review

review is a command for coding agents from primeline-ai/evolving-lite. It costs 16 tokens per session (336 once invoked), scanned A, original, MIT.

A structured code review command that examines changed code for correctness, security, quality, and performance. It labels findings by severity and gives a review decision.

In plain words
What is it for?
Use it on unstaged changes, a specific file, or all changes since the last commit.
Why use it?
It turns a broad code check into a consistent report, making defects, security risks, and maintainability problems easier to find and discuss.

Command

Part of the evolving-lite plugin — 2 skills, 16 commands, 6 agents, 6 hooks shipped together

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 commands/primeline-ai/evolving-lite/review
Clone the repo
git clone --depth 1 https://github.com/primeline-ai/evolving-lite

Or install evolving-lite, the plugin that ships this one along with the rest of its 2 skills, 16 commands, 6 agents, 6 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/commands/primeline-ai/evolving-lite/review.svg)](https://agentmods.dev/commands/primeline-ai/evolving-lite/review)
Your own site
<a href="https://agentmods.dev/commands/primeline-ai/evolving-lite/review"><img src="https://agentmods.dev/badge/commands/primeline-ai/evolving-lite/review.svg" alt="Measured on agentmods" height="20"></a>
Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 336 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 $0.00016 $0.00336
Opus 5 $0.00008 $0.00168
Sonnet 5 $0.00003 $0.00067
Haiku 4.5 $0.00002 $0.00034

Measured 3d ago against content hash eb7945aa2e23, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, 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.

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.

commands/review.md · 58 lines

What it actually says

Perform a structured code review focused on correctness, security, and quality.

Input: $ARGUMENTS

If empty: Review recent unstaged changes (git diff) If file path: Review that specific file If "recent": Review all changes since last commit

Review Checklist

1. Correctness

  • Does the code do what it claims?
  • Are edge cases handled?
  • Are error paths tested?

2. Security (OWASP Top 10)

  • Input validation at boundaries
  • No hardcoded secrets
  • SQL/command injection prevention
  • XSS prevention (if web)
  • Authentication/authorization checks

3. Quality

  • Is the code readable without comments?
  • Are names descriptive?
  • Is there unnecessary complexity?
  • Any code duplication that should be abstracted?

4. Performance

  • Any O(n^2) or worse in hot paths?
  • Unnecessary file I/O or network calls?
  • Missing caching opportunities?

Output

## Code Review: {file or scope}

### Issues Found

| # | Severity | File:Line | Issue | Suggestion |
|---|----------|-----------|-------|-----------|
| 1 | HIGH | path:42 | ... | ... |

### Summary
- Critical: {count}
- High: {count}
- Medium: {count}
- Low: {count}

Verdict: {APPROVE / REQUEST_CHANGES / NEEDS_DISCUSSION}
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 First seen · 58 lines · 16 tokens per session scan A eb7945aa2e23

Subscribe to this mod's changes

review is a command published in the GitHub repository primeline-ai/evolving-lite (48 stars, last pushed 17d ago), licensed MIT. It adds 16 tokens to every session and 336 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 2026-08-30.