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latte-chan
by latte-chan

autocomplete

Complete Magic: The Gathering card names from partial input to speed up searches in the Scryfall MCP Server.

Instructions

Autocomplete card names based on a partial query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYes

Implementation Reference

  • The handler function for the 'autocomplete' tool. It takes a query 'q', calls Scryfall.autocomplete(q), and returns the result as JSON text content.
    async ({ q }: { q: string }): Promise<ToolResult> => {
        const data: unknown = await Scryfall.autocomplete(q);
        return { content: [{ type: "text", text: JSON.stringify(data, null, 2) }] } as any;
    }
  • Zod input schema for the autocomplete tool: requires a string query 'q'.
    const autocompleteParamsShape = { q: z.string() } as const;
  • Registration of the 'autocomplete' tool with MCP server, including name, description, input schema, and handler.
    server.registerTool(
        "autocomplete",
        {
            description: "Autocomplete card names based on a partial query.",
            inputSchema: autocompleteParamsShape
        },
        async ({ q }: { q: string }): Promise<ToolResult> => {
            const data: unknown = await Scryfall.autocomplete(q);
            return { content: [{ type: "text", text: JSON.stringify(data, null, 2) }] } as any;
        }
    );
  • Helper method in Scryfall object that makes API call to Scryfall's /cards/autocomplete endpoint.
    autocomplete: (q: string) => getJson("/cards/autocomplete", { q }),
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 the tool autocompletes card names, implying a read-only, non-destructive operation, but doesn't cover aspects like rate limits, error handling, response format, or performance characteristics. For a tool with zero annotation coverage, this is inadequate, as it leaves key behavioral traits unspecified.

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: 'Autocomplete card names based on a partial query.' It is front-loaded with the core purpose, contains no redundant information, and is appropriately sized for the tool's apparent simplicity. Every word earns its place, making it highly concise 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 the lack of annotations, no output schema, and low schema description coverage, the description is incomplete. It doesn't address what the tool returns, how results are formatted, or any behavioral nuances. For a tool with one parameter but no structured support, the description should provide more context to be fully helpful to an agent.

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

Parameters2/5

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

The description mentions 'based on a partial query,' which hints at the 'q' parameter's purpose, but with 0% schema description coverage, it doesn't add meaningful semantics beyond the schema. It fails to explain what constitutes a valid query, expected formats, or examples, leaving the parameter poorly documented. This is below the baseline of 3 due to low coverage without compensation.

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 tool's purpose: 'Autocomplete card names based on a partial query.' This specifies the verb ('Autocomplete'), resource ('card names'), and mechanism ('based on a partial query'). However, it doesn't explicitly differentiate from sibling tools like 'search_cards' or 'get_card', which might offer similar 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. It doesn't mention any prerequisites, exclusions, or comparisons to sibling tools such as 'search_cards' or 'get_card', leaving the agent with no context for tool selection. This is a significant gap in usage guidance.

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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