stt_transcribe

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

Without annotations, the description carries full burden but only states input formats and model use. It fails to disclose output format, size limits, or other behavioral traits (e.g., synchronous/asynchronous, supported audio duration).

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?

Two concise sentences, no extraneous information. Every word is necessary; front-loaded with the core action.

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?

With no output schema and multiple input parameters, the description fails to explain return values or error handling. It does not specify whether the tool returns JSON with transcribed text, audio duration info, or confidence scores.

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 schema already describes parameters. The description adds value by grouping input types (file, URL, base64) but does not clarify model or language semantics beyond the schema.

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: transcribe audio to text using the Whisper model. It lists accepted input formats (file path, URL, or base64 audio), distinguishing it from sibling tools like tts_speech (text-to-speech) and diarize_audio (speaker diarization).

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 implies use when audio transcription is needed but provides no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives among sibling tools like diarize_audio or summary_text.

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