transcribe

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

With no annotations present, the description carries the full burden of behavioral disclosure and does a solid job by stating not only the action but the exact return payload: 'segments with timestamps, text, and confidence scores.' It also names the underlying engine, Whisper, which helps set expectations. It does not detail limitations or prerequisites, but the described behavior is concrete and useful.

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 one efficient sentence that front-loads the core purpose and follows with the output structure. There is no wasted phrasing or redundant information, and every word contributes to an agent's understanding of what the tool does.

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 that the tool has only two parameters, no output schema, and no annotations, the description covers the essential elements: what it does, how it does it, and what it returns. It could add guidance about how this step fits with sibling tools like detect_hallucinations or repair, but that omission does not prevent correct use of the tool itself.

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 both parameters, audio_path and language. The description adds no extra meaning about either parameter, such as default language behavior or audio format handling. The baseline score of 3 is appropriate because the schema does the heavy lifting and the description does not need to compensate.

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 uses a specific verb-resource pair, 'Transcribe an audio file using Whisper', and clearly distinguishes this tool from sibling tools like detect_hallucinations, repair, score, and estimate_cost, which operate on transcription results rather than producing them. It is immediately obvious what this tool does and how it differs from others.

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 clearly implies when to use the tool: whenever an audio file needs to be transcribed. It names the input type and the model used, providing clear context. It does not explicitly discuss when not to use it or compare to alternatives, but the sibling names suggest downstream processing rather than competing transcription options, so the basic usage context is adequate.

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