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

Annotations only declare readOnlyHint=false and destructiveHint=false; the description goes far beyond by disclosing background-job semantics (immediate job_id, poll lab_get_job), failure modes (422 solo/dialog muted/no speech, 409 concurrent edit with 'nothing was overwritten'), idempotent dedup behavior returning an existing job_id, and 'costs nothing'. This is exactly the extra context annotations cannot convey.

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 front-loaded with the render behavior before branching into job mechanics, and every clause is substantive. It is dense and heavily em-dash dependent, which slightly reduces scannability, but no sentence is 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?

With no output schema, the description must explain return values, which it does precisely: job.result holds the mixdown, measured loudness and the auto-mix report, plus per-decision sentences and missed loudness bounds. Error statuses and the required polling tool are all covered, so an agent has everything needed to invoke and follow up.

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 schema already carries the baseline. The description still adds meaning: 'broadcast (EBU R128)' explains the target enum, and the preset semantics ('spielfilm: music clearly under the dialog; doku_vo: the narrator leads') clarify what each auto_preset value actually does, which the schema's terse 'Run the auto-mix with this preset' does not.

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 names a specific verb and resource ('Render the sequence's mixdown, normalised to a loudness target') and clarifies the two distinct modes: a plain loudness-normalised render versus the AUTO-MIX path triggered by auto_preset. An agent can distinguish it from siblings like lab_mix and lab_mix_messen without opening a schema.

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?

It gives clear operational context — when to expect the auto-mix branch, and the explicit follow-up chain ('Next: lab_get_job, then lab_mix_messen'). It does not, however, state when to prefer lab_mix or another render sibling over this one, or any conditions for exclusion, so guidance is strong but lacks explicit alternatives.

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