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mcp-for-cascadeur

mcp-for-cascadeur

by Rickcy
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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semantic_pose_apply_sequence

Destructive

Applies up to eight partial semantic poses or up to 64 complete rigid-control poses to existing Cascadeur frames, with geometry verification and checkpoint recovery.

Instructions

Apply 1-8 partial semantic poses or explicitly sampled_motion=true 1-64 complete rigid-control poses. Existing frames only; verified native geometry and full checkpoint recovery.

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": {
      "keyframes": "<keyframes>"
    },
    "name": "semantic_pose_apply_sequence"
  }
}

Input Schema

NameRequiredDescriptionDefault
characterNo
keyframesYes
sampled_motionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare destructive=true and readOnly=false, so the safety profile is covered. The description adds meaningful behavior beyond annotations: it modifies existing frames only, verifies native geometry, and provides full checkpoint recovery, which is important context for a destructive pose operation.

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 compact and front-loaded, with no filler sentences. Some phrases such as 'verified native geometry' are dense and slightly opaque, but overall it communicates constraints efficiently.

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

Completeness3/5

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

For a destructive pose-application tool with no output schema and 0% parameter coverage, the description covers critical mode limits, existing-frame restriction, and checkpoint recovery. It remains incomplete on character scoping, keyframe object format, and what the operation returns.

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 0%, so the description must compensate. It usefully explains sampled_motion semantics and keyframe count limits, but it omits the character parameter and does not describe the structure of individual keyframe pose entries.

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

Purpose4/5

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

States a specific verb and resource: applying a sequence of semantic or rigid-control poses. It distinguishes sequence behavior through the 1-8 versus 1-64 mode limits, but does not explicitly name alternatives such as semantic_pose_apply or pose_apply_sequence.

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

Usage Guidelines3/5

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

Gives useful mode-selection constraints: 1-8 partial semantic poses normally, or 1-64 complete rigid-control poses when sampled_motion=true, and only for existing frames. However, it does not explicitly say when to use this sequence tool versus single-pose or sibling sequence 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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