clean_youtube_transcript

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 'AI-powered comprehensive summaries' and 'high-precision subtitles', but does not describe potential side effects (e.g., it may call external Gemini API, may require auth, may have rate limits/delays). The description doesn't state whether this is a read-only operation or what happens with the data. This lack of disclosure leaves the agent without essential behavioral context.

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 a single sentence, concise and front-loaded with the primary action. It avoids verbosity but doesn't offer any structural breakdown for multiple outputs (subtitles vs transcripts vs summaries) or parameter-specific details. It's efficient but minimal.

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 no annotations and no output schema, the description must carry substantial context. It lacks guidance on which output type to expect, how language selection works, or when the AI summary is appropriate. The tool handles several modes but the description doesn't explain how to choose among them or what the response looks like.

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 covers all three parameters (url, lang, auth_token_or_tx) but with minimal descriptions. The description adds no meaning beyond what the schema provides — it doesn't explain the `lang` default format ('ko,en') or the purpose of `auth_token_or_tx`. Since schema coverage is 100%, baseline is 3, but the description fails to enrich or clarify parameter semantics for an agent.

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 specifies a clear verb ('Extracts') and a resource ('subtitles, transcripts, or AI-powered comprehensive summaries for any YouTube video'), which tells the agent what the tool operates on. It distinguishes itself from generic transcript tools by mentioning Gemini AI for high-precision output. However, the description doesn't explicitly contrast with sibling tools (none provided), so it doesn't fully separate from alternatives.

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 states the general action ('Extracts ... for any YouTube video') but provides no guidance on when to use this tool versus alternatives. There are no sibling tools listed, no mention of use cases, prerequisites, or scenarios where this tool would be preferred. Without this context, an agent must infer usage from the schema alone.

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