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genart-dev

genart-mcp

by genart-dev

design_trace_edges

Detect edges in the current canvas or a reference image with Canny edge detection, return edge statistics, and optionally create a trace:reference layer for tracing or analysis.

Instructions

Detect edges in the current canvas or a reference image using Canny edge detection. Returns edge map statistics and optionally creates a trace:reference layer.

Input Schema

NameRequiredDescriptionDefault
sigmaNoGaussian blur sigma (default: 1.4). Higher = smoother edges.
sourceIdNoReference image asset ID to trace (default: current canvas).
createLayerNoCreate a trace:reference layer with the result (default: true).
lowThresholdNoLower hysteresis threshold 0–255 (default: 50).
highThresholdNoUpper hysteresis threshold 0–255 (default: 100).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose the side effect ('optionally creates a trace:reference layer') and that statistics are returned, which is useful. It does not say whether an existing trace:reference layer is replaced, what permissions are needed, or what the statistics contain.

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

Conciseness5/5

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

Two sentences, zero padding, with the action and output front-loaded before the optional side effect. Nothing could be cut without losing information.

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

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description should say more about the returned edge map statistics and the mutation's effect on existing layers. It is adequate to make the call but leaves the agent guessing about the result shape and state changes.

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 all five parameters (sigma, sourceId, createLayer, thresholds) are already documented with defaults and ranges. The description only reinforces the canvas-vs-reference choice and adds no syntax or behavioral detail beyond the schema, so baseline 3 applies.

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 ('Detect edges') plus the algorithm (Canny) and the two input sources (current canvas or reference image). It does not distinguish itself from the many sibling trace tools (design_trace_contours, design_trace_lines, design_trace_shapes, etc.), so an agent still has to infer which tracer to pick.

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?

Usage is only implied: sourceId defaults to the current canvas, so the reference-image case is hinted at. There is no explicit statement of when to prefer this over design_trace_contours or the other trace siblings, and no prerequisites.

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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