MakerPortal compute

Solve the best rectangular room proportions for a given volume.

roomShapeBand

Solve the best rectangular room proportions for a given volume.

The identical function that renders /lab/room-shape/{lo}-{hi}. Give a room volume in cubic feet and get the proportions to build: the length and width as multiples of the ceiling height, the exact dimensions at your volume, the widest axial gap they leave, and how far those proportions sit from a full solve at your exact volume. Also returns the band the volume falls in, that band's guarantee across its whole range, and which Bolt constraints are active at the answer. Five bands cover 800-5,000 cubic feet; a volume outside that range is refused rather than served from the nearest band.

Every result carries provenance.canonicalUrl — the published page for these exact inputs, or the lane hub when they are off the published grid.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`volume`	Yes	Room volume in cubic feet. Five bands cover 800–5000 ft³; anything outside that is a 400 naming the range, never an answer from the nearest band.

Output Schema

TableJSON Schema

Name	Required	Description
`inputs`	Yes	The parsed inputs, echoed back with defaults filled in.
`result`	Yes	The solved analysis. Shape is per-tool.
`license`	Yes
`provenance`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 6, 2026

TDQS

A4.1/5.0

Behavior5/5

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

With no annotations provided, the description carries full responsibility and delivers richly. It discloses the return contents, the volume band behavior, refusal of out-of-range input, and the presence of provenance.canonicalUrl on every result. It even clarifies that out-of-range volumes are refused rather than served from a neighboring band.

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 description is front-loaded with the core purpose and then details outputs, constraints, and provenance in a logical order. It is somewhat verbose, and the sentence about the identical rendering function is slightly tangential, but nearly every sentence earns its place.

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?

This is a single-parameter tool with an output schema, and the description covers input units, valid range, refusal behavior, output fields, band guarantees, and provenance. Nothing essential for an agent to decide whether to call it and what to expect is missing.

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 100%, so the baseline is 3. The description adds meaningful semantics beyond the schema: it specifies the valid volume range, the band structure, and the refusal behavior for out-of-range values, which helps the agent reason about valid inputs.

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 clearly states a specific verb and resource: solving rectangular room proportions for a given volume. It is unambiguous about what the tool computes, but it does not explicitly distinguish itself from sibling tools such as roomModes, so it misses the top score.

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?

The usage context is implied: provide a room volume in cubic feet and receive proportions. It also gives a firm exclusion boundary by refusing volumes outside 800–5,000 cubic feet, but it never names alternatives or states when to prefer another tool, so the guidance is only implicit.

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

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TDQS

A4.3/5.0

Disambiguation5/5

Each tool targets a clearly distinct computational domain: biquad filter design, LLM VRAM fitting, room eigenmodes, room shape selection, and solenoid fields. Even the two room-related tools are cleanly separated—one analyzes existing dimensions while the other synthesizes proportions—so an agent is unlikely to misselect.

Naming Consistency5/5

All five tool names follow the same camelCase, domain-plus-result pattern: biquadDesign, llmVramFit, roomModes, roomShapeBand, solenoidField. There are no underscores, hyphens, or mixed casing conventions, so the naming is internally consistent.

Tool Count5/5

Five tools is a well-scoped count for a specialized compute server. Each tool is substantial and standalone, and there is no sense of padding or missing middle ground between too granular and too broad.

Completeness5/5

Each tool is a self-contained calculation with rich output and explicit bounds, and no CRUD lifecycle is expected for a compute server. The coverage across the exposed domains is thorough, with no obvious dead-end workflow or missing companion operation.

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