Voxtral speech-to-text

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds behavioral context beyond annotations by listing input constraints (accepted audio formats, model options), optional parameters affecting behavior (diarize, timestamps, context bias), and return structure (plain text, detected language, segments, token usage). No contradictions with annotations.

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 well structured with clear sections for models, audio source, options, and returns. It front-loads the core purpose. However, it could be slightly more concise by avoiding repetition of parameter names already shown in the schema. Overall, it's efficiently written and easy to scan.

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 has 7 parameters (1 required), a moderately complex input schema, and an output schema, the description covers all necessary behavioral details: accepted models, audio source mechanisms, optional features like diarization and timestamps, and return structure. The output schema exists, so the description's mention of return values is sufficient.

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?

The description adds substantial meaning beyond the input schema. It explains the two audio source structures in detail, lists accepted models by name, clarifies that language is an ISO-639-1 hint, describes diarize and timestampGranularities options, and introduces contextBias. With only 43% schema description coverage, the description compensates fully by documenting every parameter effectively.

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 transcribes audio to text using a specific model family (Mistral Voxtral). It lists accepted models and audio source formats, making the purpose unmistakable. This distinctly separates it from sibling tools like codestral_fim or mistral_chat which serve different functions.

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 provides explicit guidance on how to specify audio sources (file_url or file) and accepted models. It details optional parameters like language hints and diarization. While it doesn't explicitly state when not to use this tool or name alternatives, the context from sibling tools implies use cases are clear.

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