Agent skill

Gemini Review

by alinaqi in alinaqi/maggy

Google Gemini CLI code review with Gemini 2.5 Pro, 1M token context, CI/CD integration

MITAuto-check passedDevOps & Cloud

Install Gemini Review

skills CLI
$ npx skills add alinaqi/maggy --skill gemini-review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install alinaqi/maggy gemini-review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/alinaqi/maggy.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/gemini-review .claude/skills/gemini-review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
gemini-review
GitHub stars
707
Token cost
~2.7k tokens
SKILL.md length
466 words
Files
1
Skills in repo
71
Repo updated
First seen
Licence
MIT

At a glance

Google Gemini CLI code review with Gemini 2.5 Pro, 1M token context, CI/CD integration

  • Works in 3 steps: Go to GitHub Marketplace → Gemini Code… → Click "Install" and select repositories → PRs automatically get reviewed when opened
  • Tasks that involve CI/CD
  • SKILL.md covers Why Gemini for Code Review?, Installation, Authentication and Interactive Code Review, plus 7 more sections
  • Calls gemini, brew and nvm; reaches github.com and aistudio.google.com; needs GEMINI_API_KEY and GOOGLE_API_KEY

What it does

Gemini Review is an agent skill from alinaqi/maggy. Google Gemini CLI code review with Gemini 2.5 Pro, 1M token context, CI/CD integration

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud, covering CI/CD and Code review. It works with Google Gemini and GitHub. The repository describes itself as: What started as an opinionated Claude Code setup kit is now an autonomous AI engineering command center. The licence is MIT.

When your agent uses it

  • Tasks that involve CI/CD
  • Tasks that involve Code review

Example prompts

  • “/gemini-review”

Requirements

  • Node.js
  • A credential in GEMINI_API_KEY
  • A credential in GOOGLE_API_KEY

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Go to GitHub Marketplace → Gemini Code Assist
  2. Click "Install" and select repositories
  3. PRs automatically get reviewed when opened

What it can do on your machine

Read from SKILL.md and the folder at commit 72a456e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • gemini
    • brew
    • nvm
    • npm
    • node
    • npx
    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com
    • aistudio.google.com

    Also links to:

    • codeassist.google

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • GEMINI_API_KEY
    • GOOGLE_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Gemini Review loads about 2.7k tokens when it runs. Until then it costs about 25 tokens; SKILL.md has 466 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~25
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from alinaqi/maggy at commit 72a456e, republished under its MIT licence (© alinaqi). 466 words, ~2,652 tokens.

Download SKILL.mdSave it as .claude/skills/gemini-review/SKILL.md (or your agent's skills folder).
name
gemini-review
description
Google Gemini CLI code review with Gemini 2.5 Pro, 1M token context, CI/CD integration
when-to-use
When user requests Gemini-powered code review or needs large-context review
user-invocable
true
effort
medium

Google Gemini Code Review Skill

Use Google's Gemini CLI for code review with Gemini 2.5 Pro - featuring a massive 1M token context window that can analyze entire repositories at once.

Sources: Gemini CLI | Code Review Extension | Gemini Code Assist | GitHub Action


Why Gemini for Code Review?

FeatureBenefit
Gemini 2.5 ProState-of-the-art reasoning for code
1M token contextEntire repositories fit - no chunking needed
Free tier1,000 requests/day with Google account
Consistent outputClean formatting, predictable structure
GitHub nativeGemini Code Assist app for auto PR reviews
Benchmark Performance
BenchmarkScoreNotes
SWE-Bench Verified63.8%Agentic coding benchmark
Qodo PR Benchmark56.3%PR review quality
LiveCodeBench v570.4%Code generation
WebDev Arena#1Web development

Installation

Prerequisites
bash
# Check Node.js version (requires 20+)
node --version

# Install Node.js 20 if needed
# macOS
brew install node@20

# Or via nvm
nvm install 20
nvm use 20
Install Gemini CLI
bash
# Via npm (recommended)
npm install -g @google/gemini-cli

# Via Homebrew (macOS)
brew install gemini-cli

# Or run without installing
npx @google/gemini-cli

# Verify installation
gemini --version
Install Code Review Extension
bash
# Requires Gemini CLI v0.4.0+
gemini extensions install https://github.com/gemini-cli-extensions/code-review

# Verify extension
gemini extensions list

Authentication

Free tier: 1,000 requests/day, 60 requests/min

bash
# Run gemini and follow browser login
gemini

# Select: "Login with Google Account"
# Opens browser for OAuth

This gives you access to Gemini 2.5 Pro with the full 1M token context window.

Option 2: Gemini API Key

Free tier: 100 requests/day

bash
# Get API key from https://aistudio.google.com/apikey

# Set environment variable
export GEMINI_API_KEY="your-api-key"

# Or add to shell profile
echo 'export GEMINI_API_KEY="your-api-key"' >> ~/.zshrc

# Run Gemini
gemini
Option 3: Vertex AI (Enterprise)
bash
# For Google Cloud projects
export GOOGLE_API_KEY="your-api-key"
export GOOGLE_GENAI_USE_VERTEXAI=true
export GOOGLE_CLOUD_PROJECT="your-project-id"

gemini

Interactive Code Review

Using the Code Review Extension
bash
# Start Gemini CLI
gemini

# Run code review on current branch
/code-review

The extension analyzes:

  • Code changes on your current branch
  • Identifies quality issues
  • Suggests fixes
Manual Review Prompts
bash
# In interactive mode
gemini

# Then ask:
> Review the changes in this branch for bugs and security issues
> Analyze src/api/users.ts for potential vulnerabilities
> What are the code quality issues in the last 3 commits?

Headless Mode (Automation)

Basic Usage
bash
# Simple prompt execution
gemini -p "Review the code changes for bugs and security issues"

# With JSON output (for parsing)
gemini -p "Review the changes" --output-format json

# Stream JSON events (real-time)
gemini -p "Review and fix issues" --output-format stream-json

# Specify model
gemini -m gemini-2.5-pro -p "Deep code review of this PR"
Full CI/CD Example
bash
# Get diff and review
git diff origin/main...HEAD > diff.txt

gemini -p "Review this code diff for:
1. Security vulnerabilities
2. Performance issues
3. Code quality problems
4. Missing error handling

Diff:
$(cat diff.txt)
" --output-format json > review.json
Session Tracking
bash
# Track token usage and costs
gemini -p "Review changes" --session-summary metrics.json

# View metrics
cat metrics.json

GitHub Integration

Option 1: Gemini Code Assist App (Easiest)

Install from GitHub Marketplace:

  1. Go to GitHub Marketplace → Gemini Code Assist
  2. Click "Install" and select repositories
  3. PRs automatically get reviewed when opened

Commands in PR comments:

/gemini review     # Request code review
/gemini summary    # Get PR summary
/gemini help       # Show available commands

Quota:

  • Free: 33 PRs/day
  • Enterprise: 100+ PRs/day
Option 2: GitHub Action
yaml
# .github/workflows/gemini-review.yml
name: Gemini Code Review

on:
  pull_request:
    types: [opened, synchronize]

jobs:
  review:
    runs-on: ubuntu-latest
    permissions:
      contents: read
      pull-requests: write

    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0

      - name: Setup Node.js
        uses: actions/setup-node@v4
        with:
          node-version: '20'

      - name: Install Gemini CLI
        run: npm install -g @google/gemini-cli

      - name: Run Review
        env:
          GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
        run: |
          # Get diff
          git diff origin/${{ github.base_ref }}...HEAD > diff.txt

          # Run Gemini review
          gemini -p "Review this pull request diff for bugs, security issues, and code quality problems. Be specific about file names and line numbers.

          $(cat diff.txt)" > review.md

      - name: Post Review Comment
        uses: actions/github-script@v7
        with:
          script: |
            const fs = require('fs');
            const review = fs.readFileSync('review.md', 'utf8');
            github.rest.issues.createComment({
              owner: context.repo.owner,
              repo: context.repo.repo,
              issue_number: context.issue.number,
              body: `## 🤖 Gemini Code Review\n\n${review}`
            });
Option 3: Official GitHub Action
yaml
# .github/workflows/gemini-review.yml
name: Gemini Code Review

on:
  pull_request:
    types: [opened, synchronize]
  issue_comment:
    types: [created]

jobs:
  review:
    runs-on: ubuntu-latest
    permissions:
      contents: read
      pull-requests: write
      issues: write

    steps:
      - uses: actions/checkout@v4

      - name: Run Gemini CLI
        uses: google-github-actions/run-gemini-cli@v1
        with:
          gemini_api_key: ${{ secrets.GEMINI_API_KEY }}
          prompt: "Review this pull request for code quality, security issues, and potential bugs."

On-demand commands in comments:

@gemini-cli /review
@gemini-cli explain this code change
@gemini-cli write unit tests for this component

GitLab CI/CD

yaml
# .gitlab-ci.yml
gemini-review:
  image: node:20
  stage: review
  script:
    - npm install -g @google/gemini-cli
    - |
      gemini -p "Review the merge request changes for bugs, security issues, and code quality" > review.md
    - cat review.md
  artifacts:
    paths:
      - review.md
  rules:
    - if: $CI_PIPELINE_SOURCE == "merge_request_event"
  variables:
    GEMINI_API_KEY: $GEMINI_API_KEY

Configuration

Global Config
bash
# ~/.gemini/settings.json
{
  "model": "gemini-2.5-pro",
  "theme": "dark",
  "sandbox": true
}
Project Config (GEMINI.md)

Create a GEMINI.md file in your project root for project-specific context:

markdown
# Project Context for Gemini

## Tech Stack
- TypeScript with strict mode
- React 18 with hooks
- FastAPI backend
- PostgreSQL database

## Code Review Focus Areas
1. Type safety - ensure proper TypeScript types
2. React hooks rules - check for dependency array issues
3. SQL injection - verify parameterized queries
4. Authentication - check all endpoints have proper auth

## Conventions
- Use camelCase for variables
- Use PascalCase for components
- All API errors should use AppError class

CLI Quick Reference

bash
# Interactive
gemini                          # Start interactive mode
/code-review                    # Run code review extension

# Headless
gemini -p "prompt"              # Single prompt, exit
gemini -p "prompt" --output-format json   # JSON output
gemini -m gemini-2.5-flash -p "prompt"    # Use faster model

# Extensions
gemini extensions list          # List installed
gemini extensions install URL   # Install extension
gemini extensions update        # Update all

# Key Flags
--output-format json            # Structured output
--output-format stream-json     # Real-time events
--session-summary FILE          # Track metrics
-m MODEL                        # Select model

Show full SKILL.md (186 more words)Show less

Comparison: Claude vs Codex vs Gemini

AspectClaudeCodex CLIGemini CLI
SetupNone (built-in)npm + OpenAI APInpm + Google Account
ModelClaudeGPT-5.2-CodexGemini 2.5 Pro
ContextConversationFresh per review1M tokens (huge!)
Free TierN/ALimited1,000/day
Best ForQuick reviewsHigh accuracyLarge codebases
GitHub NativeNo@codexGemini Code Assist
When to Use Each
ScenarioRecommended Engine
Quick in-flow reviewClaude
Critical security reviewCodex (88% detection)
Large codebase (100+ files)Gemini (1M context)
Free automated reviewsGemini
Multiple perspectivesAll three (dual/triple engine)

Troubleshooting

IssueSolution
gemini: command not foundnpm install -g @google/gemini-cli
Node.js version errorUpgrade to Node.js 20+
Authentication failedRe-run gemini and login again
Extension not foundgemini extensions install https://github.com/gemini-cli-extensions/code-review
Rate limitedWait or upgrade to Vertex AI
Hangs in CIEnsure DEBUG env var is not set

Anti-Patterns

  • Skipping authentication setup - Always configure before CI/CD
  • Using API key in logs - Use secrets management
  • Ignoring context limits - Even 1M tokens has limits for huge monorepos
  • Running on every commit - Use on PRs only to save quota
  • Not setting project context - Add GEMINI.md for better reviews

© alinaqi, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/gemini-review of alinaqi/maggy.

Open the folder on GitHubat commit 72a456e

Compare with similar skills

Gemini Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Gemini Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Gemini Review this skillalinaqi/maggy707—~2.7kAutomated safety check: PassMIT
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Renovate Actions PR Reviewbacknotprop/plannotator9.3k—~640Automated safety check: PassApache-2.0
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Agentic GitHub Actions Auditortrailofbits/skills7.5k6 repos~5.4kAutomated safety check: NotesCC-BY-SA-4.0
GitHub Automationruvnet/ruflo74k1 repos~368Automated safety check: PassMIT

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Questions about Gemini Review

What does Gemini Review do?

Google Gemini CLI code review with Gemini 2.5 Pro, 1M token context, CI/CD integration. Gemini Review is an agent skill from alinaqi/maggy.

When should I use Gemini Review?

Gemini Review fits situations like: tasks that involve CI/CD; tasks that involve Code review.

How do I install Gemini Review in Claude Code?

Run `npx skills add alinaqi/maggy --skill gemini-review -a claude-code`. Or copy the skill folder (skills/gemini-review in alinaqi/maggy) into .claude/skills/gemini-review in your project. Claude Code loads it when a task matches its description.

How do I install Gemini Review in Codex?

Run `npx skills add alinaqi/maggy --skill gemini-review -a codex`. Or copy the skill folder (skills/gemini-review in alinaqi/maggy) into .agents/skills/gemini-review in your project. Codex loads it when a task matches its description.

Can I use Gemini Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add alinaqi/maggy --skill gemini-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gemini-review, .gemini/skills/gemini-review, .github/skills/gemini-review and .opencode/skills/gemini-review in your project.

What does Gemini Review need to run?

Going by SKILL.md and its folder, Gemini Review needs the command-line tools its instructions call (gemini, brew, nvm, npm, node and npx) and credentials named GEMINI_API_KEY and GOOGLE_API_KEY. Our summary lists: Node.js; A credential in GEMINI_API_KEY; A credential in GOOGLE_API_KEY.

Does Gemini Review access the network?

SKILL.md names 3 domains. In commands or code: github.com and aistudio.google.com; the agent is likely to contact these when it follows the instructions. As links in the text: codeassist.google. This is read from the text; nothing was executed.

Is Gemini Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Gemini Review use?

Gemini Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Gemini Review use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Gemini Review?

Skills that share tags, products or a category with Gemini Review: GitHub Actions Pat (bifrost-proxy/bifrost, 161 stars), Renovate Actions PR Review (backnotprop/plannotator, 9.3k stars), PR Babysitter (openinterpreter/openinterpreter, 69k stars) and Agentic GitHub Actions Auditor (trailofbits/skills, 7.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Gemini Review?

alinaqi (a GitHub user) maintains it in alinaqi/maggy, which has 707 GitHub stars. The repository holds 71 skills in this directory. The repository was last updated on September 24, 2026.

Source: alinaqi/maggy on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.