Config Agent

Purpose

Provides type-safe, validated configuration management for Artemis

When to Use This Skill

1. System Initialization - Load configs
2. Environment Setup - Dev/staging/prod configs
3. Configuration Validation - Check correctness
4. Override Management - Apply runtime overrides

Responsibilities

1. Load Hydra - YAML configurations
2. Validate configuration - schemas
3. Support composition - and overrides
4. Environment-specific configs -
5. Type-safe configuration - access

Integration with Pipeline

Communication

Receives:

• Input data specific to agent's purpose

Sends:

• Processed output and analysis results

Usage Examples

Standalone Usage

python3 config_agent.py --help

Programmatic Usage

from config_agent import ConfigAgent

agent = ConfigAgent()
result = agent.execute()

Configuration

Environment Variables

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

Hydra Configuration (if applicable)

config_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