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Blender Production MCP

Blender Production MCP

by DiegoArias32

production.animation_detect_limb_pops

Idempotent

Detect limb pops in Blender animations by analyzing upper/lower/effector chains and angle, velocity, acceleration, and extension events.

Instructions

Explicit upper/lower/effector chains; contextual angle/velocity/acceleration/extension events.

Input Schema

NameRequiredDescriptionDefault
optionsNo
object_nameYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.9.0

TDQS

C2/5.0
Behavior2/5

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

Annotations declare readOnlyHint=false, idempotentHint=true and destructiveHint=false, so the description should explain what this non-read-only operation actually does or writes — it says nothing about side effects, permissions, or outputs. The phrase about 'contextual events' hints at computed results but discloses no behavioral trait.

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

Conciseness2/5

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

It is short, but the brevity comes from under-specification rather than economy: a single semicolon-joined fragment with no lead sentence stating the action. Nothing is front-loaded because there is no complete statement to front-load.

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?

An output schema exists, so return values needn't be described, but for a detection tool with a free-form options bag and dozens of sibling analyzers, the definition leaves the agent without enough to decide or configure the call. It is materially incomplete for the tool's complexity.

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% and 'options' is an untyped anyOf object, so the description must carry the burden. It hints at chain types and event types (angle/velocity/acceleration/extension) that presumably map to option keys, but it never documents them explicitly and says nothing at all about the required object_name.

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

Purpose2/5

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

The description is a noun-phrase fragment ('explicit upper/lower/effector chains; contextual angle/velocity/acceleration/extension events') with no verb, so it never states that the tool detects limb pops. It only vaguely gestures at the analysis dimensions, leaving the actual operation to be inferred from the tool name.

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 indication of when to run this, what input state it requires, or how it differs from near-identical siblings such as animation_detect_limb_stretch, animation_analyze_effector_contact, or animation_analyze_fcurves. The agent must guess from the name alone.

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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