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favourite_studio

Mark or unmark a studio as favourite on AniList using its unique ID. Requires login to manage your preferred studios efficiently.

Instructions

[Requires Login] Favourite or unfavourite a studio by its ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe AniList ID of the studio to favourite/unfavourite

Implementation Reference

  • The handler function that implements the core logic of the 'favourite_studio' tool. It performs authentication, calls the external AniList library's favouriteStudio method with the provided studio ID, and returns a formatted text response indicating success or failure.
    async ({ id }) => {
      try {
        const auth = requireAuth(config.anilistToken);
        if (!auth.isAuthorized) {
          return auth.errorResponse;
        }
    
        const result = await anilist.favouriteStudio(id);
        return {
          content: [
            {
              type: "text",
              text: result
                ? `Successfully added studio with ID ${id} to favourites.`
                : `Studio with ID ${id} was removed from favourites or operation failed.`,
            },
          ],
        };
      } catch (error: any) {
        return {
          content: [{ type: "text", text: `Error: ${error.message}` }],
          isError: true,
        };
      }
    },
  • Input schema using Zod to validate the 'id' parameter as a number, with a descriptive annotation.
    {
      id: z
        .number()
        .describe("The AniList ID of the studio to favourite/unfavourite"),
    },
  • tools/misc.ts:13-53 (registration)
    The registration of the 'favourite_studio' tool on the MCP server, specifying name, description, input schema, hints, and handler function.
    server.tool(
      "favourite_studio",
      "[Requires Login] Favourite or unfavourite a studio by its ID",
      {
        id: z
          .number()
          .describe("The AniList ID of the studio to favourite/unfavourite"),
      },
      {
        title: "Favourite/Unfavourite Studio",
        readOnlyHint: false,
        destructiveHint: true,
        idempotentHint: false,
        openWorldHint: true,
      },
      async ({ id }) => {
        try {
          const auth = requireAuth(config.anilistToken);
          if (!auth.isAuthorized) {
            return auth.errorResponse;
          }
    
          const result = await anilist.favouriteStudio(id);
          return {
            content: [
              {
                type: "text",
                text: result
                  ? `Successfully added studio with ID ${id} to favourites.`
                  : `Studio with ID ${id} was removed from favourites or operation failed.`,
              },
            ],
          };
        } 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the login requirement, which is useful, but fails to describe whether this is a toggle operation (favourite/unfavourite), what happens on success/failure, or any rate limits or side effects. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 extremely concise with just one sentence that front-loads the login requirement and states the action and resource. There is zero wasted text, and every word earns its place, making it highly efficient and well-structured.

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 that this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on the operation's behavior (e.g., toggle vs. set, response format, error handling), which are crucial for an AI agent to use it correctly. The login hint is helpful but insufficient for full contextual understanding.

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, with the 'id' parameter clearly documented as 'The AniList ID of the studio to favourite/unfavourite'. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 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 ('favourite or unfavourite') and resource ('a studio by its ID'), making the purpose specific and actionable. However, it doesn't explicitly distinguish this tool from similar sibling tools like 'favourite_anime', 'favourite_character', etc., which all follow the same pattern for different entity types.

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 includes a prerequisite '[Requires Login]', which provides some context for when authentication is needed. However, it doesn't offer guidance on when to use this tool versus alternatives (e.g., other favourite_* tools for different entities) or any exclusions, leaving usage somewhat implied rather than explicit.

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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