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nesso-labs

spaceclaim

by nesso-labs

select_edges

Read-only

Find and filter a body's edges by geometry—curve type, length, radius, face boundary, or direction—to select vertical edges, hole rims, or top-face edges for CAD operations.

Instructions

Find edges by geometry (vertical edges, edges of the top face, Ø8 hole rims ...).

Input Schema

NameRequiredDescriptionDefault
bodyYesBody id or unique name.
radiusNoCircular edges of this radius.
extremeNoOf the matches, keep those furthest along this direction.
on_facesNoOnly edges bounding one of these face ids.
curve_typeNoKeep only this curve type.
max_lengthNo
min_lengthNo
parallel_toNoStraight edges parallel to this axis ("Z" or [x, y, z]).
radius_toleranceNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is covered and the description need not repeat it. It does not disclose whether the call mutates the current selection set or merely returns matching edges, nor whether filters combine as AND or OR — meaningful behavioral gaps for a tool named select_*, given an output schema exists to cover return shape.

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?

A single parenthetical sentence that front-loads the core purpose and spends its remainder on the highest-value disambiguation. No filler, nothing repeated from annotations or schema.

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 9 parameters, present annotations and an output schema, the description is serviceable but thin: it omits how simultaneous filters interact, whether results replace the active selection, and what body references are accepted. The examples compensate partially but leave an agent guessing on filter composition.

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

Parameters4/5

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

Schema coverage is 67%, and the description's examples map usefully onto specific parameters: "vertical edges" to parallel_to, "edges of the top face" to on_faces, "Ø8 hole rims" to radius. That is genuine semantic grounding beyond the schema text, though max_length, min_length and radius_tolerance remain undocumented in both places.

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 ("Find") and resource ("edges") and pins down the domain with concrete geometric examples (vertical edges, top-face edges, Ø8 hole rims). The resource noun alone separates it from the sibling select_faces, but the description never explicitly names that sibling or the other retrieval 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?

The examples imply the usage context (locating edges for downstream operations like fillet_edges or chamfer_edges), but there is no explicit statement of when to call this versus select_faces, describe_body, or measure_distance. No exclusions or prerequisites are given; an agent must infer the workflow position.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.