Connect ARKit Face Capture

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

Annotations already indicate this is a mutating operation (readOnlyHint=false) and not destructive (destructiveHint=false). The description adds that it creates a scaffold with OSC maps, but does not disclose side effects like network changes or dependencies. This is adequate but not rich.

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 a single, focused sentence that front-loads the verb and essential details. It contains zero filler words and 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?

With 7 parameters, no output schema, and only 29% schema description coverage, the description does not provide enough context about what the scaffold includes, how parameters affect the result, or what the output looks like. It is too sparse for a tool of this complexity.

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 only 29%, so the description must compensate for lack of parameter documentation. It vaguely references 'blendshape and head-transform maps' but does not explain key parameters like face_count, receive_port, active, or name. The description adds little beyond the schema fields.

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 uses a specific verb ('Create') and resource ('ARKit Face Capture OSC scaffold') with concrete details (blendshape and head-transform maps, iPhone-driven). This clearly distinguishes it from siblings like setup_face_tracking, making the purpose unmistakable.

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 phrase 'for iPhone-driven facial performance' implies the intended use case, but there is no explicit statement of when to use this tool versus alternatives, nor any exclusions or prerequisites. Context is clear but guidance is minimal.

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