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blend-ai

by HoldMyBeer-gg
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mark_seam

Mark or clear UV seams on a mesh's edges to define where it is cut during UV unwrapping, with options for all edges or only selected ones.

Instructions

Mark or clear UV seams on all edges of a mesh.

UV seams guide the UV unwrapping process. Edges marked as seams define where the mesh is "cut" when unwrapped to 2D.

Args: object_name: Name of the mesh object. clear: If True, clear seams instead of marking them.

selection: "ALL" to act on the whole mesh, or "CURRENT" to act only
    on what is already selected. Use the select_* tools to choose
    first. Defaults to "ALL".

Returns: Confirmation dict.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
clearNo
selectionNoALL
object_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.7.0
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / selection
      Added value: +{
+  "default": "ALL",
+  "enum": [
+    "ALL",
+    "CURRENT"
+  ],
+  "title": "Selection",
+  "type": "string"
+}
  2. Addedv1.2.2

TDQS

A4/5.0
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 behavioral burden. It explains what seams do and how clear/selection behave, but omits prerequisites such as required mode/selection state, whether changes are reversible, and whether marking affects existing seams.

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?

The text is front-loaded with purpose and organized into Args/Returns, but the 'Returns: Confirmation dict' line is redundant because an output schema exists, and the opening 'all edges' phrasing sits awkwardly with the scoped selection parameter.

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. The description covers all parameters and selection semantics, but for a no-annotation mesh mutation it leaves mode/prerequisite details unstated, so it is adequate but not fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description documents all three parameters with semantics: object_name identifies the mesh, clear reverses marking, and selection has ALL/CURRENT meanings plus guidance to use select_* first. This fully compensates for the schema gap.

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 action (mark/clear UV seams) and resource (mesh edges) and explains the effect on UV unwrapping. It does not explicitly distinguish this tool from siblings such as mark_sharp, so it is clear but not fully sibling-differentiated.

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?

It clearly tells the agent to use select_* tools first for the CURRENT option and explains ALL vs CURRENT and clear behavior. It does not name alternative UV tools or when not to use this tool, keeping it below explicit when/when-not/alternatives.

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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