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Glama

Scene Plan

scene_plan

Validate Maya scene organization and generate actionable layout plans, detecting orphan meshes, empty groups, spacing issues, and conflicts before detailed modeling.

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.

Boundary: Disambiguated from scene_review (scene_plan focuses on forward-looking layout planning and actionable auto_fix reorganization, whereas scene_review provides an overall diagnostic audit score).

Input 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

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false and destructiveHint=false, carrying the safety profile. The description adds that output is forward-looking planning with 'actionable auto_fix reorganization', but never plainly states that auto_fix mutates the scene or which issues get changed, so it adds only moderate context beyond structured fields.

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?

Front-loads the one-line purpose, then uses a scannable bullet list for capabilities and ends with the sibling boundary. Slightly long but every block serves routing or scoping; no filler sentences.

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?

With an output schema present, return values need not be described, and the description covers purpose, methodology, and boundary disambiguation. Complete enough for a 4-param tool; what's missing is explicit disclosure of the mutation trigger, which the annotations partly cover.

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 the schema already documents all four parameters fully. The description only loosely gestures at 'auto_fix reorganization' and 'natural language objectives', which map to existing parameters without adding format or behavioral detail, so baseline 3 applies.

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

Purpose5/5

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

States a specific verb (planning) and resource (scene), then enumerates the concrete outputs (organization validation, zone analysis, layout suggestions, action plan). It explicitly distinguishes itself from the sibling scene_review, so an agent can route between the two without opening either schema.

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

Usage Guidelines4/5

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

Gives a clear usage context ('validate organization and proportions before committing to detailed modeling') and names the alternative sibling scene_review with the condition that selects each. No explicit when-not-to-use case beyond the boundary statement, so a 4 rather than 5.

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