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Blender Production MCP

Blender Production MCP

by DiegoArias32

production.rig_classify

Read-onlyIdempotent

Classify limb-level IK/FK, switches, and deform/control rigs from an object name to support rig validation and production workflows. Unknown classifications are valid.

Instructions

Classify limb-level IK/FK, switches, deform/control rigs; unknown is valid.

Input Schema

NameRequiredDescriptionDefault
optionsNo
object_nameYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.9.0

TDQS

C2.6/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so safety is covered. The phrase 'unknown is valid' usefully warns that classification can return an indeterminate result rather than erroring, which is real added value, but nothing is said about scope (whole armature vs. selected bone), cost, or failure modes.

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?

A single compact clause with no filler and the domain is front-loaded, so there is no bloat. However, brevity here shades into under-specification: the fragment has no verb-object for what is returned and reads more like a tag list than a usable instruction.

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 need not be described. That said, a classification tool with an opaque options object and an ambiguous target parameter leaves the agent unable to determine what to pass or what granularity of result to expect.

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 neither parameter is referenced: object_name is undocumented (is it a bone, an armature, an object?) and the free-form 'options' bag is entirely opaque in both schema and description. For a tool with an untyped options object, the description needed to explain what can go in it.

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

Purpose3/5

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

Names the action (classify) and the domain (limb-level IK/FK, switches, deform/control rigs), so the general intent is inferrable. But it never states what the classification produces or how it differs from near-siblings like rig_analyze_limbs or rig_map_semantics, leaving an agent to guess at the boundary.

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?

No when-to-use, when-not-to-use, or alternative is mentioned despite several overlapping rig-inspection siblings. The only guidance-like statement, 'unknown is valid', addresses result interpretation rather than tool selection.

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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