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moving_estimate_from_scan

Estimate a move from RoomPlan scans by mapping detected furniture to cube-sheet sizes, excluding built-in fixtures, and flagging missing items for user review.

Instructions

Estimate a move from a RoomPlan room scan (JSON export, USDZ, or a PLY/OBJ the room tools can load).

Pass path (one merged scan) or paths (one file per room). Scanned furniture (sofa, bed, table, storage, appliances...) is mapped to cube-sheet sizes; built-in fixtures (sink, toilet, bathtub, built-in cabinets) are excluded unless fixture_policy="include_all". IMPORTANT: a scan only sees large furniture, so boxes, clothes, books and kitchenware are missing: read coverage_warning, ask the user about boxes, and pass them as extra_items (same item format as moving_estimate_from_inventory) or use contents_allowance. Ambiguous objects appear in needs_review. A raw point cloud or mesh has no furniture labels: the result then says no_furniture_recognised and asks for a RoomPlan export or an inventory list instead of a number.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNo
pathsNo
unitsNoboth
detailNosummary
room_namesNo
extra_itemsNo
size_methodNocatalog_first
fixture_policyNoexclude_builtins
contents_allowanceNonone
include_recommendationsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and meets it: it discloses mapping behavior (furniture to cube-sheet sizes), fixture exclusion semantics, the `coverage_warning`/`needs_review` signals, and the critical failure mode that a raw point cloud yields `no_furniture_recognised` rather than a number. These are behavioral traits no structured field conveys.

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 every sentence carries operational content, with caps used to flag the IMPORTANT caveat. It is dense but not padded; a mild readability hit from packing the middle into one long block.

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?

An output schema exists, so return values need not be spelled out, yet the description still names key response fields and edge-case outcomes. Combined with input guidance and failure-mode coverage, it is nearly complete for a 10-parameter tool, with only several parameter meanings left unstated.

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 description coverage is 0%, so the description must compensate. It clarifies `path` vs `paths`, the `fixture_policy="include_all"` value, and that `extra_items` uses the same format as moving_estimate_from_inventory, but leaves `units`, `detail`, `room_names`, `size_method`, and `include_recommendations` unexplained across 10 parameters.

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 first sentence states a specific verb and resource ('Estimate a move from a RoomPlan room scan') and names the accepted input formats. This clearly separates it from inventory-based siblings such as moving_estimate_from_inventory without needing to open either schema.

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 concrete routing guidance: use `path` for one merged scan vs `paths` for one file per room, and points to `extra_items`/`contents_allowance` as fallbacks when small items are missing. However it stops short of an explicit 'use moving_estimate_from_inventory instead when...' rule, leaving the sibling choice partly to inference.

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