transcribe

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

With no annotations, the description carries the full behavioral burden and delivers real constraints: the 25 MB upload cap and the https-link requirement. It also notes timestamps are returned only 'when the model returns them', which preempts a false expectation of guaranteed timestamps. It stops short of describing error behavior or output formatting.

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?

Three compact sentences with the core purpose front-loaded, then the optional capability, then the operational constraint and model routing. Every sentence carries information; only slight density loss from the parenthetical use-cases.

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?

For a 3-parameter tool with no output schema and no annotations, the description covers purpose, input constraints, model selection path, and the optional timestamps behavior. A brief note on the returned text format would close the remaining gap, but nothing needed to invoke it correctly is missing.

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 the baseline is 3, but the description earns above baseline by enumerating concrete model ids ("openai/gpt-4o-transcribe", "openai/whisper-1", "google/gemini-3.5-transcribe") that the schema has no enum for, and by restating the 25 MB ceiling on audio_url that the schema omits.

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?

States a specific verb+resource (turn speech in audio/video into text) and immediately scopes it with the optional-timestamps variant, distinguishing it from audio-adjacent siblings like generate_speech (text→speech) and generate_text. An agent can tell exactly what this tool produces without opening the schema.

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?

Gives concrete invocation guidance: supply an https link, max 25 MB, and pick a model from list_models with type "transcription", explicitly pointing to the sibling that resolves the model argument. It does not explicitly state when-not to use it, but the transcription framing is unambiguous against the sibling set.

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