Gemini Codebase Onboard

Gemini Codebase Onboard Skill

Kanitsal Cerceve (Evidential Frame Activation)

Kaynak dogrulama modu etkin.

Purpose

Use Gemini CLI's massive 1 million token context window to analyze entire codebases in a single pass. Generate architecture maps, pattern documentation, and onboarding guides.

When to Use This Skill

• Onboarding to a new codebase
• Understanding full system architecture
• Mapping dependencies across all files
• Finding patterns and anti-patterns
• Migration planning (need full context)
• Security audits requiring full codebase awareness
• Refactoring impact analysis

When NOT to Use This Skill

• Working with single file (use Claude directly)
• Complex reasoning tasks (Claude is better)
• Writing new features (Gemini gets stuck in loops)
• Iterative refinement (use Codex)

Workflow

Phase 1: Megacontext Load

# Load entire codebase
./scripts/multi-model/gemini-yolo.sh "Analyze architecture" task-id megacontext

# Via delegate.sh
./scripts/multi-model/delegate.sh gemini "Map full architecture" --all-files

# Direct Gemini
bash -lc "gemini --all-files 'Analyze entire codebase and document architecture'"

Phase 2: Analysis Queries

Common analysis patterns:

• Architecture overview
• Dependency mapping
• Pattern identification
• Security scanning
• Migration assessment

Phase 3: Documentation Generation

1. Gemini produces findings
2. Claude synthesizes into documentation
3. Store in project for future reference

Context Window Specs

Success Criteria

• Full architecture understood
• Key patterns documented
• Dependencies mapped
• Onboarding guide created

Example Usage

Example 1: New Project Onboarding

User: "I just joined this team, help me understand the codebase"

Gemini Analysis:
bash -lc "gemini --all-files 'Create comprehensive onboarding guide including:
1. High-level architecture
2. Key components and their responsibilities
3. Data flow between components
4. Configuration and environment setup
5. Common patterns used'"

Output:
- Architecture: Microservices with API gateway
- Key Services: auth, users, orders, notifications
- Patterns: Repository pattern, Event-driven
- Setup: Docker Compose with 4 services

Example 2: Refactoring Impact Analysis

User: "What would break if we rename User to Account?"

Gemini Analysis:
bash -lc "gemini --all-files 'Identify all files affected by renaming User to Account'"

Output:
- 47 files with direct User references
- 12 database migrations needed
- 8 API endpoints returning User data
- 15 frontend components
- 3 background jobs

Example 3: Security Audit

User: "Find all places handling sensitive data"

Gemini Analysis:
bash -lc "gemini --all-files 'Security audit: Find all PII handling, auth patterns, and potential vulnerabilities'"

Output:
- PII fields: 12 database columns
- Auth: JWT with refresh tokens
- Concerns: 3 endpoints missing auth middleware
- Logging: 2 instances of sensitive data in logs

Query Patterns

Architecture Documentation

gemini --all-files "Document the full system architecture with component interactions"

Dependency Mapping

gemini --all-files "Create a dependency graph showing how all modules relate"

Pattern Analysis

gemini --all-files "Identify all design patterns used and assess consistency"

API Documentation

gemini --all-files "Document all API endpoints with their request/response formats"

Integration with Meta-Loop

META-LOOP PROPOSE PHASE:
    |
    +---> gemini-codebase-onboard
    |         |
    |         +---> Gemini: Load entire codebase (--all-files)
    |         +---> Gemini: Analyze architecture
    |         +---> Gemini: Identify impact areas
    |
    +---> Claude: Synthesize into plan
    |
    +---> Continue to IMPLEMENT phase

Memory Integration

Results stored at:

• Key: multi-model/gemini/onboard/{project}/{task_id}
• Tags: WHO=gemini-megacontext, WHY=codebase-analysis
• Contains: Architecture map, patterns, dependencies

Limitations

Based on real developer feedback:

• May generate errors in analysis (missing XML tags)
• Can get stuck in loops trying to fix mistakes
• Switches to Flash model after 5 minutes (Flash is weaker)
• Slower than Claude for complex reasoning
• Not great for implementation tasks

Strengths

• Breadth of analysis is excellent
• Can summarize entire folders effectively
• Great for onboarding and auditing
• Powerful for architectural understanding

Related Skills

• multi-model-discovery: Find existing solutions
• gemini-research: Current info research
• codex-iterative-fix: After understanding, for implementation
• documentation: Generate docs from analysis

Verification Checklist

• Entire codebase loaded
• Architecture documented
• Key patterns identified
• Dependencies mapped
• Onboarding guide created
• Memory-MCP updated