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Save a rigged model as a living, persistent agent body

create_agent_persona

Turn a generated GLB into a NAMED, persistent agent body: a "persona" the assistant reuses across turns and across sessions. The model is copied into durable storage so the body survives the source URL expiring, then registered under a stable persona_id. The returned view renders the LIVING body inline: it idles between turns, and persona_say makes it lip-sync and emote a reply. The persona_id is the handle: keep it and pass it to get_agent_persona or persona_say later to bring the exact same body back. No sign-in required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesA display name for the persona, 1–80 characters.
voiceNoOptional voice name to speak with (used for audio-driven lip-sync when available).
glb_urlYesPublic https URL of the rigged GLB to embody (e.g. from forge_avatar).
source_promptNoOptional: the prompt that generated this body, kept as provenance.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations only indicate non-read-only, open-world, non-idempotent, and non-destructive behavior. The description adds valuable specifics: durable copying (survives URL expiry), registration, inline rendering with idle animation, lip-sync via persona_say, and 'No sign-in required'. It does not cover failure modes or potential costs, but it goes beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is five sentences, front-loaded with the main action and persistence guarantee. Later sentences explain the living render and persona_id usage. While a bit verbose, each sentence carries useful information, with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a creation tool with no output schema, the description adequately covers the key outcomes: durable storage, persona_id registration, and the living inline view. It implies the id is returned (via 'keep it and pass it'), which is sufficient for an agent. It does not mention potential conflicts or error handling, but for this complexity it is nearly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the parameters are fully documented in the schema. The description does not add substantial parameter-level meaning beyond echoing that glb_url comes from forge_avatar and voice enables lip-sync, which are already in the schema descriptions. The baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a precise verb ('Turn a generated GLB into a NAMED, persistent agent body') and resource, clearly distinguishing this from siblings like get_agent_persona (retrieval) and persona_say (speech). It also explains the lifecycle: copy to durable storage, register under a stable persona_id, and render the living body inline.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context: after generating a rigged GLB (e.g., from forge_avatar), you embody it as a persistent persona. It explains how to reuse it later via get_agent_persona or persona_say, but does not explicitly state exclusions or alternatives for creation (e.g., when not to use this). The context is clear enough.

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

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