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find_floating

Read-only

Detect floating parts in a 3D model by grouping touching meshes and reporting gaps from the ground and tiny seams, so you can fix assembly errors.

Instructions

Find parts that hang in the air. Meshes that touch or overlap form groups; the main group is the one that stands on ground_z (or the largest). Every other group is floating: the answer names its nearest part and the gap. tiny_gaps lists pairs that miss by touch..near metres (seams you cannot see). Run it after assembling a model, then fix with move_to_contact or attach. Long lists are folded to max_listed entries with a count. Empty touch and search follow the part size: 0.001 m and 1 m for parts of 0.3 m and more, less for small parts (a 5 cm part gets about a sixth). Empty near is 2 percent of the size of each pair (the diagonal of both parts together), at most 0.03 m: about 6 mm for a pair 0.3 m across. Each tiny gap shows the near it was held against. Give numbers in metres to fix them.

Input Schema

NameRequiredDescriptionDefault
nearNo
namesNo
touchNo
searchNo
ground_zNo
max_listedNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A4.5/5.0
Behavior5/5

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

With annotations already covering the read-only, non-destructive safety profile, the description adds rich behavioral detail: grouping logic, how the main group is chosen, tiny-gap detection, default touch/search/near values, max_listed folding, and even the nearest-part output. This is well beyond what the annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded and most sentences carry necessary information, especially the default-value rules that compensate for missing schema descriptions. The text is dense and could be more scannable, but it avoids empty filler.

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 complex spatial analysis tool with no output schema and no parameter descriptions, the description covers purpose, behavior, defaults, usage, and output shape well. The main omission is the names parameter, which prevents a perfect score.

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 description coverage is 0%, so the description must carry parameter meaning. It successfully defines ground_z, touch, near, search, and max_listed defaults and units, but the names parameter is never explained, leaving one of six parameters semantically undocumented.

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 uses a specific verb and resource: 'Find parts that hang in the air.' It immediately clarifies the exact output (floating groups, nearest part, gap) and distinguishes the diagnostic operation from sibling fixers like move_to_contact and attach.

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?

It gives clear timing ('Run it after assembling a model') and names the follow-up tools (move_to_contact or attach). However, it does not state when not to use this tool or discuss alternative analysis tools such as check_contacts.

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