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genart-dev

genart-mcp

by genart-dev

design_trace_to_layers

Analyze an image and generate layered trace references—edges, contours, regions, and value maps—from selected trace types for use in generative art workflows.

Instructions

Run full image analysis and create multiple trace layers (edges, contours, regions, values). Combines multiple trace types into a layered reference structure.

Input Schema

NameRequiredDescriptionDefault
kNoColor clusters for regions (default: 5).
typesNoTrace types to generate (default: all).
sourceIdNoReference image asset ID (default: current canvas).
valueLevelsNoValue quantization levels (default: 5).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. It says layers are created but not whether they're added to the current document, whether existing trace layers are replaced, how many layers result, or what permissions/state are needed for a mutating batch operation.

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?

Two sentences, front-loaded with the action and immediately followed by the output concept. No filler, though the second sentence largely restates the first.

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 mutating, multi-layer-producing tool with no annotations and no output schema, the definition omits what the resulting layer structure looks like, how layers are named/ordered, and whether prior layers are touched — key facts an agent needs before calling it.

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 k, types, sourceId and valueLevels are already documented with defaults. The description only echoes four of the seven enum values (edges, contours, regions, values) and adds no meaning beyond the schema.

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?

States a specific verb and resource: it runs image analysis and creates multiple trace layers of several types, which implicitly distinguishes it from the single-type siblings like design_trace_edges and design_trace_regions. It never names those siblings, so the distinction is inferable rather than explicit.

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?

The phrase 'combines multiple trace types into a layered reference structure' implies this is the batch/combined option, but it doesn't say when to prefer it over the individual design_trace_* tools or whether it should follow a reference analysis step.

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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