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mcp-for-cascadeur

mcp-for-cascadeur

by Rickcy
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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motion_sample

Read-only

Builds a keyframed pose sequence using easing and shortest-arc quaternion SLERP, then returns an application plan for pose_apply_sequence without making native edits.

Instructions

Build a pose sequence using easing and shortest-arc quaternion SLERP. Returns a plan without native edits; feed suitable batches to pose_apply_sequence.

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": "motion_sample"
  }
}

Input Schema

NameRequiredDescriptionDefault
stepNo
easingNo
keyframesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.7/5.0
Behavior4/5

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

The annotations already declare readOnlyHint=true and destructiveHint=false, and the description reinforces this with 'Returns a plan without native edits', telling the agent nothing is committed to the scene. It stops short of describing what the plan looks like or how large batches should be split, which would have been genuinely additive.

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 tight sentences, mechanism front-loaded and the follow-up action placed last. No filler or restated field names.

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?

With no output schema and a deeply nested, undocumented input object, the description should explain more about the returned plan and the step parameter. Naming the downstream consumer is helpful, but an agent still has to infer what a 'plan' contains and how batches are sized.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must carry parameter meaning, and it only partially does: mentioning easing and SLERP hints at how interpolation between keyframes works. It says nothing about 'step' (apparently a sampling interval, 1-10000), the meaning of the four easing enum values, or the expected structure of a keyframe's poses array.

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 ('Build a pose sequence') plus the interpolation technique (easing, shortest-arc quaternion SLERP). An agent can distinguish it from pose_apply_sequence, but the term 'plan' is never defined, leaving the artifact itself slightly opaque.

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?

Explicitly routes the agent downstream: 'feed suitable batches to pose_apply_sequence', which clarifies that this tool is a pre-computation step in a two-stage workflow. It gives no exclusions, though, such as when to use transforms_animate or tracks_set_keys instead for native keyframing.

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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