formlabs-local-mcp

detect_minima

Read-only

Count unsupported local minima per model to identify points that would print in mid-air, helping you detect print failures before slicing.

Instructions

Count unsupported local minima per model (points that would print in mid-air).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "detect_minima"
  }
}

Input Schema

Name	Required	Description	Default
`scene_id`	No	Scene id; omit for the default scene	default

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.4Sep 16, 2026

TDQS

A3.5/5.0

Behavior3/5

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

Annotations already declare this as read-only and non-destructive. The description adds useful domain context by defining unsupported local minima as points that would print in mid-air, but it does not disclose additional behavioral details such as output format or error conditions.

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 one focused sentence that front-loads the main action and uses the parenthetical only to clarify the key term. There is no redundant or filler wording.

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?

For a simple read-only tool with one optional schema-documented parameter and no output schema, the description is complete: it states what is counted, defines the concept, and the annotations cover safety. Nothing essential is missing for an agent to invoke it correctly.

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?

The single parameter scene_id is fully documented in the schema with a default value and description, so schema coverage is 100%. The tool description adds no parameter-specific meaning beyond the schema, matching the baseline.

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 names a specific action ('Count') and resource ('unsupported local minima per model'), and the parenthetical clarifies what those minima are. It is distinct enough from siblings like detect_supportedness, though it does not explicitly name an alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives such as detect_supportedness or detect_thin_walls. The parenthetical implies a print-safety use case, but no explicit context or exclusions are provided.

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