transcribe_audio

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

With no annotations, the description fully discloses behavioral traits: it is experimental, requires separate setup, runs in the background and returns a job_id immediately, handles model loading automatically, has occasional language auto-detection issues, and saves a transcript whose location must be communicated to the user. These are all non-obvious behaviors that an agent needs to know.

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?

Though the description is longer than average, every sentence adds necessary operational detail. It is well-structured: function and setup first, then background behavior, then troubleshooting/caveats, then parameter documentation. No redundancy or filler.

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?

This is a complex tool with background execution, setup requirements, and a failure-prone language auto-detection. The description covers the full workflow: call, monitor, handle failures, correct language, and inform the user of the output location. No gaps remain given the absence of an output schema.

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 input schema has no descriptions (0% coverage), but the description's Args section explains each parameter: model_size with listed options, language as ISO code or None, and task as transcribe/translate. This fully compensates for the schema's lack of detail.

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 the entire project audio using faster-whisper (local, offline).' It uses a specific verb and resource, and distinguishes itself from siblings by emphasizing 'entire project audio' and noting not to call transcription_set_model first. Though it doesn't explicitly contrast with transcribe_selection, the wording 'entire project audio' makes the scope clear.

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 usage guidance: tells the user to monitor via check_transcription_status, poll every 10-15 seconds, and explicitly says 'Do NOT call transcription_set_model first.' It also instructs what to do on failure, how to handle language misdetection with language/task parameters, and what to do after completion. This goes well beyond minimal guidance.

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