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Blender Production MCP

Blender Production MCP

by DiegoArias32

production.animation_cleanup_fcurves

Propose conservative cleanup of duplicate F-curve keys, then verify dense samples against per-channel tolerances before applying changes.

Instructions

Conservative proposal-first key cleanup on duplicate; verify dense samples against per-channel tolerances.

Input Schema

NameRequiredDescriptionDefault
modeNoanalyze
optionsNo
operationNo
object_nameNo
operation_idNo

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 declare a non-read-only, non-destructive, non-idempotent write. The description adds meaningful context beyond that: "proposal-first" and "conservative" signal that changes are proposed rather than applied immediately, and "per-channel tolerances" hints at a verification gate. It still omits permissions, whether proposals persist, and what the proposal output looks like.

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?

It is a single front-loaded sentence with no filler, but terseness comes at the cost of clarity: "key cleanup on duplicate" is dense and ambiguous rather than genuinely efficient.

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 5-parameter mutation tool with 0% schema coverage and an analyze/apply mode switch, the description is too thin. The output schema exists so return values needn't be covered, but the mode semantics and parameter roles are unexplained, leaving an agent unable to call it confidently.

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 coverage is 0% across 5 parameters, so the description must carry the load, but it never explains mode (default "analyze"), options, operation, object_name, or operation_id. Only a vague nod to "per-channel tolerances" might map to options, leaving four parameters undocumented anywhere.

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?

The description names an action ("key cleanup on duplicate") but "duplicate" is ambiguous and it never states it operates on F-curves directly, relying on the tool name. It is not clearly distinguishable from siblings like animation_polish_curves, animation_repair_bezier, or animation_analyze_fcurves.

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?

"Conservative proposal-first" implies this proposes rather than applies changes, but there is no explicit when-to-use vs when-not-to-use guidance and no named alternative among the many curve-editing siblings.

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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