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genart-dev

genart-mcp

by genart-dev

design_add_figure_landmarks

Add anatomical landmark annotations to a figure by supplying keypoints directly or copying them from a mannequin layer, with optional labels and landmark sets.

Instructions

Add anatomical landmark annotations. Provide keypoints directly or reference a mannequin layer.

Input Schema

NameRequiredDescriptionDefault
keypointsNoKeypoints as Record<string, {x,y}>.
showLabelsNoShow labels (default: true).
landmarkSetNoLandmark set (default: 'essential').
mannequinLayerIdNoID of an existing mannequin layer to copy keypoints from.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the behavioral burden. It implies a mutation through 'Add' but does not disclose whether existing landmarks are replaced or appended, whether at least one input source is required, what permissions or side effects exist, or what the tool returns.

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?

The description is two sentences, front-loads the purpose, and then states the input approach. There is no filler, and every sentence contributes directly to understanding what the tool does.

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?

The tool mutates annotation state, has no annotations, no output schema, and four optional parameters including a nested keypoints object. The description leaves important behavioral questions unanswered, such as whether one of keypoints or mannequinLayerId is required, whether landmarks accumulate or replace existing ones, and how landmarkSet interacts with supplied inputs.

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 keypoints, showLabels, landmarkSet, and mannequinLayerId. The description's 'provide keypoints directly or reference a mannequin layer' restates the schema's two input paths without adding format, precedence, or constraint details beyond it.

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 and resource: 'Add anatomical landmark annotations.' This is clearly distinct from siblings that create mannequins, pose skeletons, or gesture lines, but it does not explicitly name alternatives or clarify how it differs from pose annotation tools.

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 gives two input modes: provide keypoints directly or reference a mannequin layer. However, it does not say when this tool should be preferred over siblings like design_annotate_pose or design_set_pose_keypoints, nor does it state exclusions or 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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