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favourite_character

Add or remove characters as favorites on AniList using their unique ID. Requires user login to manage your preferred anime characters quickly.

Instructions

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

Input Schema

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

Implementation Reference

  • The handler function for the 'favourite_character' tool. It authenticates using requireAuth, calls anilist.people.favouriteChar(id) to toggle the favourite status, and returns a success or error message.
      async ({ id }) => {
        try {
          const auth = requireAuth(config.anilistToken);
          if (!auth.isAuthorized) {
            return auth.errorResponse;
          }
    
          const result = await anilist.people.favouriteChar(id);
          return {
            content: [
              {
                type: "text",
                text: result
                  ? `Successfully added character with ID ${id} to favourites.`
                  : `Character 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 for the 'favourite_character' tool, defining the 'id' parameter as a required number (AniList character ID).
    {
      id: z
        .number()
        .describe("The AniList ID of the character to favourite/unfavourite"),
    },
  • tools/people.ts:48-88 (registration)
    Registration of the 'favourite_character' MCP tool using server.tool(), including name, description, input schema, metadata hints, and handler function.
      "favourite_character",
      "[Requires Login] Favourite or unfavourite a character by its ID",
      {
        id: z
          .number()
          .describe("The AniList ID of the character to favourite/unfavourite"),
      },
      {
        title: "Favourite/Unfavourite Character",
        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.people.favouriteChar(id);
          return {
            content: [
              {
                type: "text",
                text: result
                  ? `Successfully added character with ID ${id} to favourites.`
                  : `Character 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 key traits like whether this is a toggle action (favourite/unfavourite), potential side effects (e.g., updates to user profiles), rate limits, or error conditions. This leaves significant gaps for an AI agent.

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 highly concise and front-loaded, consisting of just one sentence that efficiently conveys the core purpose and prerequisite. Every word earns its place, with no wasted information, making it easy for an AI 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 complexity of a mutation tool (favourite/unfavourite) with no annotations and no output schema, the description is incomplete. It lacks details on behavior (e.g., toggle nature), return values, error handling, and how it integrates with sibling tools, leaving the AI agent with insufficient context for reliable use.

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 schema description coverage is 100%, with the 'id' parameter clearly documented as 'The AniList ID of the character to favourite/unfavourite'. The description adds no additional semantic context beyond this, so it meets the baseline score of 3 for adequate but not enhanced parameter understanding.

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 ('favourite or unfavourite') and resource ('a character by its ID'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'favourite_anime' or 'favourite_manga' beyond the character focus, which prevents a perfect 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 minimal guidance with '[Requires Login]', indicating a prerequisite, but offers no explicit advice on when to use this tool versus alternatives (e.g., when to favourite vs. unfavourite, or how it relates to other favourite tools). This lack of context-specific direction limits its utility for an AI agent.

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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