code-review

code-review is a skill for Claude Code, Codex from tahirraufkeeyu/software-development-agent-stack--sdas. It costs 54 tokens per session (1,705 once invoked), scanned A, original, MIT.

A structured review of code changes such as a diff, pull request, patch, or staged files.

In plain words
What is it for?
Use it to review a pull request or patch, check staged changes, or investigate concerns such as injection, cross-site scripting, authorization bugs, race conditions, or inefficient database access.
Why use it?
It helps find security, correctness, performance, style, and testing problems before changes are merged, with each issue tied to a file and line.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

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/tahirraufkeeyu/software-development-agent-stack--sdas/code-review
Any agent
npx skills add tahirraufkeeyu/software-development-agent-stack--sdas --skill code-review
Clone the repo
git clone --depth 1 https://github.com/tahirraufkeeyu/software-development-agent-stack--sdas

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/tahirraufkeeyu/software-development-agent-stack--sdas/code-review.svg)](https://agentmods.dev/skills/tahirraufkeeyu/software-development-agent-stack--sdas/code-review)
Your own site
<a href="https://agentmods.dev/skills/tahirraufkeeyu/software-development-agent-stack--sdas/code-review"><img src="https://agentmods.dev/badge/skills/tahirraufkeeyu/software-development-agent-stack--sdas/code-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,705 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 $0.00054 $0.01705
Opus 5 $0.00027 $0.00852
Sonnet 5 $0.00011 $0.00341
Haiku 4.5 $0.00005 $0.00170

Measured 5d ago against content hash 4e853324d093, 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 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 5d 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.

departments/developers/skills/code-review/SKILL.md · 121 lines

How it starts

The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.

When to use

  • User pastes a diff, patch, or PR URL and asks "review this", "is this safe to merge", "look for issues".
  • User asks to self-review staged changes before committing (git diff --staged).
  • User wants a security- or performance-focused pass on a specific file.
  • User mentions N+1, SQL injection, XSS, authorization, race conditions, or unbounded loops.

Do not use this skill for architectural review of a design doc (use api-design or an ADR skill) or for large multi-PR audits (run this skill per PR).

Inputs

  • A unified diff, a PR URL (resolved via the GitHub MCP), or a list of files to review.
  • Optional: the language/framework (inferred if omitted), the repo's style guide or linter config, and the PR description so intent can be compared against implementation.

Outputs

A Markdown review with three sections:

  1. Summary: 2-4 sentence assessment plus an overall verdict (approve, approve-with-nits, request-changes, block).
  2. Findings table: one row per issue with columns Severity | File:Line | Category | Issue | Suggested fix.
  3. Inline suggestions: for each high or blocker finding, a fenced code block showing the exact replacement.

Severity ladder: blocker (must fix, ship-stopping), high (fix before merge), medium (fix soon, track in issue), low (nit, optional), info (observation, no action).

Tool dependencies

  • Read, Grep, Glob for local files.
  • GitHub MCP (get_pull_request, get_pull_request_diff, get_pull_request_files) when reviewing a PR by URL.
  • Optional: language-specific linters (eslint, ruff, golangci-lint, clippy) — run them if available and cite their output.

Procedure

  1. Fetch the diff. If given a PR URL, use the GitHub MCP to pull the title, body, and unified diff. If given a branch, run git diff <base>...HEAD. Always obtain the full diff, not a summary — reviews over summarised diffs miss subtle bugs.
  2. Read the PR description and identify the stated intent. Note any mismatch between intent and the actual changes; call that out in the summary.
  3. Enumerate touched files and, for each non-trivial file, read at least 50 lines above and below the hunk to understand context. Never review a hunk in isolation.
  4. Walk the checklist in references/review-checklist.md in order: security, correctness, performance, maintainability, testing, observability. Skipping a category is not acceptable; if a category does not apply, state so explicitly in the summary.
  5. For each issue, assign a severity from the ladder above and write the finding using this template: <what is wrong> -> <why it matters> -> <concrete fix>. Always cite path/to/file.ext:Lstart-Lend.
  6. Cross-check every flagged issue against references/common-antipatterns.md to ensure the label is precise (e.g. distinguish feature envy from law-of-demeter violations).
  7. If the diff touches tests, confirm the tests actually exercise the new behaviour. A passing test that never asserts the new code path is a high finding.
  8. If any finding is blocker or high, set the verdict to request-changes or block. Never mark a PR approve while high issues remain.
  9. Emit the review in the output format above. Keep each finding under four lines; push rationale into links to the references.

Read the full file on GitHub · 121 lines

Files

What ships with it

2 files 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. 5d ago First seen · 121 lines · 54 tokens per session scan A 4e853324d093

Subscribe to this mod's changes

code-review is a skill published in the GitHub repository tahirraufkeeyu/software-development-agent-stack--sdas (18 stars, last pushed 4mo ago), licensed MIT. It adds 54 tokens to every session and 1,705 once invoked, about $0.0003 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.

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