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

Goes well beyond the annotations by disclosing hard account limits (3 cloned voices, 5 enrollments/day) and sample limits (10 MB, wav/mp3/m4a, 10–30s single-speaker). Critically, it explains the async contract — returns status 'enrolling' and there is no job to poll — which prevents an agent from wrongly reaching for get_job_status.

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?

Front-loads the verb and resource, then constraints, then the follow-up workflow — a logical order with no filler. It is dense and stacks several parentheticals into one paragraph, which slightly hurts scanability, but essentially every clause carries actionable information.

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 mutating, rate-limited, async tool with an output schema, the description covers prerequisites, input constraints, limits, and the post-call polling path. Return values are partly described anyway (voice_id, status 'enrolling'), leaving nothing an agent needs missing.

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 baseline is 3; the description earns a 4 by adding acceptance constraints the schema does not state, notably the 10–30 second duration window and single-speaker cleanliness, which determine whether enrollment succeeds. The oneOf XOR is restated rather than added, but the format and size guidance is genuinely new.

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 specific verb and resource ('Enroll a custom cloned voice from an audio sample') plus the async nature in the first clause. It is unmistakable against siblings like list_voices and text_to_speech, which are named only as downstream consumers.

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 states the gating conditions (Pro or active 7-day pass key), the input requirement (exactly one of audio_base64 or audio_url), and the full workflow after enrollment (poll list_voices, then use in text_to_speech, create_podcast, or the REST endpoint). It effectively tells the agent when this tool applies and what to do next.

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