| name | Gemini CLI |
| description | Use Google Gemini CLI directly from Claude Code for second opinions, architectural advice, debugging help, code reviews, and security audits. Leverage Gemini's 1M+ context window for comprehensive code analysis using the official gemini command-line tool. Use when: Need second opinion on architectural decisions, stuck debugging after 2+ attempts, writing security-sensitive code (auth, payments, data handling), planning large refactors (5+ files), approaching 70%+ context capacity, unfamiliar with technology stack, want to compare Flash vs Pro model recommendations, need comprehensive codebase analysis, or consulting Gemini for peer review on critical code changes. Keywords: gemini-cli, google gemini, gemini command line, second opinion, model comparison, gemini-2.5-flash, gemini-2.5-pro, architectural decisions, debugging assistant, code review gemini, security audit gemini, 1M context window, AI pair programming, gemini consultation, flash vs pro, AI-to-AI prompting, peer review, codebase analysis, gemini CLI tool, shell gemini, command line AI assistant, gemini architecture advice, gemini debug help, gemini security scan, gemini code compare |
| license | MIT |
| metadata | [object Object] |
Gemini CLI
Leverage Gemini's 1M+ context window as your AI pair programmer within Claude Code workflows.
This skill teaches Claude Code how to use the official Google Gemini CLI (gemini command) to get second opinions, architectural advice, debugging help, and comprehensive code reviews. Based on production testing with the official CLI tool.
Table of Contents
- Quick Start
- When to Use Gemini Consultation
- Installation
- Using Gemini CLI
- Model Selection: Flash vs Pro
- Proactive Consultation Patterns
- AI-to-AI Prompting Best Practices
- Common Use Cases
- Integration Examples
- Troubleshooting & Known Issues
Quick Start
Prerequisites:
- Gemini CLI installed (
npm install -g @google/gemini-cli) - Authenticated with Google account (run
geminionce to authenticate)
Basic Usage Patterns:
# Quick question (non-interactive with -p flag)
gemini -p "Should I use D1 or KV for session storage?"
# Code review with file context (using --all-files)
gemini --all-files -p "Review this auth implementation for security issues"
# Architecture advice using Pro model
gemini -m gemini-2.5-pro -p "Best way to handle WebSockets in Cloudflare Workers?"
# Pipe file content for review
cat src/auth.ts | gemini -p "Review this authentication code for security vulnerabilities"
# Interactive mode for follow-up questions
gemini -i "Help me debug this authentication error"
When to Use Gemini Consultation
ALWAYS Consult (Critical Scenarios)
Claude Code should automatically invoke Gemini in these situations:
Major Architectural Decisions
- Example: "Should I use D1 or KV for session storage?"
- Example: "Durable Objects vs Workflows for long-running tasks?"
- Why: Gemini provides complementary perspective, may prioritize different concerns
- Pattern:
gemini -m gemini-2.5-pro -p "[architectural question]"
Security-Sensitive Code Changes
- Authentication systems
- Payment processing
- Data handling (PII, sensitive data)
- API key/secret management
- Why: Gemini 2.5 Pro excels at security audits
- Pattern:
cat [security-file] | gemini -m gemini-2.5-pro -p "Security audit this code"
Large Refactors
- Affecting 5+ files
- Core architecture changes
- Database schema migrations
- Why: Fresh perspective prevents tunnel vision
- Pattern:
gemini --all-files -m gemini-2.5-pro -p "Review this refactoring plan"
Stuck Debugging (2+ Failed Attempts)
- Error persists after 2 debugging attempts
- Stack trace unclear
- Intermittent bugs
- Why: Different reasoning approach may spot root cause
- Pattern:
gemini -p "Help debug: [error message]" < error.log
Context Window Pressure (70%+ Full)
- Approaching token limit
- Need to offload analysis to Gemini
- Why: Gemini's 1M context can handle large code files
- Pattern:
cat large-file.ts | gemini -p "Analyze this code structure"
OPTIONALLY Consult
Unfamiliar Technology
- Using library/framework for first time
- Experimenting with new patterns
- Why: Gemini may have more recent training data
- Pattern:
gemini -p "Best practices for [new technology]"
Code Reviews
- Before committing major changes
- Pull request preparation
- Why: Catches edge cases and improvements
- Pattern:
git diff | gemini -p "Review these changes"
Installation
1. Install Gemini CLI
npm install -g @google/gemini-cli
2. Authenticate
gemini
Follow the authentication prompts to link your Google account.
3. Verify Installation
gemini --version
Should show version 0.13.0 or higher.
4. Test Connection
gemini -p "What is 2+2?"
Using Gemini CLI
Core Command Patterns
Non-Interactive Mode (-p flag)
Best for Claude Code integration:
# Direct question
gemini -p "Your question here"
# With model selection
gemini -m gemini-2.5-flash -p "Quick debugging question"
gemini -m gemini-2.5-pro -p "Complex architectural decision"
# With file context via pipe
cat src/auth.ts | gemini -p "Review this code"
# With all files in current directory
gemini --all-files -p "Analyze project structure"
# With stdin input
echo "Error: Cannot connect to database" | gemini -p "Help debug this error"
Interactive Mode (-i flag)
For follow-up conversations:
# Start interactive session with initial prompt
gemini -i "Let's discuss the architecture"
# Interactive with model selection
gemini -m gemini-2.5-pro -i "Help me design a database schema"
YOLO Mode (-y flag)
Auto-accepts all actions (use with caution):
# Dangerous: Auto-executes suggested commands
gemini -y -p "Fix all linting errors"
⚠️ Warning: YOLO mode can execute commands without confirmation. Only use in trusted environments.
Model Selection: Flash vs Pro
gemini-2.5-flash (Default)
Characteristics:
- Fast response time: ~5-25 seconds
- Good quality for most tasks
- Lower cost
- Safe for general questions
Use For:
- Code reviews
- Debugging
- General questions
- Quick consultations
- When speed matters
Example:
gemini -m gemini-2.5-flash -p "Review this function for performance issues"
gemini-2.5-pro
Characteristics:
- Response time: ~15-30 seconds
- Excellent quality, thorough analysis
- Higher cost
- Best for critical decisions
Use For:
- Architecture decisions (critical)
- Security audits (thorough)
- Complex reasoning tasks
- Major refactoring plans
- When accuracy > speed
Example:
gemini -m gemini-2.5-pro -p "Security audit this authentication system"
How to Choose
Quick question? → Flash
Security/architecture? → Pro
Debugging? → Flash (try Pro if stuck)
Code review? → Flash
Refactoring 5+ files? → Pro
Proactive Consultation Patterns
Pattern 1: Architecture Decision
Trigger: User asks about technology choice Claude Action: Automatically consult Gemini for second opinion
# Claude runs:
gemini -m gemini-2.5-pro -p "Compare D1 vs KV for session storage in Cloudflare Workers. Consider: read/write patterns, cost, performance, complexity."
# Then synthesizes both perspectives
Pattern 2: Security Review
Trigger: Working on auth/payment/sensitive code Claude Action: Request Gemini security audit
# Claude runs:
cat src/auth/verify-token.ts | gemini -m gemini-2.5-pro -p "Security audit this authentication code. Check for: token validation, timing attacks, injection vulnerabilities, error handling."
Pattern 3: Debugging Assistance
Trigger: Error persists after 2 attempts Claude Action: Get Gemini's perspective
# Claude runs:
echo "[error message and stack trace]" | gemini -p "Help debug this error. What's the likely root cause?"
Pattern 4: Code Review
Trigger: Major changes ready to commit Claude Action: Request comprehensive review
# Claude runs:
git diff HEAD | gemini --all-files -p "Review these changes for: correctness, edge cases, performance, security, best practices."
AI-to-AI Prompting Best Practices
How Claude Should Format Prompts to Gemini
✅ GOOD: Context-Rich, Specific
gemini -m gemini-2.5-pro -p "I'm building a Cloudflare Worker with user authentication. Should I use D1 or KV for storing session data? Consider: 1) Session reads on every request, 2) TTL-based expiration, 3) Cost under 10M requests/month, 4) Deployment complexity."
❌ BAD: Vague, No Context
gemini -p "D1 or KV?"
Prompt Structure Template
[Context: What you're building]
[Question]
[Considerations: Key factors (numbered)]
Example: Architecture Decision
gemini -m gemini-2.5-pro -p "
Context: Building a real-time collaborative editing app on Cloudflare Workers.
Question: Should I use Durable Objects or Workflows for managing document state?
Considerations:
1. Need to handle WebSocket connections (100+ simultaneous users per document)
2. Document state must be consistent across all clients
3. Need to persist changes every 5 seconds
4. Budget: <\$100/month at 1000 documents
5. Simple deployment preferred
"
Common Use Cases
1. Technology Selection
# Compare two technologies
gemini -m gemini-2.5-pro -p "Compare Drizzle ORM vs raw SQL for Cloudflare D1. Consider: type safety, performance, query complexity, bundle size."
2. Security Audit
# Audit authentication code
cat src/middleware/auth.ts | gemini -m gemini-2.5-pro -p "
Security audit this authentication middleware. Check for:
1. Token validation vulnerabilities
2. Timing attack risks
3. Error handling leaks
4. CSRF protection
5. Rate limiting
"
3. Debugging Root Cause
# Analyze error logs
tail -100 error.log | gemini -p "
These errors started appearing after deploying auth changes. What's the likely root cause?
Context:
- Added JWT validation middleware
- Using @cloudflare/workers-jwt
- Errors only on /api/* routes
"
4. Code Review
# Review pull request changes
git diff main...feature-branch | gemini --all-files -p "
Review this pull request. Focus on:
1. Breaking changes
2. Edge cases not handled
3. Performance implications
4. Security concerns
"
5. Refactoring Plan
# Plan large refactor
gemini --all-files -m gemini-2.5-pro -p "
I want to refactor this Express app to Cloudflare Workers with Hono. Analyze the codebase and suggest:
1. Migration order (which routes first)
2. Potential blockers (middleware that won't work)
3. Testing strategy
4. Deployment plan
"
6. Performance Optimization
# Analyze performance
cat src/api/heavy-endpoint.ts | gemini -p "
This endpoint is slow (500ms+ response time). Identify performance bottlenecks and suggest optimizations.
Context:
- Cloudflare Worker
- Fetches data from 3 external APIs
- Processes 1000+ items
"
Integration Examples
Example 1: Claude Consulting Gemini Automatically
Scenario: User asks architectural question
User: "Should I use D1 or KV for storing user sessions?"
Claude (internal): This is an architectural decision. Consult Gemini for second opinion.
[Runs: gemini -m gemini-2.5-pro -p "Compare D1 vs KV for user session storage in Cloudflare Workers..."]
Claude (to user): "I've consulted Gemini for a second opinion. Here's what we both think:
My perspective: [Claude's analysis]
Gemini's perspective: [Gemini's analysis]
Key differences: [synthesis]
Recommendation: [combined recommendation]"
Example 2: Security Review Before Commit
User: "Ready to commit these auth changes"
Claude (internal): Security-sensitive code. Request Gemini audit.
[Runs: cat src/auth/*.ts | gemini -m gemini-2.5-pro -p "Security audit..."]
Claude (to user): "I've reviewed the code and consulted Gemini for security concerns:
Gemini identified: [security issues]
Additional checks I recommend: [Claude's additions]
Safe to commit after addressing: [list]"
Example 3: Debugging Assistance
User: "Still getting this error after trying your suggestions: [error]"
Claude (internal): Two failed attempts. Consult Gemini for fresh perspective.
[Runs: echo "[error details]" | gemini -p "Help debug..."]
Claude (to user): "Let me get a second opinion from Gemini...
Gemini suggests: [Gemini's diagnosis]
This makes sense because: [Claude's analysis]
Let's try: [combined solution]"
Troubleshooting & Known Issues
Issue 1: Not Authenticated
Error: Error: Not authenticated
Solution:
gemini
# Follow authentication prompts
Issue 2: Model Not Found
Error: Error: Model not found: gemini-2.5-flash-lite
Cause: Model deprecated or renamed
Solution:
# Use stable models
gemini -m gemini-2.5-flash -p "Your question"
gemini -m gemini-2.5-pro -p "Your question"
Issue 3: Rate Limit
Error: Error: Rate limit exceeded
Solution: Wait 1-5 minutes, then retry
Prevention: Space out requests
Issue 4: Large File Context
Error: File too large for context
Solution: Use --all-files carefully or pipe specific sections
# Instead of:
gemini --all-files -p "Review everything"
# Do:
cat src/specific-file.ts | gemini -p "Review this file"
Issue 5: Command Hangs
Cause: Interactive mode when expecting non-interactive
Solution: Always use -p flag for non-interactive commands
# ✅ Correct
gemini -p "Question"
# ❌ Wrong (will hang waiting for input)
gemini "Question"
Production Best Practices
1. Always Use -p for Automation
# ✅ Good for scripts
gemini -p "Question"
# ❌ Bad for scripts (interactive)
gemini
2. Select Model Based on Criticality
# Architecture/security → Pro
gemini -m gemini-2.5-pro -p "[critical question]"
# Debugging/review → Flash
gemini -m gemini-2.5-flash -p "[general question]"
3. Provide Context in Prompts
# ✅ Good
gemini -p "Context: Building Cloudflare Worker. Question: Best auth pattern? Considerations: 1) Stateless, 2) JWT, 3) <100ms overhead"
# ❌ Bad
gemini -p "Best auth?"
4. Pipe File Content for Reviews
# ✅ Good
cat src/auth.ts | gemini -p "Review for security"
# ❌ Inefficient
gemini -p "Review src/auth.ts" # Gemini has to read file separately
5. Handle Errors Gracefully
# Add error handling
if output=$(gemini -p "Question" 2>&1); then
echo "Gemini says: $output"
else
echo "Gemini consultation failed, proceeding with Claude's recommendation"
fi
6. Synthesize, Don't Just Forward
❌ BAD: Just paste Gemini's response
User: "Should I use D1?"
Claude: [runs gemini] "Gemini says: [paste]"
✅ GOOD: Synthesize both perspectives
User: "Should I use D1?"
Claude: [runs gemini]
"I've consulted Gemini for a second opinion:
My analysis: [Claude's perspective]
Gemini's analysis: [Gemini's perspective]
Key differences: [synthesis]
Recommendation: [unified answer]"
Version History
2.0.0 (2025-11-13):
- Complete rewrite for official Gemini CLI (removed gemini-coach wrapper)
- Direct CLI integration patterns
- Simplified to core use cases
- Updated command examples for
geminiCLI v0.13.0+
1.0.0 (2025-11-08):
- Initial release with gemini-coach wrapper
- Production testing and experimentation
- 8+ documented errors prevented
Related Skills
- google-gemini-api - Gemini API integration via SDK
- google-gemini-embeddings - Gemini embeddings for RAG
- google-gemini-file-search - Managed RAG with Gemini
License
MIT - See LICENSE
Support
- Issues: https://github.com/jezweb/claude-skills/issues
- Email: jeremy@jezweb.net
- Official Gemini CLI: https://github.com/google-gemini/gemini-cli