Skip to main content
Glama

image_to_grid

Downsample a picture into LEGO colour-letter rows for fill_layers; crop to subject, set cell aspect ratio, and map transparent pixels to '.'.

Instructions

Downsample a picture into rows of colour letters using LEGO colours, ready for fill_layers. crop = [left, top, right, bottom] fractions (0-1) to focus on the subject. cell sets the cell's aspect ratio when height is omitted: 'stud' for top-down maps, 'brick' or 'plate' for upright walls. Transparent pixels become '.'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cellNostud
cropNo
widthYes
heightNo
paletteNo
image_pathYes
max_colorsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It usefully discloses the output representation (rows of letters, transparent -> '.') and the crop coordinate convention, but says nothing about palette quantisation behaviour, max_colors clamping, or whether the result is returned vs written to a file.

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?

Four tight sentences, front-loaded with the core action, then the two highest-value parameter notes. No filler, though the cell/height sentence is densely packed and slightly awkward.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

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 no prose, and the description supplies workflow context. With 7 parameters, zero schema descriptions, and no annotations, however, an agent still lacks guidance on palette, max_colors, and sizing interplay, leaving real gaps for a transform tool of this complexity.

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

Parameters2/5

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

Schema description coverage is 0% across 7 parameters, so the description must compensate. It explains crop's format and cell's enum meaning, but leaves width, height, palette, max_colors, and image_path entirely undocumented in both places, covering well under half the parameters.

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?

States a concrete verb+resource ('downsample a picture into rows of colour letters') and names the downstream consumer, fill_layers, which lets an agent place it in a workflow. It does not distinguish itself from build_mosaic, a sibling that plausibly covers a overlapping end-to-end path.

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?

'ready for fill_layers' implies a pipeline position, and the crop/cell notes hint at intended uses (top-down maps vs upright walls). But there is no explicit when-to-use or when-not, and no mention of build_mosaic as an alternative for the same job.

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