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search_staff

Find AniList staff members by query term, with options to paginate and limit results for efficient searching and data retrieval.

Instructions

Search for staff members based on a query term

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amountNoResults per page (max 25)
pageNoPage number for results
termYesSearch term for finding staff members

Implementation Reference

  • The handler function that performs the staff search by calling anilist.searchEntry.staff and returns formatted JSON results or an error message.
    async ({ term, page, amount }) => {
      try {
        const results = await anilist.searchEntry.staff(term, page, amount);
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(results, null, 2),
            },
          ],
        };
      } catch (error: any) {
        return {
          content: [{ type: "text", text: `Error: ${error.message}` }],
          isError: true,
        };
      }
    },
  • Zod input schema for the search_staff tool parameters: term (required string), page and amount (optional numbers with defaults).
    {
      term: z.string().describe("Search term for finding staff members"),
      page: z
        .number()
        .optional()
        .default(1)
        .describe("Page number for results"),
      amount: z
        .number()
        .optional()
        .default(5)
        .describe("Results per page (max 25)"),
    },
  • Registration of the search_staff tool on the MCP server within the registerSearchTools function, including name, description, schema, hints, and handler.
    server.tool(
      "search_staff",
      "Search for staff members based on a query term",
      {
        term: z.string().describe("Search term for finding staff members"),
        page: z
          .number()
          .optional()
          .default(1)
          .describe("Page number for results"),
        amount: z
          .number()
          .optional()
          .default(5)
          .describe("Results per page (max 25)"),
      },
      {
        title: "AniList Staff Search",
        readOnlyHint: true,
        openWorldHint: true,
      },
      async ({ term, page, amount }) => {
        try {
          const results = await anilist.searchEntry.staff(term, page, amount);
          return {
            content: [
              {
                type: "text",
                text: JSON.stringify(results, null, 2),
              },
            ],
          };
        } catch (error: any) {
          return {
            content: [{ type: "text", text: `Error: ${error.message}` }],
            isError: true,
          };
        }
      },
    );
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 mentions searching but doesn't disclose behavioral traits like pagination (implied by parameters), rate limits, authentication needs, or what constitutes a 'staff member'. The description is minimal and lacks crucial operational details for a search tool.

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 with zero waste—it directly states the tool's function without redundancy. It is appropriately sized and front-loaded, making it easy 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 no annotations, no output schema, and a search tool with 3 parameters, the description is incomplete. It lacks details on return format (e.g., what fields are included), error handling, or how search results are ranked. For a tool with moderate complexity, this leaves significant gaps for an AI agent.

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?

Schema description coverage is 100%, so the schema fully documents parameters (term, amount, page). The description adds no additional meaning beyond implying 'term' is for searching, which is already clear from the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

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 ('search') and target resource ('staff members') with the constraint 'based on a query term'. It distinguishes from siblings like 'get_staff' (likely a direct fetch) by specifying search functionality, though it doesn't explicitly contrast with 'search_user' or 'search_activity' which share similar patterns.

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?

No guidance is provided on when to use this tool versus alternatives like 'get_staff' (which might retrieve specific staff by ID) or other search tools (e.g., 'search_user'). The description implies usage for finding staff with a query but lacks explicit context, 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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