Requirements Parser Agent

Purpose

Extracts and structures requirements from documents using NLP and LLM intelligence

When to Use This Skill

1. Project Kickoff - Parse initial requirements
2. Requirement Updates - Process change requests
3. Compliance Verification - Ensure complete requirements
4. Sprint Planning Input - Provide structured backlog

Responsibilities

1. Parse natural - language requirements documents
2. Extract functional - and non-functional requirements
3. Classify requirements - (MoSCoW: Must/Should/Could/Won't)
4. Identify dependencies - and constraints
5. Validate requirement - completeness and clarity

Integration with Pipeline

Communication

Receives:

• Input data specific to agent's purpose

Sends:

• Processed output and analysis results

Usage Examples

Standalone Usage

python3 requirements_parser_agent.py --help

Programmatic Usage

from requirements_parser_agent import RequirementsParserAgent

agent = RequirementsParserAgent()
result = agent.execute()

Configuration

Environment Variables

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

Hydra Configuration (if applicable)

requirements_parser_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