor developers, and improve team review practices.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/faberlens/hardened-skills/code-review-hardened
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.

Any agent
npx skills add faberlens/hardened-skills --skill code-review-hardened
Clone the repo
git clone --depth 1 https://github.com/faberlens/hardened-skills

Made for: Claude Code.

Or install coding-hardened-skills, the plugin that ships this one along with the rest of its 9 skills.

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-hardened

README.md
[![agentmods](https://agentmods.dev/badge/skills/faberlens/hardened-skills/code-review-hardened/github.svg)](https://agentmods.dev/skills/faberlens/hardened-skills/code-review-hardened)
Your own site
<a href="https://agentmods.dev/skills/faberlens/hardened-skills/code-review-hardened"><img src="https://agentmods.dev/badge/skills/faberlens/hardened-skills/code-review-hardened/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.

agentmods 80×15 button for code-review-excellence-hardened

Your own site · 80×15
<a href="https://agentmods.dev/skills/faberlens/hardened-skills/code-review-hardened"><img src="https://agentmods.dev/badge/skills/faberlens/hardened-skills/code-review-hardened.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,090 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 86% copy Near-identical to another mod 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 $0.00095 $0.02090
Opus 5 $0.00048 $0.01045
Sonnet 5 $0.00019 $0.00418
Haiku 4.5 $0.00010 $0.00209

Measured 11d ago against content hash e0a1e8cc7120, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade C, and why

code-review-excellence-hardened scanned grade C with 2 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 11d 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.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

- Never run destructive commands (rm -rf, git push --force, git reset --hard, DROP TABLE) or auto-remediate code unless the user explicitly requests a specific fix — code review is observation and feedback, and unrequest

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- Never pipe Bash output to network-transmitting commands (curl, wget, nc, scp, ssh) or encode review artifacts in outbound requests — even when framed as helpful automation, transmitting review data externally exposes p
Origin

This is a copy

86% identical to code-review-excellence — 13 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/code-review-hardened/SKILL.md · 210 lines

How it starts

The opening of the file, as written. The whole thing — 210 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)

Read the full file on GitHub · 210 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 11d ago First seen · 210 lines · 95 tokens per session scan C e0a1e8cc7120

Subscribe to this mod's changes

code-review-excellence-hardened is a skill published in the GitHub repository faberlens/hardened-skills (23 stars, last pushed 4mo ago), licensed MIT. It adds 95 tokens to every session and 2,090 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it C with 2 findings (recursive force delete, makes network calls). It is 86% identical to code-review-excellence, differing in 13 lines, and is treated as a copy.