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Photo Mosaic & AI Collage Maker - Collager.ai

List collage shapes

list_collage_shapes
Read-onlyIdempotent

Lists the shapes make_shape_collage can draw (hearts of 27-164 photos, numbers, words, I love you, circle, star, flower, grid, your own mask) and how many photos fill each without repeats.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so safety is covered. The description adds real domain context beyond that: each shape has a photo-count range (hearts 27-164) and photos fill a shape 'without repeats', which is a constraint an agent would not otherwise know.

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?

A single sentence, front-loaded with the verb and the sibling it serves, with no filler. The parenthetical shape list is long and dense, but every element is actionable information rather than padding.

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?

With no output schema and no parameters, the description carries the burden of explaining the return, and it does so at a content level (shape names plus photo counts). It stops short of specifying the exact return shape (e.g., whether the photo count is a single number or a range field), which is the only remaining gap.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. The enumerated shape values are effectively the domain of the downstream make_shape_collage input, which is a useful bonus.

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?

States a specific verb (Lists) and resource (the shapes make_shape_collage can draw), and enumerates the actual shape values, so an agent knows exactly what it will get back. It also names the sibling make_shape_collage, distinguishing it from get_shape_collage.

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?

Naming make_shape_collage makes the intended use clear: this is the reference lookup that supplies valid shape values to that tool. However, it never states explicitly when to call this versus get_shape_collage, nor any precondition, so it stops short of full routing guidance.

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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