production.facial_generate_lipsync

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

The description adds substantial behavior beyond annotations: candidates are new Actions evaluated through NLA tracks, the body Action is never modified, facial is an immutable plan.json reference, and apply defaults to false. It also discloses the TIMING_INPUT_REQUIRED failure mode. It does not cover permissions or return details, but the output schema carries return structure.

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 compact and avoids padding, but the wording is dense and jargon-heavy ("M7 facial unit", "Evidence-based semantic mapping (never names only)"). The core action is not front-loaded, making the paragraph harder to parse than its length suggests.

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 complex 7-parameter generation tool with zero schema description coverage, the description leaves most parameters unexplained and gives no sibling comparison. It does cover important safety/workflow behavior, and output details are handled by the output schema, but the parameter gaps are too large for an agent to invoke it confidently without additional inference.

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 description coverage is 0% across 7 parameters, so the description must compensate. It only explains apply (default false) and facial (immutable plan.json reference), while brief, intent, options, object_name, and operation_id remain undocumented.

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 name identifies lipsync generation, but the description itself opens with the opaque phrase "M7 facial unit" and never plainly states that it generates a lipsync animation action. It implies the purpose through "Candidates are new Actions" and the speech/phoneme requirement, but does not distinguish it from nearby siblings such as facial_prepare_speech or facial_map_visemes.

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 useful workflow guidance: "plan first, apply=false by default" and requires explicit timed phonemes/visemes for speech. However, it does not say when to prefer this over related tools like facial_generate, facial_prepare_speech, or facial_map_visemes, so alternative selection remains largely inferred.

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