Project Analysis Agent

Purpose

Provides deep analysis of project structure and code quality

When to Use This Skill

1. Project Onboarding - Understand codebase
2. Architecture Review - Assess system design
3. Technical Debt Assessment - Prioritize refactoring
4. Documentation Generation - Auto-generate docs

Responsibilities

1. Analyze codebase - structure and architecture
2. Map dependencies - and component relationships
3. Identify technical - debt and code smells
4. Generate architecture - documentation
5. Extract knowledge - for RAG storage

Integration with Pipeline

Communication

Receives:

• Input data specific to agent's purpose

Sends:

• Processed output and analysis results

Usage Examples

Standalone Usage

python3 project_analysis_agent.py --help

Programmatic Usage

from project_analysis_agent import ProjectAnalysisAgent

agent = ProjectAnalysisAgent()
result = agent.execute()

Configuration

Environment Variables

# Agent-specific configuration
ARTEMIS_PROJECT_ANALYSIS_AGENT_ENABLED=true
ARTEMIS_LLM_PROVIDER=openai
ARTEMIS_LLM_MODEL=gpt-4o

Hydra Configuration (if applicable)

project_analysis_agent:
  enabled: true
  llm:
    provider: openai
    model: gpt-4o

Best Practices

1. Follow agent-specific guidelines
2. Monitor performance metrics
3. Handle errors gracefully
4. Log important events
5. Integrate with observability

Cost Considerations

Typical cost: $0.05-0.20 per operation depending on complexity

Limitations

• Depends on LLM quality
• Context window limits
• May require multiple iterations

References

• Artemis Documentation
• Agent Pattern

Version: 1.0.0

Maintained By: Artemis Pipeline Team

Last Updated: October 24, 2025