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

Annotations already establish non-readonly, non-destructive, non-idempotent behavior, so the description does not need to repeat those basics. It adds the auth precondition (transcription key) and the return format, which is useful. It does not disclose whether transcription is synchronous or asynchronous, or whether it persists anything, but the annotations cover the safety profile.

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 compact sentences with no filler. The first sentence states the core purpose and output; the second sentence gives the downstream workflow and a key prerequisite. Every clause earns its place.

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 single-parameter tool with no output schema, the description compensates well: it defines the return structure inline, identifies the next step in the pipeline, and states the required credential. An agent has enough information to select and call the tool correctly.

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 the single url parameter is already documented. The description adds the qualifier 'hosted' and ties the URL to the caption cue output, but adds little beyond what the schema already provides. Baseline 3 is appropriate.

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?

States a precise action — transcribe a hosted media/audio URL into time-coded caption cues — and gives the exact output shape. This clearly separates it from sibling studio tools like neuron_studio_voiceover or neuron_studio_transform_video.

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?

Explains the intended workflow by directing output to neuron_studio_apply add_captions, and notes the transcription key requirement. It does not explicitly state when not to use it or name competing transcription-like alternatives, but the downstream routing gives strong contextual guidance.

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