YouTube Transcript MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must fully disclose behavioral traits. It mentions that the tool returns a summary with statistics and sample text, which gives some output context, but it lacks details on permissions, rate limits, error handling, or whether it's a read-only operation. For a tool with no annotations, this is insufficient to ensure safe and effective use.

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

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

The description is well-structured and concise, with no wasted words. It front-loads the purpose in the first sentence, followed by clear sections for arguments and returns. Each sentence adds value, making it easy to parse and understand quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is partially complete. It covers the purpose and parameters adequately but lacks usage guidelines, behavioral details, and output specifics. Without annotations or an output schema, more context on the return format or operational constraints would improve completeness.

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

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

The description adds meaningful semantics beyond the input schema, which has 0% description coverage. It explains that 'video_id' can be a YouTube video ID or URL, 'language_code' is optional, and 'max_length' controls the sample text length. This compensates well for the schema's lack of descriptions, though it doesn't specify format details like valid language codes or length constraints.

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

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

The description clearly states the tool's purpose: 'Get a summary of the transcript including key statistics and sample text.' It specifies the verb ('Get') and resource ('transcript summary'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_transcript' or 'search_transcript', which likely provide different outputs or functionalities.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 such as 'get_transcript' or 'search_transcript', nor does it specify use cases, prerequisites, or exclusions. This leaves the agent without context for tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.