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Nirlepb

3D CAD BasePlate Generator MCP

by Nirlepb

repair_mesh

Repair 3D meshes to make them manifold, watertight, and print-ready. Removes non-manifold edges, fills holes, unifies face normals, and optionally remeshes for clean topology.

Instructions

Repair a 3D mesh (from Meshy image-to-3D or local CadQuery CAD) to make it manifold, watertight, and print-ready. Removes non-manifold edges/vertices, fills holes, unifies face normals, and optionally remeshes for clean topology. Accepts a URL (e.g. from generate_visual_mesh) or a raw base64-encoded mesh. Returns the repaired STL (or chosen format) as base64 plus a repair summary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNopublicly accessible URL of the mesh to repair (e.g. from generate_visual_mesh)
stlBase64Noraw mesh file (STL/OBJ/PLY) encoded as base64, for locally-generated meshes
inputFormatNofile format of the incoming mesh; used when writing the temp input filestl
repairLevelNohow extensively to repair the mesh; see field description for detailsstandard
outputFormatNoformat for the repaired output meshstl
targetFaceCountNotarget face count for remeshing pass (aggressive only); 0 = skip remesh
holeSizeThresholdNomax hole perimeter in faces to auto-fill; ignored for repairLevel conservative
Behavior4/5

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

Details repair actions (removing non-manifold edges, filling holes, unifying normals, remeshing). No annotations exist, so description carries full burden; covers key behaviors but omits potential downsides like quality loss.

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?

Three sentences, front-loaded with main purpose and inputs. Every sentence adds value; no redundancy.

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

Completeness5/5

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

Covers all inputs (URL, base64, format), operations, outputs (STL/base64 + summary). No output schema, but description sufficiently explains return value. Complete for a repair tool with 7 params.

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 coverage is 100%, so baseline 3. Description adds minimal extra semantics beyond schema; e.g., repairLevel options deferred to field description. Adequate but not enhanced.

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?

Clearly states repairing 3D meshes to be manifold/watertight/print-ready, with specific operations listed. Distinguishes from sibling tools (generate, fill) by focusing on repair.

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?

Describes when to use (e.g., from generate_visual_mesh or local CadQuery). Does not explicitly exclude other tools or state when not to use, but context implies repair for flawed meshes.

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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