transcribe_start

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

No annotations provided, so description carries full burden. It discloses background execution, immediate return, Web UI prerequisite, and return format. Missing details like auth or side effects, but core behavior is transparent.

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?

Description is concise and well-structured: purpose first, then usage context, detailed flow, prerequisite, and return shape. Every sentence adds value with no redundancy.

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 5 parameters, no output schema, and no annotations, the description provides a good high-level summary but fails to document most parameters. This gap hinders correct invocation despite solid flow guidance.

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 0%, so description must compensate for 5 parameters. It only mentions file_path in the flow, ignoring language, model_size, num_speakers, and enable_diarization. This leaves agents without guidance for these critical inputs.

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?

Description clearly states the tool starts transcription as a background job and returns a job_id immediately. It distinguishes from transcribe_podcast by specifying use for long files, providing a specific verb and resource.

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?

Explicitly tells when to use this tool vs transcribe_podcast ('for long files so you can narrate progress'), and provides a complete workflow. This clear context and exclusion of alternative makes it highly actionable.

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