xiaohongshu
xiaohongshu
gemini-large-context
Use when analyzing large codebases, comparing multiple files, or researching project-wide patterns that exceed typical context limits - leverages Gemini CLI's 1M token context window for comprehensive analysis
Full skill instructions
Use Gemini CLI's massive context window (1M tokens) when analysis requires more context than available in current session. Ideal for codebase-wide searches, multi-file comparisons, and pattern discovery across large projects.
# Basic non-interactive analysis
gemini -p "@src/ Summarize architecture"
# Multiple directories
gemini -p "@src/ @tests/ Analyze test coverage"
# All project files
gemini --all-files -p "Project overview"
# Specific model (Pro = 1M context)
gemini -m gemini-2.5-pro -p "@src/ Deep analysis"
# Single file
gemini -p "@src/main.py Explain this file"
# Multiple files
gemini -p "@package.json @src/index.js Analyze dependencies"
# Entire directory (recursive)
gemini -p "@src/ Summarize architecture"
# Multiple directories
gemini -p "@src/ @tests/ Analyze test coverage"
# Current directory
gemini -p "@./ Project overview"
# Alternative: all files flag
gemini --all-files -p "Analyze project structure"
gemini -p "@src/
Describe:
1. Overall architecture pattern (MVC, Clean, etc.)
2. Key modules and their responsibilities
3. Data flow between components
4. External dependencies and integrations"
gemini -p "@src/ @lib/
Has [FEATURE] been implemented?
Show:
- Relevant files and functions
- Implementation approach
- Any gaps or incomplete areas"
gemini -p "@src/
Find all instances of [PATTERN]:
- File paths
- Implementation variations
- Consistency assessment"
gemini -p "@src/ @api/
Security review:
- Input validation practices
- Authentication/authorization patterns
- SQL injection protections
- XSS prevention measures"
gemini -p "@src/ @tests/
Assess test coverage:
- Which modules have tests?
- Which are missing tests?
- Test quality (unit vs integration)
- Edge cases covered"
When researching within task boundaries:
# 1. Include bead spec in context
gemini -p "@src/ @.beads/artifacts/bd-xxx/spec.md
Research implementations matching spec constraints"
# 2. Save findings to bead artifacts
# Write to .beads/artifacts/bd-xxx/research.md
In AGENTS.md or prompts, instruct agents:
When analysis requires more than 100KB of files:
1. Use Gemini CLI: `gemini -p "@[paths] [question]"`
2. Capture output
3. Synthesize findings in response
# Plain text (default)
gemini -p "query"
# JSON for parsing
gemini -p "query" --output-format json
# Streaming for long ops
gemini -p "query" --output-format stream-json
gemini -p "@src/ Describe architecture"gemini -p "@src/ Where is [X] implemented?"gemini -p "@src/ Find all [pattern] usages"gemini -p "@package.json @src/ Analyze dependency usage"gemini -p "@src/ Identify code smells"gemini -p "@src/ Plan migration from [A] to [B]"# Google login (free tier: 60 req/min, 1000/day)
gemini # Follow OAuth flow
# Or API key
export GEMINI_API_KEY="your-key"
For most analysis tasks, gemini-2.5-pro is the best choice—it has a 1M token context window and handles code, text, and image analysis exceptionally well. This is the default model.
Use gemini-2.5-flash when you need faster responses and don't need the full context window.
Important: If you're analyzing images or screenshots, use gemini-2.5-pro. Image generation models like imagen-3.0-generate-002 are for creating new images, not understanding existing ones.
# Gemini 2.5 Pro (1M context) - default, best for analysis
gemini -p "query"
# Gemini Flash (faster, smaller context)
gemini -m gemini-2.5-flash -p "query"
gemini -p "..." > analysis.md@file syntax: best in interactive modexiaohongshu
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