Transcribe audio

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

readOnlyHint=true is consistent with a transcription operation, and the description adds that an external OpenAI model performs the work, hinting at API cost/dependency. However, it discloses nothing about file size or duration limits, remote URL fetching behavior, latency, or error modes, so behavioral burden mostly falls on the schema.

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?

A single front-loaded sentence with no filler or redundancy. It is efficient, though its brevity means nothing is prioritized or expanded where the operation is non-trivial.

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 five-parameter tool wrapping an external paid API with no output schema, the description omits practical constraints an agent needs: input size/duration limits, whether remote URLs are fetched, expected latency, and cost implications. The schema covers parameter details, but operational context 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 description coverage is 100%, so file formats, model, format enum, prompt, and language are all documented in the schema itself. The description adds no parameter-level meaning beyond naming the model provider, which is the baseline for fully covered schemas.

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 and resource ('Transcribe spoken audio to text') plus the underlying engine ('OpenAI speech-to-text model'). It is reasonably distinguishable from sibling translate_audio by the verb 'transcribe', though it never explicitly contrasts the two.

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?

No guidance on when to use this tool versus translate_audio or generate_speech, and no preconditions such as file size limits, supported duration, or cost/auth implications of calling an OpenAI model. The agent must infer usage entirely from the name and schema.

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