yt-analysis-mcp

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 states the tool 'Returns a text summary based on the specified detail level', which implies a read-only operation without side effects. However, it doesn't mention potential limitations such as video length constraints, processing time, authentication needs, or rate limits. The description is adequate but lacks depth for a tool with no annotation support.

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 highly concise and front-loaded, consisting of just two sentences that directly state the tool's function and output. Every word earns its place, with no redundant or vague phrasing. It efficiently communicates the core purpose without unnecessary elaboration.

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 (2 parameters, no output schema, no annotations), the description is minimally complete. It covers the basic action and output type but lacks details on error handling, summary format (e.g., bullet points vs. paragraphs), or example outputs. Without an output schema, more guidance on return values would be beneficial, but the description meets the minimum viable threshold.

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 input schema has 100% description coverage, with clear documentation for 'youtube_url' (URL formats) and 'detail_level' (enum values with explanations). The description adds minimal value beyond the schema, only reiterating that summarization is 'based on the specified detail level'. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.

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: 'Summarize a YouTube video's content' with the verb 'summarize' and resource 'YouTube video'. It distinguishes from siblings like 'ask_about_video' (Q&A), 'extract_frames' (image extraction), 'extract_screenshots' (screenshot capture), and 'get_video_timestamps' (timestamp listing) by focusing on textual summarization. However, it doesn't explicitly contrast with these alternatives, preventing 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.

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 its siblings. It mentions a 'detail level' parameter but doesn't explain scenarios where 'brief', 'medium', or 'detailed' summaries are appropriate, nor does it reference alternatives like 'ask_about_video' for specific queries. This lack of contextual usage advice limits its effectiveness 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.