ai-review

ai-review is a skill for Claude Code from zawlinnnaing/ai-review-cli. It costs 64 tokens per session (1,226 once invoked), scanned A, original, no licence file.

A code-review helper for GitLab Merge Requests, which are proposed changes waiting to be checked before they are added to a project. It reads the change list, writes comments grouped by severity, and can post them to GitLab.

In plain words
What is it for?
Use it to analyse a GitLab Merge Request, identify issues, produce structured feedback, and optionally publish that feedback on the merge request.
Why use it?
It helps you review proposed code changes without manually inspecting every changed line and writing each comment yourself.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to analyse a GitLab Merge Request, identify issues, produce structured feedback, and optionally publish that feedback on the merge request.

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

Made for: Claude Code.

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 ai-review

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/zawlinnnaing/ai-review-cli/mr-review"><img src="https://agentmods.dev/badge/skills/zawlinnnaing/ai-review-cli/mr-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,226 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.
Origin unknown 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 $0.00064 $0.01226
Opus 5 $0.00032 $0.00613
Sonnet 5 $0.00013 $0.00245
Haiku 4.5 $0.00006 $0.00123

Measured 10d ago against content hash 2c30c4b6b9ec, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

ai-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 10d 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.

skills/mr-review/SKILL.md · 155 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. 10d ago First seen · 155 lines · 64 tokens per session scan A 2c30c4b6b9ec

Subscribe to this mod's changes

ai-review is a skill published in the GitHub repository zawlinnnaing/ai-review-cli (2 stars, last pushed 6mo ago), with no licence file. It adds 64 tokens to every session and 1,226 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 2026-08-31.

Related

Other skills, from other repositories

ralphctl-code-review-and-quality

Multi-phase code-quality skill — primary frame for the evaluator role in Execute, the architecture axis in Plan, and correctness/readability in Refine. Multi-axis code review with severity vocabulary. Use when you are the evaluator assessing a generator's output, and when reviewing any change before signalling…

lukas-grigis/ralphctl · 76 tokens

prereview

Review the current diff against this team's conventions and invariants before it ships. Invoke with /prereview before opening a PR, or run as a pre-push gate.

singhharsh1708/kitbash · 0 tokens

pr-review-response

Teaches agents to reply to PR review comment threads after fixing issues, making resolutions traceable.

bradygaster/squad · 22 tokens

fact-checking

Review and validate claims using counter-hypothesis testing. Use when verifying technical content, checking references, validating API endpoints, or performing quality assurance on deliverables.

bradygaster/squad · 36 tokens

umbra-trust-review

Verify AI-generated code before shipping. Run Umbra's Trust Score scan before committing or finishing any coding task, treat findings as blocking issues, and re-scan until clean. Use when finishing a task, before a commit, or when reviewing code written by an agent.

elberacasa/umbra · 60 tokens

copilot-setup-audit

Audit a repository's Copilot CLI customization setup and suggest improvements. Use when the user wants to review their Copilot configuration, find gaps, validate agents, skills, instructions, hooks, plugins, or MCP setup, or optimize their CLI customization setup.

trsdn/github-copilot-cli · 57 tokens