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CaseyRo
by CaseyRo

Create mockups

create_mockups

Render one design into one or more device or print mockups from a screenshot URL, image URL, or base64 image, returning CDN-ready mockup outputs.

Instructions

[mockuuups] Put one design into one or more mockups and render them.

Give exactly one source:

  • screenshot_url — Mockuuups screenshots the live page itself. Best for websites; costs one extra credit per render.

  • image_url — any publicly reachable image.

  • image_base64 — raw image bytes for a design that only exists locally. Mockuuups can only render from a URL, so the image is staged on this server under a short-lived unguessable link for the render to fetch.

Pass several mockup_ids to render the same design across devices in one call; they run concurrently. Renders that outrun the wait budget come back as pending with a render_id for get_renders — the CDN links are already valid and will fill in once the render lands.

Each render costs a credit, +1 for a screenshot, so check account_status before a large batch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNo
image_urlNo
mockup_idsYes
image_base64No
wait_secondsNo
screenshot_urlNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
failedYes
pendingYes
rendersYes
summaryYes
requestedYes
succeededYes
credits_spentYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.7

TDQS

A4.8/5.0
Behavior5/5

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

Goes well beyond the annotations (openWorldHint=true, idempotentHint=false, destructiveHint=false) by disclosing credit costs per render and per screenshot, the concurrent execution of multiple mockup_ids, the base64 staging-to-short-lived-URL behavior, and the pending/render_id outcome when the wait budget is exceeded. This is exactly the operational context the annotations cannot carry.

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-loaded with the core action, then organized into a source-selection block and a cost/behavior block; every sentence carries information. It is somewhat long for a tool description, though the length is earned by the genuine complexity.

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?

For a 6-parameter mutation tool with an output schema present, the description covers input selection rules, cost model, concurrency, base64 constraints, and the asynchronous pending path. Nothing an agent needs before invoking it correctly is missing, aside from the minor `size` omission.

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 0%, so the description must supply parameter meaning; it thoroughly explains the three mutually exclusive source parameters and mockup_ids, plus implies wait_seconds via the 'wait budget' remark. However, the `size` parameter is never mentioned, leaving one of six parameters undocumented anywhere.

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, resource, and scope: 'Put one design into one or more mockups and render them.' Combined with the sibling set (search_mockups, get_renders, account_status), the agent can immediately tell this is the render-creation tool rather than a search or polling tool.

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 bounds the input choice ('Give exactly one source') and names the conditions selecting each option (websites vs. any public image vs. local-only files). It also routes the agent to account_status before large batches and to get_renders for pending results, covering when-not and alternatives.

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