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Showoff.dev – AI Mockup Generator

List compositions, palettes and formats

list_compositions
Read-only

Lists the building blocks for laying out a still or film scene: compositions (device arrangements derived from curated reference shots, with their device count and best formats), measured reference shots, background palettes, format presets, text roles and text regions. Use it before create_project or edit_scene to choose a composition, reference, palette or format; use list_templates instead when the user wants a finished, named scene, and suggest_palette for palettes matched to their screenshots. Read-only, no parameters. Returns a readable list plus compositions, references, palettes, formats, text_roles and text_regions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/destructiveHint=false, but the description adds that it takes no parameters and discloses the return shape ('a readable list plus compositions, references, palettes, formats, text_roles and text_regions'), which is valuable since there is no output schema. It does not mention caching, ordering, or size limits, so it stops short of a 5.

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?

Front-loads the resource list, then usage, then alternatives, then return shape in three dense sentences with no filler. The parenthetical describing compositions is slightly long but earns its place by clarifying what a 'composition' is.

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, the description usefully enumerates the return keys and the follow-up tools. A count of how many items typically return or whether the list is filtered is not stated, but for a read-only enumeration tool the coverage is adequate.

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?

Zero parameters, so there is no parameter semantics to document; the description correctly confirms 'no parameters'. Baseline 4 applies for a parameterless tool.

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?

Names a specific verb ('Lists') and enumerates the exact resource set: compositions, measured reference shots, palettes, format presets, text roles and text regions. An agent can tell precisely what it returns without opening anything else.

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

Usage Guidelines5/5

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

Explicitly states when to use it ('before create_project or edit_scene to choose a composition, reference, palette or format') and names two alternatives with their selecting conditions (list_templates for finished named scenes, suggest_palette for screenshot-matched palettes). Nothing is left to inference.

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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