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Blender Production MCP

Blender Production MCP

by DiegoArias32

production.animation_refine_generated

Refines generated animation on a compatible body rig by planning changes first, validating mapping and QA, and applying updates only when explicitly enabled.

Instructions

animation_refine_generated: high-level M6 unit. Plan first, apply=false by default; generation is the immutable plan.json reference. Explicit mapping and compatible body rig required. Source Actions retained; technical QA and temporal artistic review are distinct. options carries declared stage parameters, thresholds or visual review; unsupported adapters return concrete errors.

Input Schema

NameRequiredDescriptionDefault
applyNo
briefNo
intentNo
optionsNo
generationNo
object_nameNo
operation_idNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.9.0

TDQS

C2.7/5.0
Behavior4/5

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

Beyond the annotations, the description discloses that apply defaults to false, that the generation reference is immutable, that source Actions are retained, and that unsupported adapters return concrete errors. These are useful behavioral details that help an agent understand mutation scope and failure modes, though the phrasing is dense.

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?

The description is a single compact paragraph and does front-load the plan-first default, but 'high-level M6 unit' and several dense clauses are jargon that reduce clarity. It is not bloated, but structure and phrasing could be much cleaner.

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?

For a seven-parameter mutation tool with many overlapping animation siblings, the description does not establish clear purpose or when-to-use routing, and it documents only a minority of the parameters. The presence of an output schema removes return-value burden, but the input-side context remains insufficient.

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% for seven parameters. The description clarifies apply, generation, and options somewhat, but leaves brief, intent, object_name, and operation_id completely unexplained, so most parameters remain opaque to an agent.

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 opens with the tool name followed by opaque internal jargon ('high-level M6 unit'), and never plainly states that it refines a generated animation. 'Plan first, apply=false by default' hints at workflow, but there is no clear verb+resource statement to distinguish it from siblings like animation_refinement_plan or animation_refine_arcs.

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

Usage Guidelines3/5

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

It implies a plan-first workflow with 'apply=false by default' and lists prerequisites ('Explicit mapping and compatible body rig required'), which gives some usage context. However, it never names an alternative sibling tool or states when to use this high-level refinement versus more specific refine/accept/generate tools.

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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