Skip to main content
Glama

qa_character

Detect joint cracks, foot slide, and mobile bone-budget violations in Spine character animations, then return per-joint and per-clip fixes.

Instructions

Character QA played in spine-core: joint cracks (where two parts' art separates at a bending joint, or a single mesh folds), foot slide (a planted foot drifting from the clip's ground speed) and the mobile bone budget for the rig type (biped, quadruped, flier, serpent, face; auto detects) plus mobile_character. Returns fix: what to change, joint by joint and clip by clip.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fpsNo
projectYes
rig_typeNoauto
animationsNo
crack_thresholdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

C2.8/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose the checks performed, the auto-detection of rig type, and the shape of the result ('Returns fix: what to change, joint by joint and clip by clip'), but never states whether the tool mutates anything, permissions needed, or cost/runtime behavior for a diagnostic over potentially many clips.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded, but the single run-on sentence packs parenthetical definitions and the cryptic fragment 'plus mobile_character' that adds noise rather than clarity. Readable but not tight.

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

Completeness2/5

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

A 5-parameter tool with zero schema coverage, no annotations, and no output schema needs a fuller description. It explains the return field but omits fps/crack_threshold semantics, scope of the scan, and any safety or side-effect information an agent needs to invoke it correctly.

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 compensate, and it only partially does. It clarifies rig_type (listing biped/quadruped/flier/serpent/face and 'auto detects') and implies animations ('clip by clip'), but says nothing about fps or crack_threshold, leaving two of five parameters undocumented.

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 (QA) and resource (character) and enumerates the concrete checks: joint cracks, foot slide, and mobile bone budget. However, it never distinguishes itself from the sibling qa_budget, which appears to overlap with the bone-budget portion of this tool, leaving ambiguity about which QA tool to pick.

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 statement of when to run this versus alternatives like qa_budget or validate, nor any prerequisite context (does it require a completed rig? a spine-core project?). The inline definitions explain what it detects, not when an agent should choose it.

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