speech_to_text

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

With no annotations, the description carries full burden for behavioral disclosure. It mentions supported features (diarization, audio event tagging) but omits important details: required authentication, limits on audio length or file size, latency, and whether the operation is destructive or read-only. The description provides moderate transparency but lacks depth.

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 two sentences long, entirely front-loaded with the core purpose. Every sentence adds value: first states the action and model, second lists supported features and output. No wasted words.

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 no output schema and no annotations, the description covers the main purpose and supported features. However, it lacks details on output format (e.g., structure of transcription text, timestamps), error handling, and constraints (e.g., audio length, supported languages). It is fairly complete for a straightforward transcription tool but could be richer.

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 baseline is 3. The description mentions diarization and audio event tagging, which correspond to boolean parameters, adding slight context. However, it does not elaborate on parameter formats, defaults, or interactions beyond what the schema already provides.

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 verb 'Transcribe' and the resource 'audio to text', specifying the model (ElevenLabs Scribe v1) and key features (diarization, audio event tagging). It effectively distinguishes this tool from sibling tools like audio_isolation or generate_tts.

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 is provided on when to use this tool versus alternatives such as audio_isolation or separate_vocals. The description does not mention any prerequisites, constraints, or use cases, leaving the AI agent without decision-making context.

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