review

review is a skill for Claude Code from softspark/ai-toolkit. It costs 29 tokens per session (2,866 once invoked), scanned A, original, Apache-2.0.

A code review workflow that examines changed files for correctness, quality, security issues, merge conflicts, failed checks, and other warning signs.

In plain words
What is it for?
Use it to review a pull request, branch, or pending changes before merging.
Why use it?
It gathers problems across the change instead of stopping at the first failure, giving the author a fuller review.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: agent in frontmatter.

Part of the ai-toolkit plugin — 115 skills, 44 agents, 14 hooks shipped together

Good fit Use it to review a pull request, branch, or pending changes before merging.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/softspark/ai-toolkit/review
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 softspark/ai-toolkit --skill review
Clone the repo
git clone --depth 1 https://github.com/softspark/ai-toolkit

Made for: Claude Code.

Or install ai-toolkit, the plugin that ships this one along with the rest of its 115 skills, 44 agents, 14 hooks.

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 review

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/softspark/ai-toolkit/review"><img src="https://agentmods.dev/badge/skills/softspark/ai-toolkit/review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,866 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00029 $0.02866
Opus 5 $0.00015 $0.01433
Sonnet 5 $0.00006 $0.00573
Haiku 4.5 $0.00003 $0.00287

Measured 3d ago against content hash b090bac58347, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

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 3d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/diff-analyzer.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

app/skills/review/SKILL.md · 281 lines

How it starts

The opening of the file, as written. The whole thing — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Code Review

$ARGUMENTS

Reviews code changes for quality and issues.

Changed files context

  • Changes: !git diff --stat main...HEAD 2>/dev/null || git diff --cached --stat 2>/dev/null || echo "no changes detected"

Signal Collection (never stop at the first red)

Collect every failing signal up front, then review the diff in full anyway:

Signal How to read it
Merge conflict with base gh pr view --json mergeable,mergeStateStatus or git merge-tree
Failing CI checks gh pr checks or the platform equivalent
Lint / typecheck failure the project's own commands

Each failing signal becomes a blocker finding. None of them ends the run.

A review that aborts on the first red signal spends the whole cycle repeating what the tracker already displayed, while the finding that would have told the author something new never gets written. One invocation produces the most complete picture of the change that it can.

Automated Diff Analysis

Before starting manual review, run the diff analyzer script to get a structured risk assessment:

python3 ${CLAUDE_SKILL_DIR}/scripts/diff-analyzer.py [base_branch]
# Default base branch: main
# Example: python3 ${CLAUDE_SKILL_DIR}/scripts/diff-analyzer.py develop

The script outputs JSON with:

  • files: each changed file with additions, deletions, category (security/test/config/migration/infra/docs/logic), and risk level
  • risk_score: overall assessment (high/medium/low)
  • hotspots: top 5 files by additions
  • secrets_scan: potential secret leaks detected in added lines
  • test_coverage_estimate: whether test files accompany logic changes (good/partial/none)
  • parallel_review_recommended: boolean flag

If the script reports parallel_review_recommended: true, use the Parallel Review (Agent Teams) mode below.


Parallel Review (Agent Teams)

For significant PRs or large changesets, create a parallel review team:

Create an agent team to review [target]:
- Teammate 1 (security-auditor): "Review for security vulnerabilities, auth issues,
  injection risks, secret leaks. Report with severity ratings." Use Opus.
- Teammate 2 (performance-optimizer): "Check for N+1 queries, memory leaks,
  unnecessary allocations, caching opportunities. Report with impact ratings." Use Opus.
- Teammate 3 (test-engineer): "Validate test coverage, edge cases, mock quality,
  missing assertions. Report coverage gaps." Use Opus.
Each reviewer should report findings independently. Do NOT modify files.

Read the full file on GitHub · 281 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. 3d ago Changed · +5 lines b090bac58347
  2. 7d ago First seen · 276 lines · 29 tokens per session scan A 0c03d6356320

Subscribe to this mod's changes

review is a skill published in the GitHub repository softspark/ai-toolkit (170 stars, last pushed 2d ago), licensed Apache-2.0. It adds 29 tokens to every session and 2,866 once invoked, about $0.0001 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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