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musharna

ldraw-mcp

by musharna

bill_of_materials

Generate a bill of materials for an LDraw model, listing each part, color, and quantity. Handles submodel expansion and reports unknown colors or missing parts.

Instructions

Bill of materials for an LDraw model: part x colour x quantity rows.

Give path (a .ldr/.mpd file) or ldr (inline LDraw text), not both. MPD sub-models are expanded with their multiplicity, and colour 16 inherits the colour of the line that referenced the sub-model. Part descriptions and colour names come from the LDraw library when one is installed; without it the counts are the same and those fields are null. A colour code that LDConfig.ldr does not define is listed in unknown_color_codes, and a part the library lacks in parts_not_in_library.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ldrNo
pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.0

TDQS

A4.4/5.0
Behavior5/5

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

No annotations exist, and the description compensates well by disclosing non-obvious behavior: MPD sub-models are expanded with multiplicity, colour 16 inherits referencing line colour, library absence leaves description/colour fields null while counts are unaffected, and unknown colors/parts are surfaced in separate fields. This gives an agent an accurate model of edge cases and output 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?

Four sentences, with the core purpose first and only consequential edge cases after. No filler; every sentence adds either input constraints or behavior relevant to correct invocation.

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?

An output schema exists, so return-value shape doesn't need repeating. The description still covers input selection, library dependency, color inheritance, and error-surfacing fields, leaving few gaps for an agent to guess about.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description carries the burden. It defines both parameters (`path` as a .ldr/.mpd file, `ldr` as inline LDraw text) and clarifies the exclusive-or relationship with 'not both'.

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 states the tool produces a bill of materials for an LDraw model and defines output rows as part x colour x quantity, so an agent can tell this from render_ldraw_file/text and lookup_color. It lacks an explicit verb ('computes'/'lists') and doesn't name a differentiating sibling, but the resource and row structure are concrete.

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

Usage Guidelines3/5

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

It gives concrete invocation guidance: pass either `path` or `ldr`, not both, and describes what each input form is. However, it never explicitly states when to choose this tool over siblings like render_ldraw_text or search_parts; that choice is only implied by the BOM purpose.

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