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Glama

compare

Assess 3D model silhouettes against reference images, returning per-view IoU, diff images, and edge-error band tables in world units. Use these to move the right joint or blob by exact amounts.

Instructions

Compare model silhouettes to the references. Per view: IoU, a diff image (grey = match, red = model has extra, blue = model is missing) and band tables of edge errors in world units, which tell you which joint/blob to move and by how much. fit: "auto" searches the reference scale/offset for best overlap, so only shape differences remain (absolute size is ignored); "height"/"width" instead match that dimension, bottom-aligned. against: "refs" (set_reference images), "plan" (the model's plan, placed exactly: no rescaling), or "auto" (the plan if there is one).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fitNoauto
nameYes
viewsNo
againstNoauto
resolutionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It transparently describes the output artifacts (IoU, diff image with color meanings, band tables), explains how 'fit' handles scale and offset (ignoring absolute size in auto mode), and clarifies how 'against' selects references or plan. It stops short of mentioning side effects, but for a read-oriented comparison tool this is a minor gap.

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 dense yet organized: it starts with the core purpose, then enumerates outputs, then defines the two key parameters. Every sentence contributes information without fluff. It is a little long but remains efficient and logically structured.

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?

Given the absence of annotations and output schema, the description provides substantial detail about comparison semantics and output, but it omits clarification for 'views' and 'resolution'. These have defaults, so a basic call may be possible, but advanced usage would require inferring their meaning. The tool is moderately complex, and the description is only partially complete.

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 adds rich meaning for two parameters ('fit' with values auto/height/width, 'against' with refs/plan/auto) and their behavior, but it leaves 'name', 'views', and 'resolution' unexplained. The description adds value for key parameters but is incomplete for the others.

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 ('compare') and resource ('model silhouettes') and clarifies the reference target. It details the per-view outputs (IoU, diff image, band tables) so an agent understands exactly what the tool produces, distinguishing it from measurement or editing tools.

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 description explains the semantics of the 'fit' and 'against' parameters, giving context on when to use specific values, but it does not explicitly compare this tool to siblings like 'check' or 'measure' or state when to choose one over another. Usage is implied but not contrasted with alternatives.

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