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MPfeifer33

Ensemble MCP

by MPfeifer33

riff_generate_motion

Generate motion design tokens: durations, cubic-bezier easing, and transition presets for animation styles like minimal or fluid.

Instructions

Generate a motion system: durations, easing curves (cubic-bezier) and ready-made transition presets.

animation_style: none (reduced motion), minimal (the default), fluid (smooth, longer), energetic (snappy, springy).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
colorNoBrand color in hex. Optional here; defaults to #3B82F6.
colorsNoAdditional brand colors in hex (up to 5 colors in total, including `color`).
preferencesNoOther design preferences, so tools called separately stay consistent with each other. Pass the same values to every tool.
animation_styleNoThe character of the motion (default minimal)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden and does not meet it. It never says whether this is a pure generation call, what the returned tokens look like, whether anything is written or persisted, or how the result interacts with the separately generated theme.

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?

Two short lines, front-loaded with the deliverable and with zero filler. The second line is spent entirely on one parameter's values while the other four go unmentioned, which is a reasonable but slightly lopsided allocation.

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 four-parameter, all-optional generation tool with no annotations and no output schema, the description covers purpose and one enum well but omits the nature of the return value and any consistency contract beyond the schema's note about passing the same preferences to every tool.

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

Parameters4/5

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

Schema coverage is 100%, so the 3 baseline applies; the description exceeds it by explaining each animation_style value qualitatively — none as reduced motion, fluid as smooth/longer, energetic as snappy/springy — which the schema only labels as 'Motion character'. It stops short of explaining how animation_style differs from preferences.animation_style, which is left to inference.

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 — generate a motion system — and enumerates the concrete artifacts produced (durations, cubic-bezier easing curves, transition presets). The motion/animation domain is clearly distinct from the sibling resources (palette, fonts, scale, shadows, grid), though the description never names an alternative explicitly.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance, no prerequisites, and no routing to alternatives such as bridge_generate_theme or compose_export. The description only enumerates option values, which is parameter information rather than usage context.

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