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build123d-mcp

build123d-mcp

by pzfreo
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

repair_hints

Read-only

Turn a build123d error message into targeted fix suggestions for common modeling mistakes, gate failures, and B-rep defects.

Instructions

Given an error message or validity-gate reason, return targeted fix suggestions for common build123d mistakes and gate failures: wrong Location syntax, missing .part, CadQuery idioms, blocked imports, degenerate boolean results, fillet edge selection, B-rep defects, mesh non-manifold/open-edge failures, and more. Pass the full error string from execute(), last_error(), validate(), or export().

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "error_text": "<error_text>"
    },
    "name": "repair_hints"
  }
}

Input Schema

NameRequiredDescriptionDefault
error_textYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.19
  2. Removedv0.3.17
  3. First observedv0.3.10

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, confirming safe read-only behavior. The description goes beyond by detailing the types of errors covered (wrong Location syntax, missing .part, etc.) and recommended sources, adding meaningful behavioral context without contradicting annotations.

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 concise sentences with no redundant information. The first sentence front-loads the purpose and scope, while the second provides usage guidance. Every sentence is necessary and earns its place.

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?

Given the tool's simplicity (one parameter, read-only, with an output schema), the description sufficiently covers how and when to use it. It mentions return type implicitly ('return targeted fix suggestions'), and the output schema handles return value details.

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?

With 0% schema description coverage, the description compensates by identifying the sole parameter (error_text) as an error string and specifying its origin. It adds value beyond the schema's title, though it could include more format or length constraints.

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 clearly states the tool's purpose: to return targeted fix suggestions for common build123d mistakes given an error message. It specifies the verb 'return' and the resource 'fix suggestions', and lists specific error categories, distinguishing it from siblings like repair_advice or workflow_hints.

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?

The description explicitly tells the user to pass the full error string from specific sources (execute(), last_error(), validate(), or export()), providing clear context for when to use the tool. However, it does not mention when not to use it or specify alternatives among sibling tools.

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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