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kitan23

Dedalus MCP Documentation Server

by kitan23

analyze_docs

Analyze documentation for tasks like finding gaps, generating outlines, or checking consistency to prepare results for agent handoffs.

Instructions

Analyze documentation for specific tasks (foundation for agent handoffs)

Args:
    task: Analysis task (e.g., "find_gaps", "generate_outline", "check_consistency")
    docs: Optional list of specific documents to analyze
    output_format: Output format (summary, detailed, structured)

Returns:
    Analysis results ready for agent handoff

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYes
docsNo
output_formatNosummary

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The complete implementation of the analyze_docs tool, including the @mcp.tool() decorator for registration, type-hinted parameters serving as input schema, docstring, validation logic, document gathering via list_docs(), and structured output for agent handoffs.
    @mcp.tool()
    def analyze_docs(
        task: str, docs: Optional[List[str]] = None, output_format: str = 'summary'
    ) -> Dict[str, Any]:
        """
        Analyze documentation for specific tasks (foundation for agent handoffs)
    
        Args:
            task: Analysis task (e.g., "find_gaps", "generate_outline", "check_consistency")
            docs: Optional list of specific documents to analyze
            output_format: Output format (summary, detailed, structured)
    
        Returns:
            Analysis results ready for agent handoff
        """
        available_tasks = [
            'find_gaps',
            'generate_outline',
            'check_consistency',
            'extract_examples',
            'identify_prerequisites',
            'suggest_improvements',
        ]
    
        if task not in available_tasks:
            return {
                'error': f'Unknown task. Available tasks: {", ".join(available_tasks)}',
                'available_tasks': available_tasks,
            }
    
        # Gather documents to analyze
        if not docs:
            all_docs = list_docs()
            docs = [doc['path'] for doc in all_docs]
    
        # This is where different analysis agents would be invoked
        # Structure the response for easy handoff to specialized agents
        return {
            'task': task,
            'documents_analyzed': len(docs),
            'output_format': output_format,
            'results': {
                'summary': f"Analysis task '{task}' ready for processing",
                'documents': docs,
                'next_steps': [
                    'Connect specialized agent for this task',
                    'Process documents according to task requirements',
                    'Return structured results',
                ],
            },
            'agent_handoff_ready': True,
            'suggested_model': 'gpt-4'
            if task in ['find_gaps', 'check_consistency']
            else 'claude-3-5-sonnet',
        }
  • src/main.py:49-49 (registration)
    The analyze_docs tool is listed in the MCP server instructions as an available tool with its description.
    - analyze_docs(task): Analyze documentation for specific tasks
  • src/main.py:539-539 (registration)
    The analyze_docs tool is listed among available tools in the test mode print statement.
    'Tools available: list_docs, search_docs, ask_docs, index_docs, analyze_docs'

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