transcribe

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

Annotations are absent, so the description carries the burden. It discloses the exact return format ({ok, text, words, duration, language}), input types (local path or URL), error shape, and dry_run cost-saving behavior. It could mention auth, file size limits, or processing time, but core behavior is transparent.

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?

Four dense sentences, front-loaded with the core capability. Every sentence serves a purpose: use cases, input contract, return contract, and cost-saving option. No filler or redundancy.

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 output schema, it still explains return values thoroughly and covers common invocation concerns. It is complete enough for selection and basic use; missing details like format limitations or authentication are not critical for an agent deciding to invoke it.

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 coverage is 100%, so baseline 3 applies. The description reinforces the audio param type and dry_run purpose, but adds no meaningful parameter-level detail beyond what the schema already provides.

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?

Clearly states the verb 'Transcribe speech' and the resource ('audio or video file') and differentiates itself with word-level timestamps. The mention of chaining into caption_video distinguishes this tool from sibling tools like video_analysis and audio_generate.

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?

Provides concrete use cases: captioning a video, reading a voiceover, analyzing a competitor ad's spoken script, and explicitly suggests the transcribe -> caption_video chain. It lacks explicit when-not-to-use guidance or named alternatives, but the context is strong enough for an agent to decide.

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