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Ukenn2112

Bangumi TV MCP Service

by Ukenn2112

get_episode_details

Retrieve formatted details of a specific anime episode by providing its unique ID. Integrates with Bangumi TV API for accurate and structured episode information.

Instructions

Get details of a specific episode.

Args:
    episode_id: The ID of the episode.

Returns:
    Formatted episode details or an error message.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
episode_idYes
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 retrieves details (implying a read operation) and may return an error, but doesn't specify authentication needs, rate limits, data format, or what 'formatted episode details' entails. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured with three clear sections: purpose, args, and returns. Each sentence earns its place, and it's front-loaded with the main purpose. However, the 'Args' and 'Returns' sections could be integrated more smoothly, and some redundancy exists (e.g., 'episode_id' is repeated).

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 tool's complexity (simple retrieval), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'formatted episode details' includes, error conditions, or how it differs from sibling tools. For a tool in a server with many similar detail-fetching tools, more context is needed to guide effective use.

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

Parameters4/5

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

The description adds meaningful context for the single parameter 'episode_id' by specifying it's 'The ID of the episode', which clarifies its purpose beyond the schema's title 'Episode Id' and type 'integer'. With 0% schema description coverage and only one parameter, this adequately compensates, though it doesn't detail ID format or sources.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool's purpose as 'Get details of a specific episode', which is clear but vague. It specifies the verb ('Get') and resource ('episode details'), but doesn't distinguish it from sibling tools like 'get_episodes' (which likely lists multiple episodes) or 'get_subject_details' (which might provide similar detail for subjects). The purpose is understandable but lacks differentiation from related tools.

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 sibling tools like 'get_episodes' for listing episodes or 'get_subject_details' for related details, nor does it specify prerequisites or exclusions. The only implied usage is needing an episode_id, but this is covered in the input schema, not in contextual 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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