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ttiimmaacc

mcp-for-clo3d

by ttiimmaacc

sew_edges

Joins two pattern outline edges by specifying matching endpoints, automatically aligning stitch directions to prevent twisted seams in CLO3D.

Instructions

Sew two outline edges by saying which points meet: from_a meets from_b and to_a meets to_b. The lines are found by their endpoints (2D pattern coordinates, mm, within 2 mm) and the stitch directions follow, so the seam cannot come out twisted (with sew_lines the direction flags are easy to get backwards).

Args: pattern_a: Piece of side A. from_a: One end of the edge on A, e.g. the neck point [x, y]. to_a: The other end on A, e.g. the shoulder point. pattern_b: Piece of side B. from_b: The point on B that meets from_a. to_b: The point on B that meets to_a.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
to_aYes
to_bYes
from_aYes
from_bYes
pattern_aYes
pattern_bYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.1

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden. It discloses important behavior: lines are found by endpoints using 2D pattern coordinates in mm within a 2 mm tolerance, and stitch directions are derived so the seam cannot twist. It does not explicitly state whether the operation is destructive, reversible, or requires existing pattern IDs, but the core mechanics are well explained.

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 front-loaded with the core purpose and mechanism, followed by a compact Args section. Every sentence earns its place, including the parenthetical contrast with sew_lines, and there is no redundant filler.

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?

For a six-parameter mutation tool with no annotations and no output schema, the description covers purpose, mechanism, parameter meanings, and an alternative. It could still mention side effects or whether the operation is undoable, but it is largely complete for correct invocation.

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%, and the description compensates fully by documenting all six parameters. It explains what each point represents, gives examples ('neck point [x, y]', 'shoulder point'), clarifies coordinate format and tolerance, and maps from_b/to_b to their counterparts on side A.

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?

The description states a specific verb and resource ('Sew two outline edges') and explains the exact mechanism: matching endpoints so from_a meets from_b and to_a meets to_b. It also distinguishes itself from the sibling sew_lines by noting that stitch direction follows automatically and avoids twisted seams.

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 gives a clear reason to choose this tool over sew_lines ('the seam cannot come out twisted') and names the alternative explicitly. However, it does not state explicit when-not conditions or a full decision rule for using sew_lines instead.

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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