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Glama

Scene Plan

scene_plan

Validate Maya scene organization and optimize layout by detecting orphans, empty groups, overlaps, and conflicts, then generate a prioritized action plan.

Instructions

Holistic scene planning with organization validation and layout optimization.

Performs comprehensive scene health check and generates actionable plans:

  • Organization validation: detects orphan meshes, empty groups, default names

  • Zone analysis: coverage and spatial balance across functional zones

  • Layout suggestions: spacing, overlap, and clustering detection

  • Conflict prevention: near-miss collision prediction

  • Action plan: prioritized step-by-step execution guide

Based on blockout-first methodology: validate organization and proportions before committing to detailed modeling. Supports natural language objectives.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoOutput format - "json" (default) or "cos".json
auto_fixNoIf True, auto-fix safe issues (remove empty groups, reparent orphans).
objectiveNoNatural language goal description. e.g., "set up entrance area with display window and clear circulation"
session_keyNoMaya session key.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

A3.5/5.0
Behavior3/5

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

Annotations declare readOnlyHint=false, destructiveHint=false, and idempotentHint=false. The description frames the tool as analysis/planning, which aligns with the non-destructive hint, and it details the scope of what gets checked. It doesn't disclose that the auto_fix parameter can mutate the scene, leaving a gap the annotations don't fully cover.

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

Conciseness4/5

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

The opening sentence is front-loaded and the bullet list is scannable, with each bullet earning its place by naming a distinct capability. Slightly verbose, but the structure pays for the length.

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

Completeness4/5

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 explained, and the description thoroughly covers what the tool analyzes and produces. The only real gap is the absence of routing guidance relative to the many sibling scene tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so parameters (format, auto_fix, objective, session_key) are fully documented in the schema, setting the baseline at 3. The description only loosely echoes the objective parameter with 'Supports natural language objectives' and adds no new syntax or format detail.

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?

The description states a specific verb+resource ('scene planning') and enumerates concrete capabilities (organization validation, zone analysis, layout suggestions, conflict prevention, action plan). This distinguishes it from siblings like scene_validate and scene_inspect, though it doesn't explicitly name which sibling to prefer.

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 offers implied guidance via 'blockout-first methodology' and 'before committing to detailed modeling,' giving a sense of when in the workflow to use it. However, it never states when to choose this over scene_validate, scene_review, or scene_aesthetics, nor any exclusions.

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