Skip to main content
Glama
Golrigames

Roller Derby Rules MCP Server

by Golrigames

get_section

Retrieve specific sections from French Roller Derby rules documentation, including game parameters, scoring, penalties, and officiating guidelines.

Instructions

Get the complete content of a specific rules section

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler function for the get_section tool. Retrieves the specified section's file using sectionMap, reads its content from the sections directory, and returns it as MCP content or an error if the section is invalid.
    async (args) => {
      const filename = sectionMap[args.section];
      if (!filename) {
        return {
          content: [
            {
              type: "text",
              text: `Invalid section: ${args.section}`,
            },
          ],
          isError: true,
        };
      }
    
      const filePath = path.join(SECTIONS_DIR, filename);
      const content = await fs.readFile(filePath, "utf-8");
    
      return {
        content: [
          {
            type: "text",
            text: content,
          },
        ],
      };
    }
  • Input schema for get_section tool defining the required 'section' parameter as a string with enum values for available sections.
    inputSchema: {
      type: "object",
      properties: {
        section: {
          type: "string",
          description: "The section to retrieve",
          enum: [
            "introduction",
            "parametres",
            "le-jeu",
            "score",
            "penalites",
            "arbitrage",
          ],
        },
      },
      required: ["section"],
    },
  • index.js:131-180 (registration)
    Registration of the get_section tool using server.registerTool, including name, schema, description, and handler.
    server.registerTool(
      "get_section",
      {
        description: "Get the complete content of a specific rules section",
        inputSchema: {
          type: "object",
          properties: {
            section: {
              type: "string",
              description: "The section to retrieve",
              enum: [
                "introduction",
                "parametres",
                "le-jeu",
                "score",
                "penalites",
                "arbitrage",
              ],
            },
          },
          required: ["section"],
        },
      },
      async (args) => {
        const filename = sectionMap[args.section];
        if (!filename) {
          return {
            content: [
              {
                type: "text",
                text: `Invalid section: ${args.section}`,
              },
            ],
            isError: true,
          };
        }
    
        const filePath = path.join(SECTIONS_DIR, filename);
        const content = await fs.readFile(filePath, "utf-8");
    
        return {
          content: [
            {
              type: "text",
              text: content,
            },
          ],
        };
      }
    );
  • Helper mapping object from section ID strings to corresponding markdown filenames, used by the get_section handler.
    const sectionMap = {
      introduction: "00-introduction.md",
      parametres: "01-parametres.md",
      "le-jeu": "02-le-jeu.md",
      score: "03-score.md",
      penalites: "04-penalites.md",
      arbitrage: "05-arbitrage.md",
    };
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states the tool gets content, implying a read operation, but doesn't disclose behavioral traits like whether it requires authentication, has rate limits, returns structured or unstructured data, or handles errors. For a tool with zero annotation coverage, this is a significant gap in transparency.

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 a single, clear sentence with zero waste—it directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple tool and front-loaded with essential information, making it highly efficient.

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

Completeness2/5

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

Given the tool's complexity (implied to fetch content), lack of annotations, no output schema, and 0 parameters, the description is incomplete. It doesn't explain what 'complete content' includes (e.g., text, metadata), how the section is specified, or what the return format is. For a tool that likely involves data retrieval, more context is needed to guide effective use.

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 no parameters need documentation. The description adds value by implying that a 'specific rules section' is targeted, but doesn't specify how that section is identified (e.g., by ID or name). Since there are no parameters, a baseline of 4 is appropriate, as the description provides some context beyond the empty schema.

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 action ('Get') and resource ('complete content of a specific rules section'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_sections' (which likely lists sections) or 'search_rules' (which likely searches across rules), leaving some ambiguity about when to choose this tool over others.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'list_sections' or 'search_rules'. It implies usage when you need content of a specific section, but doesn't specify prerequisites (e.g., how to identify the section) or exclusions (e.g., not for listing multiple sections). This lack of context makes it harder for an agent to select correctly.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Golrigames/RollerDerbyRulesMcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server