transcribe_selection

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

With no annotations, the description carries the full burden, and it does well: it discloses the experimental status, separate setup requirement, background execution with immediate job_id return, and the risk of language auto-detection misidentifying short or ambiguous clips. It does not describe error behavior or what happens if no region is selected, but the disclosed behavior is substantial and useful.

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 longer than average but every sentence delivers critical information: setup, selection prerequisite, async behavior, monitoring path, language caveat, and parameter semantics. It is well-structured with a clear Args block and no 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?

For a tool with three optional parameters, no output schema, and no annotations, the description covers the prerequisites, execution model, monitoring pattern, failure mode, and all parameter values. An agent has enough context to invoke it correctly and know what to expect.

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 schema only provides parameter names, types, and defaults, while the description's Args section adds concrete allowed values for model_size ("tiny", "base", "small", "medium", "large-v3"), the meaning of language (ISO code or None), and valid task values ("transcribe" or "translate"). It also provides practical guidance like passing `language` explicitly to avoid misdetection.

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 states a specific verb and resource: "Transcribe only the currently selected audio region." The word "only" clearly scopes this tool to selection-based transcription and distinguishes it from broader sibling tools like transcribe_audio or transcribe_to_labels.

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 gives clear context: select a region first, call the tool, and use check_transcription_status to monitor progress. It also explains when to pass `language` or `task="translate"`. It does not explicitly name alternative transcription tools or state when not to use them, but the usage context is clear and actionable.

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