asr

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals input format constraints and the effect of the language parameter on accuracy, but it does not describe the output format beyond 'plain text', nor does it mention potential side effects, timeout behavior, or error handling. That leaves gaps for a tool with no annotation support.

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 concise and well-structured: it starts with the core purpose, followed by use-case context, then constraints, and ends with a performance tip. Every sentence contributes meaningful information without redundancy or fluff.

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 tool with no output schema, the description does not fully specify the return format or structure. It mentions the result is plain text, but not whether it returns a string, JSON object, or includes metadata. It also lacks info on error cases or asynchronous behavior. Given the tool's moderate complexity and missing output schema, the description is decent but incomplete.

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. The description adds value beyond the schema by explaining that specifying the language (auto/zh/en) can improve accuracy, which is not evident from the enum alone. It also reinforces the audio format and size limits already present in the schema, giving practical guidance.

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's purpose: converting audio to plain text via speech recognition (ASR). It specifies the resource (audio) and the action (transcription), and differentiates from siblings like analyze_audio by focusing on producing text rather than analyzing audio features.

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 clear context on when to use the tool: 'suitable for meeting notes, dialects, noisy environment recordings'. It also gives constraints (wav/mp3, max 10MB). However, it does not explicitly mention when not to use it or name alternative tools such as analyze_audio, so it stops short of a full 5.

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