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get_related_keywords

Find related keywords for a search query to expand research or content creation. Input a query to receive a list of associated terms.

Instructions

Get keywords related to a search query

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query
limitNoNumber of keywords to return (default: 10)

Implementation Reference

  • MCP tool handler for 'get_related_keywords'. Parses arguments, invokes the API client method, and formats the response as MCP content.
    handler: async (args) => {
      const { query, limit = 10 } = args;
      const result = await apiClient.getRelatedKeywords(query, limit);
      return {
        content: [{
          type: "text",
          text: JSON.stringify({
            success: true,
            data: result,
            message: `Found ${result.items?.length || 0} related keywords for "${query}"`
          }, null, 2)
        }]
      };
    }
  • Input schema defining the parameters for the get_related_keywords tool: required 'query' string and optional 'limit' number.
    inputSchema: {
      type: "object",
      properties: {
        query: {
          type: "string",
          description: "Search query"
        },
        limit: {
          type: "number",
          description: "Number of keywords to return (default: 10)",
          default: 10
        }
      },
      required: ["query"]
    },
  • server.js:900-932 (registration)
    Full tool registration object in the tools array for 'get_related_keywords', including name, description, schema, and handler.
    {
      name: "get_related_keywords",
      description: "Get keywords related to a search query",
      inputSchema: {
        type: "object",
        properties: {
          query: {
            type: "string",
            description: "Search query"
          },
          limit: {
            type: "number",
            description: "Number of keywords to return (default: 10)",
            default: 10
          }
        },
        required: ["query"]
      },
      handler: async (args) => {
        const { query, limit = 10 } = args;
        const result = await apiClient.getRelatedKeywords(query, limit);
        return {
          content: [{
            type: "text",
            text: JSON.stringify({
              success: true,
              data: result,
              message: `Found ${result.items?.length || 0} related keywords for "${query}"`
            }, null, 2)
          }]
        };
      }
    },
  • Supporting method in WebSimAPIClient that performs the actual HTTP request to retrieve related keywords from the WebSim API endpoint `/api/v1/search/related`.
    async getRelatedKeywords(query, limit = 10) {
      const params = new URLSearchParams({ q: query, limit: limit.toString() });
      return this.makeRequest(`/api/v1/search/related?${params}`);
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but lacks details on aspects like rate limits, authentication needs, error handling, or the format of returned keywords. For a tool with no 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, efficient sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded and wastes no space, making it easy for an agent to parse quickly.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'related keywords' means in practice, how they are generated, or what the return format looks like. For a tool with no structured output information, more context is needed to guide the agent effectively.

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

Parameters3/5

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

The input schema has 100% description coverage, clearly documenting both parameters ('query' and 'limit' with a default). The description doesn't add any semantic details beyond what the schema provides, such as examples or constraints, so it meets the baseline score for high schema coverage.

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 verb 'get' and the resource 'keywords related to a search query', making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_top_searches' or 'search_relevant_assets', which might have overlapping functionality, so it doesn't reach the highest score.

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 such as 'search_relevant_assets' or 'get_top_searches'. There's no mention of specific contexts, prerequisites, or exclusions, leaving the agent to guess based on tool names alone.

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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