Skip to main content
Glama

Scene Aesthetics

scene_aesthetics
Read-onlyIdempotent

Analyze a Maya scene's visual design across color, composition, proportion, lighting, and flow; get an overall score, grade, and actionable improvement suggestions.

Instructions

Professional-grade aesthetic analysis with 5 design dimensions.

Analyzes scene aesthetics across 5 professional design dimensions:

  1. Color Theory: 60-30-10 rule, temperature balance, harmony type, saturation variety, contrast

  2. Spatial Composition: golden ratio proportions, rule-of-thirds alignment, visual weight balance

  3. Proportion & Scale: human ergonomic reference, size hierarchy (hero/secondary/tertiary)

  4. Lighting Quality: layer composition (key/fill/rim/accent), color temperature consistency

  5. Visual Flow: sight line clarity, circulation paths, visual rhythm patterns

Returns an overall score (0-100) with grade (S/A/B/C/D/F) and improvement suggestions.

Boundary: Disambiguated from scene_review (scene_aesthetics evaluates visual design theory and artistic harmony in depth, while scene_review is a broad multi-system scene health audit).

Input Schema

NameRequiredDescriptionDefault
formatNoOutput format - "json" (default) or "cos" (chain-of-symbol, token-efficient).json
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, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds the output shape (0-100 score, letter grade, improvement suggestions), but no session/auth requirements, latency, or failure behavior, and the return detail is largely redundant given an output schema exists.

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 purpose, then uses a scannable numbered list for the five dimensions, closing with return info and the boundary rule. The dimension detail is somewhat verbose for tool selection but earns its place by conveying analysis depth; 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?

An output schema exists, so return values needn't be explained again, and the description still summarizes the scoring model. Combined with annotations covering safety and a fully described two-param schema, the definition is essentially complete, missing only minor context like prerequisites or session handling.

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 both parameters (format, session_key) are already documented in the schema. The description adds nothing about the format enum or session_key semantics, so the baseline 3 for fully-covered schemas 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 and resource ('Analyzes scene aesthetics across 5 professional design dimensions') and enumerates exactly what those dimensions are. The Boundary section explicitly disambiguates it from scene_review, so an agent can distinguish it from siblings without opening a 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?

The Boundary statement gives an explicit routing rule: use scene_aesthetics for deep visual design theory/artistic harmony, scene_review for a broad multi-system health audit. That is clear alternative-selection guidance, though it stops short of stating trigger conditions like 'call this after placing assets' or prerequisites.

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