PicoBerry MCP Server

animate

Auto-rig existing 3D character assets and apply animation presets, generating a new animated asset asynchronously. Choose a preset to match your engine and get a ready-to-use model.

Instructions

Auto-rig an existing 3D character asset and apply an animation, producing a NEW asset (async). Pick preset from list_animation_presets for the SAME engine. Costs credits — see list_models(category='animate'). wait_for_asset → files.model.

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": {
      "asset_id": "<asset_id>"
    },
    "name": "animate"
  }
}

Input Schema

Name	Required	Description	Default
`engine`	No
`preset`	No
`asset_id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 14, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Despite no annotations, the description discloses key behaviors: async nature ('async'), that it produces a new asset (non-destructive), costs credits, and that the result is accessible via 'wait_for_asset → files.model'. This adds value by outlining the asynchronous workflow and cost implications.

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?

The description is extremely concise: two sentences delivering core purpose, async nature, preset guidance, cost reference, and post-processing step. Every sentence is necessary and the critical information 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?

Given no annotations and no output schema, the description covers essential context: what the tool does, async behavior, cost, prerequisite actions (list_animation_presets, list_models), and how to retrieve results (wait_for_asset). It is nearly complete for a 3-parameter tool, though it could mention the returned asset's structure more explicitly.

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?

The description adds context to parameters by mentioning 'asset_id' (existing asset), 'engine' (implied by 'SAME engine'), and 'preset' (from list_animation_presets). However, with 0% schema coverage, it does not fully describe each parameter's type, constraints, or optionality. It partially compensates through contextual hints.

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 clearly states the tool's function: 'Auto-rig an existing 3D character asset and apply an animation, producing a NEW asset (async).' It uses a specific verb ('auto-rig and apply') and resource ('existing 3D character asset'), and distinguishes it from sibling tools like 'generate_3d_from_text' and 'remesh' by focusing on animation application.

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 provides important usage guidance: 'Pick `preset` from list_animation_presets for the SAME engine. Costs credits — see list_models(category='animate'). wait_for_asset → files.model.' It tells the user how to obtain the preset, check costs, and what to do after the call. While it lacks explicit 'when not to use', it effectively directs the agent to complementary tools.

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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