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

Beyond the annotations (readOnly=false, openWorld=true, idempotent=false), it discloses that the model is copied into durable storage, that the body survives the source URL expiring, that there is no sign-in requirement, and what the returned view does (idles, lip-syncs via persona_say). That is meaningful behavioral context the annotations do not provide.

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?

It is dense but front-loaded, leading with the core purpose before the persistence and return-view details. Sentences largely earn their place, though the living-body/render description runs slightly long.

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 steps in to explain what the caller gets back (an inline living-body view) and how to reuse the persona_id. For a 4-param creation tool, nothing an agent needs to invoke it correctly is 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 description coverage is 100%, so each parameter is already documented. The description adds framing around glb_url (embodying a rigged model, e.g. from forge_avatar) and the persona_id handle, but the voice and source_prompt semantics come from the schema, so this stays at the baseline.

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 states a specific verb and resource ("Turn a generated GLB into a NAMED, persistent agent body: a 'persona'") and clarifies the persistence model. It differentiates from siblings by naming get_agent_persona and persona_say as the consumers of the returned persona_id.

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 a clear trigger condition: "Use this once a rigged model should become a recurring character the assistant speaks through," and routes the agent to later tools. It stops short of stating when NOT to use it (e.g., one-off render vs. persistent body), but the context is strong.

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