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dhevenb

Spec3 MCP Server

by dhevenb

list_documents

Retrieve available Spec3 racing reference documents including constructor guides, manuals, and rules for race preparation and compliance.

Instructions

List all available Spec3 racing reference documents.

Available documents include: Spec3 Constructor's Guide, Bentley E36 Manual, 2025 NASA CCR rules, and 2025 Spec3 class rules.

Returns: dict: Document IDs, names, and descriptions

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The async handler function that implements the 'list_documents' tool logic. It constructs a list of available documents from the AVAILABLE_DOCS dictionary, including each document's ID, name, and description, and returns it along with the count.
    async def list_documents() -> dict[str, Any]:
        """
        List all available Spec3 racing reference documents.
    
        Available documents include: Spec3 Constructor's Guide, Bentley E36 Manual,
        2025 NASA CCR rules, and 2025 Spec3 class rules.
    
        Returns:
            dict: Document IDs, names, and descriptions
        """
        logger.info("list_documents called")
    
        docs_list = []
        for doc_id, doc_info in AVAILABLE_DOCS.items():
            docs_list.append({
                "id": doc_id,
                "name": doc_info["name"],
                "description": doc_info["description"]
            })
    
        return {
            "documents": docs_list,
            "count": len(docs_list)
        }
  • The @mcp.tool() decorator registers the list_documents function as an available tool in the FastMCP server.
    @mcp.tool()
  • Docstring providing the tool description, usage, and return type annotation, which FastMCP likely uses to generate the tool schema for MCP.
    """
    List all available Spec3 racing reference documents.
    
    Available documents include: Spec3 Constructor's Guide, Bentley E36 Manual,
    2025 NASA CCR rules, and 2025 Spec3 class rules.
    
    Returns:
        dict: Document IDs, names, and descriptions
    """
  • AVAILABLE_DOCS constant dictionary that defines the list of available Spec3 documents, directly used by the list_documents handler.
    AVAILABLE_DOCS = {
        "spec3_constructor_guide": {
            "name": "Spec3 E36 Race Car Constructor's Guide",
            "s3_key": "Spec3 E36 Race Car Contsructor's Guide.pdf",
            "description": "Comprehensive guide for building a Spec3 E36 race car"
        },
        "bentley_manual_general": {
            "name": "Bentley General Manual",
            "s3_key": "bentley_general.pdf",
            "description": "Bentley BMW E36 Manual - GENERAL SECTION"
        },
        "nasa_ccr": {
            "name": "2025 NASA Competition Comp Rules (CCR)",
            "s3_key": "2025.4_NASACCR.pdf",
            "description": "2025 NASA Club Championship Racing rules"
        },
        "spec3_rules": {
            "name": "2025 Spec3 Rules",
            "s3_key": "2025_Spec3_Rules.pdf",
            "description": "2025 Spec3 racing class specific rules and regulations"
        }
    }
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses that the tool returns a dictionary with IDs, names, and descriptions, which is helpful behavioral context. However, it doesn't mention potential limitations like pagination, rate limits, or authentication needs, leaving gaps for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded: the first sentence states the purpose, followed by examples of available documents, and ends with return value details. Every sentence adds value without redundancy, making it efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, no annotations, but with an output schema), the description is reasonably complete. It explains what the tool does, provides examples of documents, and describes the return format. However, it could be more complete by explicitly guiding usage relative to siblings or noting any constraints, slightly reducing the score.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so the schema fully documents the lack of inputs. The description appropriately adds no parameter information, as none are needed, and instead focuses on output semantics. This meets the baseline of 4 for zero-parameter tools.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'List all available Spec3 racing reference documents' with a specific verb ('List') and resource ('Spec3 racing reference documents'). It distinguishes from sibling 'get_document' by indicating this lists available documents rather than retrieving a specific one, though it doesn't explicitly contrast with 'get_car_context'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by listing available documents and their types, suggesting this tool is for discovering what documents exist. However, it doesn't provide explicit guidance on when to use this versus 'get_document' (e.g., 'use this to find document IDs before retrieving content') or mention any prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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