Transcribe video audio

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so no contradiction. The description adds behavioral context beyond these: it specifies the order of caption/Whisper sources, notes that local files require Whisper or sidecar, and states YouTube is fast due to native captions. This helps an agent set expectations about execution time and dependencies without repeating annotation information.

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 extremely concise: three short lines that front-load the core purpose and then provide the resolution order and practical tips. There is zero fluff or redundancy. Every sentence serves a purpose, from the output definition to the operational hints.

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 modest complexity (4 params, all documented in schema) and the annotations covering safety (read-only, idempotent), the description is largely complete. It indicates the output is a timestamped transcript and outlines the method. It might benefit from an explicit note about the response format (markdown vs json) but that is in the schema. Overall, an agent can call this tool correctly without missing critical information.

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?

Schema description coverage is 100%, so the schema already documents all parameters (source, language, force_whisper, response_format). The description does not add significant per-parameter semantics beyond what the schema provides, though it does contextualize the preference order (captions vs force_whisper) and mentions Whisper for local/cloud, which aligns with the source parameter. Since the schema handles the heavy lifting, a baseline 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: producing a timestamped transcript from video audio, with a specified preference for captions or Whisper. It uses a specific verb ('transcribe') and resource ('video audio'), and the output type is explicitly named. It naturally differentiates from sibling tools like video_analyze or video_ocr, which are not transcription-focused.

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?

It provides practical guidance on when the tool is efficient (fast for YouTube) and requirements for local files (need Whisper or sidecar captions). It also outlines the source resolution order. However, it does not explicitly mention when to use an alternative tool (e.g., if visual analysis is needed), but the purpose is clear enough that an agent can infer suitability. This is strong guidance, missing only direct exclusion of alternatives.

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