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rig_3d_model

Add a skeleton to a 3D model so it can be animated: a humanoid, a four-legged animal, or a prop's moving parts (a chest lid, a door, a tree's trunk). Run before animate_3d_model. 30 credits.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "rig_3d_model"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYes3D model asset ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare a non-read-only, non-idempotent, non-destructive, closed-world mutation, so the safety profile is covered. The description adds genuinely useful context beyond that: a concrete cost of '30 credits' and the fact that this is a prerequisite stage in the animation pipeline. It could go further by noting that re-running on an already-rigged model may replace or stack a rig (relevant since idempotentHint=false means repeat calls cost credits again).

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

Conciseness5/5

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

Two sentences, zero filler: capability and scope first, then the ordering constraint, then the cost. Each sentence carries distinct decision-relevant information and the most important framing is front-loaded.

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 one-parameter mutation with full schema coverage, annotations, and no output schema, the description covers purpose, pipeline position, and cost. The main remaining gap is the return/effect model — whether the input asset is modified in place and how the agent learns the rig succeeded — which matters given no output schema exists.

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?

There is a single parameter and the schema description coverage is 100%, so the 'id' field is already fully documented as a 3D model asset ID. The description adds no meaning about the parameter — no note on where the ID comes from (e.g., list_assets or generate_3d_model) or what to expect if the asset is not a 3D model. Baseline 3 applies when the schema does the heavy lifting.

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 gives a specific verb and resource ('Add a skeleton to a 3D model') and immediately bounds the scope with three concrete rig categories (humanoid, four-legged animal, prop moving parts such as a chest lid or door). This clearly separates it from siblings like animate_3d_model or generate_3d_model, so an agent can pick it without opening the schema.

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?

It states an explicit pipeline prerequisite: 'Run before animate_3d_model,' naming the sibling and the ordering constraint. It does not state when not to use it (e.g., models that already have a rig, or rigging a sprite), so it stops short of full when/when-not/alternatives coverage.

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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