formlabs-local-mcp

get_print_validation

Read-only

Checks each model for printability issues like cups, unsupported minima, undersupported areas, and seamlines, so you can identify and fix problems before printing.

Instructions

Full printability check per model: cups, unsupported_minima, undersupported, has_seamline.

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": "get_print_validation"
  }
}

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

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds useful context by listing the fields returned, but it does not disclose behavior around missing scenes, multiple models, error cases, or output structure.

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 concise sentence with no filler. The core purpose is front-loaded and the field list is compact and informative.

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 read-only tool with one optional parameter and no output schema, the field list plus annotations make it mostly complete. The main gap is the lack of detail on how per-model results are returned and how the scene_id parameter selects models.

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 schema describes scene_id with 100% coverage, so the baseline is 3. The description does not add any parameter-level meaning beyond the schema and does not clarify how 'per model' relates to scene_id.

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 ('get') and resource ('print validation'), and identifies it as a 'full printability check per model' listing four concrete result fields. This distinguishes it from the individual detect_* sibling tools, which each target a single check.

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 explicit guidance about when to use this tool versus the detect_cups, detect_minima, detect_supportedness, or other sibling tools. The word 'full' implies aggregation, but no clear when-to-use or when-not-to-use context is provided.

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