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Showoff.dev – AI Mockup Generator

Look at a template

get_template
Read-only

Shows one template up close before you use it: what it shows, its public page, the full scene (devices with their angles, camera, background, overlaps), its review and a preview sketch with object ids. Use it after list_templates to check that a template fits the user's screenshots, then start a project from it with create_project (template_id). Read-only; it never creates or changes a project. Returns template, scene and review, plus the sketch unless preview is false.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
previewNoAttach a preview sketch with object ids (default true). false returns text and data only, which is faster.
template_idYesThe template id exactly as list_templates returns it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so 'Read-only; it never creates or changes a project' largely reinforces structured data. However, the description adds genuinely new behavioral context: the return shape (`template`, `scene`, `review`) and that the sketch is omitted when preview is false. This goes beyond what annotations and schema provide.

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 content is front-loaded with the purpose, then ordered as workflow, safety note, and return values. It is dense but every clause adds information; the main cost is a long first sentence that mixes purpose with an enumeration of return contents.

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?

There is no output schema, but the description names the returned keys (`template`, `scene`, `review`, plus the optional sketch), so an agent knows what to expect. Combined with the workflow guidance and read-only assurance, nothing essential for correct invocation 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 nonetheless adds meaning beyond the schema by explaining that the preview sketch is included 'unless preview is false' and framing preview as a speed tradeoff ('false returns text and data only, which is faster'), reinforcing the parameter's effect.

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 states a specific verb and resource ('Shows one template up close') and enumerates exactly what it reveals: what it shows, its public page, the full scene, its review, and a preview sketch. It distinguishes itself from siblings by name, positioning it between list_templates and create_project.

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?

It gives explicit workflow placement: 'Use it after list_templates to check that a template fits the user's screenshots, then start a project from it with create_project (template_id).' Both the preceding and following tools are named with the condition that selects them, leaving nothing 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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