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Glama

face_clip

Build or rebuild a facial animation clip on a rigged face for idle, happy, sad, angry, surprised, or talk states. Set duration, intensity, seed, and text/phonemes to shape the motion.

Instructions

(Re)build one face clip on a rigged face: idle | happy | sad | angry | surprised | talk. duration 0 = the clip's default (idle 4 s loop, expressions ~1.8-2 s; talk = the speech + 0.35 s). intensity scales amplitudes, seed drives idle's Poisson saccades/blinks, text/phonemes/wpm feed talk, name renames the animation (e.g. happy_big).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
wpmNo
clipYes
nameNo
seedNo
textNo
spineNo
projectYes
durationNo
phonemesNo
intensityNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.5/5.0
Behavior4/5

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

With zero annotations the description carries the full burden, and it delivers substantial behavioral detail: default durations per clip type, what intensity scales, what seed drives (Poisson saccades/blinks), and that text/phonemes/wpm only affect 'talk'. It does not state what happens to an existing clip on rebuild, nor permission/return behavior, leaving some gaps for a mutation tool.

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?

Four tightly packed lines, front-loaded with purpose followed by parameter semantics, with essentially no filler. Jargon like 'Poisson saccades' is terse but still informative, keeping it efficient rather than bloated.

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 10-parameter tool with no annotations and no output schema, the description covers the semantically rich parameters but omits project and spine entirely and does not describe overwrite/rebuild consequences. Adequate to invoke the core use case but incomplete for the full parameter surface.

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 description coverage is 0%, so the description must compensate, and it explains most parameters well: duration (with per-clip defaults), intensity, seed, text/phonemes/wpm, and name's rename effect. Only project and spine are left undocumented, so the compensation is strong but not total.

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+resource ('(Re)build one face clip on a rigged face') and enumerates the valid clip values (idle | happy | sad | angry | surprised | talk), which acts as an implicit enum. It does not explicitly contrast itself with neighbors like clip_set or lipsync, so it stops short of full sibling differentiation.

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 explicit when-to-use or when-not-to-use guidance, and no routing to alternatives such as clip_set (multi-clip) or lipsync (speech). Usage is only inferable from the phrase 'on a rigged face' and the clip-type list.

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