When analyzing large codebases or multiple files that might exceed context limits, use the Gemini CLI with its massive
context window. Use gemini -p
to leverage Google Gemini's large context capacity.
Use the @
syntax to include files and directories in your Gemini prompts. The paths should be relative to WHERE you run the
gemini command:
Single file analysis:
gemini -p "@src/main.py Explain this file's purpose and structure"
Multiple files:
gemini -p "@package.json @src/index.js Analyze the dependencies used in the code"
Entire directory:
gemini -p "@src/ Summarize the architecture of this codebase"
Multiple directories:
gemini -p "@src/ @tests/ Analyze test coverage for the source code"
Current directory and subdirectories:
gemini -p "@./ Give me an overview of this entire project"
#
Or use --all_files flag:
gemini --all_files -p "Analyze the project structure and dependencies"
Implementation Verification Examples
Check if a feature is implemented:
gemini -p "@src/ @lib/ Has dark mode been implemented in this codebase? Show me the relevant files and functions"
Verify authentication implementation:
gemini -p "@src/ @middleware/ Is JWT authentication implemented? List all auth-related endpoints and middleware"
Check for specific patterns:
gemini -p "@src/ Are there any React hooks that handle WebSocket connections? List them with file paths"
Verify error handling:
gemini -p "@src/ @api/ Is proper error handling implemented for all API endpoints? Show examples of try-catch blocks"
Check for rate limiting:
gemini -p "@backend/ @middleware/ Is rate limiting implemented for the API? Show the implementation details"
Verify caching strategy:
gemini -p "@src/ @lib/ @services/ Is Redis caching implemented? List all cache-related functions and their usage"
Check for specific security measures:
gemini -p "@src/ @api/ Are SQL injection protections implemented? Show how user inputs are sanitized"
Verify test coverage for features:
gemini -p "@src/payment/ @tests/ Is the payment processing module fully tested? List all test cases"
When to Use Gemini CLI
Use gemini -p when:
- Analyzing entire codebases or large directories
- Comparing multiple large files
- Need to understand project-wide patterns or architecture
- Current context window is insufficient for the task
- Working with files totaling more than 100KB
- Verifying if specific features, patterns, or security measures are implemented
- Checking for the presence of certain coding patterns across the entire codebase
Important Notes
- Paths in @ syntax are relative to your current working directory when invoking gemini
- The CLI will include file contents directly in the context
- No need for --yolo flag for read-only analysis
- Gemini's context window can handle entire codebases that would overflow Claude's context
- When checking implementations, be specific about what you're looking for to get accurate results # Using Gemini CLI for Large Codebase Analysis
When analyzing large codebases or multiple files that might exceed context limits, use the Gemini CLI with its massive
context window. Use `gemini -p` to leverage Google Gemini's large context capacity.
## File and Directory Inclusion Syntax
Use the `@` syntax to include files and directories in your Gemini prompts. The paths should be relative to WHERE you run the
gemini command:
### Examples:
**Single file analysis:**
```bash
gemini -p "@src/main.py Explain this file's purpose and structure"
Multiple files:
gemini -p "@package.json @src/index.js Analyze the dependencies used in the code"
Entire directory:
gemini -p "@src/ Summarize the architecture of this codebase"
Multiple directories:
gemini -p "@src/ @tests/ Analyze test coverage for the source code"
Current directory and subdirectories:
gemini -p "@./ Give me an overview of this entire project"
# Or use --all_files flag:
gemini --all_files -p "Analyze the project structure and dependencies"
Implementation Verification Examples
Check if a feature is implemented:
gemini -p "@src/ @lib/ Has dark mode been implemented in this codebase? Show me the relevant files and functions"
Verify authentication implementation:
gemini -p "@src/ @middleware/ Is JWT authentication implemented? List all auth-related endpoints and middleware"
Check for specific patterns:
gemini -p "@src/ Are there any React hooks that handle WebSocket connections? List them with file paths"
Verify error handling:
gemini -p "@src/ @api/ Is proper error handling implemented for all API endpoints? Show examples of try-catch blocks"
Check for rate limiting:
gemini -p "@backend/ @middleware/ Is rate limiting implemented for the API? Show the implementation details"
Verify caching strategy:
gemini -p "@src/ @lib/ @services/ Is Redis caching implemented? List all cache-related functions and their usage"
Check for specific security measures:
gemini -p "@src/ @api/ Are SQL injection protections implemented? Show how user inputs are sanitized"
Verify test coverage for features:
gemini -p "@src/payment/ @tests/ Is the payment processing module fully tested? List all test cases"
When to Use Gemini CLI
Use gemini -p when:
- Analyzing entire codebases or large directories
- Comparing multiple large files
- Need to understand project-wide patterns or architecture
- Current context window is insufficient for the task
- Working with files totaling more than 100KB
- Verifying if specific features, patterns, or security measures are implemented
- Checking for the presence of certain coding patterns across the entire codebase
Important Notes
- Paths in @ syntax are relative to your current working directory when invoking gemini
- The CLI will include file contents directly in the context
- No need for --yolo flag for read-only analysis
- Gemini's context window can handle entire codebases that would overflow Claude's context
- When checking implementations, be specific about what you're looking for to get accurate results
Claude.md
라는 것을 생성하면 된다.