production.facial_analyze_jaw

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

Annotations mark this as a non-readonly, non-destructive, idempotent operation. The description adds useful behavioral context: apply defaults to false, the body Action is never modified, candidates are new Actions on NLA tracks, and speech requires explicit timed phonemes/visemes. These details go beyond the annotations and clarify the mutation scope, though some phrasing is cryptic.

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 but dense with jargon and lacks front-loading; it opens with a cryptic label rather than a plain statement of intent. It avoids redundancy, but the structure could be clearer for an agent scanning for 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?

Given six undocumented parameters, no schema descriptions, and an output schema, the description should do more to explain how to invoke the tool correctly. It covers some behavioral constraints but omits parameter meaning and the nature of the analysis, leaving key gaps.

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% and the description explains only the apply parameter (default false) and vaguely gestures at facial as an immutable plan.json reference. It does not explain brief, intent, options, or object_name, leaving most of the six parameters without semantic guidance.

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 restates the tool name but never clearly defines what 'analyze jaw' means. It adds jargon like 'M7 facial unit' and 'Evidence-based semantic mapping' without stating the specific resource or analysis being performed, and it does not differentiate from siblings like facial_analyze_lips or facial_generate_jaw.

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?

The only workflow hint is 'plan first, apply=false by default' and a note that 'Technical QA and artistic review stay separate.' There is no explicit guidance on when to choose this tool over the many facial_analyze_* or facial_generate_* alternatives.

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