get_transcript

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

Annotations already indicate read-only and open-world hints, but the description adds valuable behavioral context: the automatic language fallback mechanism and the ad-stripping functionality based on chapter markers. This goes beyond annotations by explaining conditional behaviors and processing logic, though it doesn't cover rate limits or error handling.

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, well-structured sentence that efficiently conveys the core functionality and key behavioral traits (language fallback). Every word serves a purpose, with no redundancy or unnecessary elaboration, making it easy to parse 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 (4 parameters, read-only operation) and the presence of both rich annotations and an output schema, the description is largely complete. It covers the main action and notable behaviors, though it could benefit from mentioning output format or error cases. The output schema likely handles return values, reducing the burden on the description.

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?

With 100% schema description coverage, the input schema fully documents all parameters. The description mentions language fallback and ad-stripping, which are already covered in the schema descriptions for 'lang' and 'strip_ads'. It adds no significant semantic information beyond what the schema provides, so 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 specific action ('Extract transcript'), resource ('from a YouTube video'), and input type ('URL or ID'). It also mentions the fallback behavior for language selection, which adds specificity. With no sibling tools to distinguish from, this is maximally clear.

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 implies usage for extracting transcripts from YouTube videos, but provides no explicit guidance on when to use this tool versus alternatives (e.g., other transcript tools or manual methods). Since there are no sibling tools, it doesn't need to differentiate, but it lacks broader context about prerequisites or typical use cases.

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