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Generate AI image

generate_image

Create billboard artwork from a text prompt and return base64 data URIs for upload_media, so AI agents can attach ready images to GPS-anchored ads.

Instructions

Generate billboard artwork from a prompt (recommended 640x373). Returns base64 data URIs you can pass to upload_media. Prefer realistic photos.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
widthNo
heightNo
promptYes
aiProviderNoProvider type from GET /global-config/all: 5 = Grok (default, recommended), 1 = OpenAI

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the return format (base64 data URIs) and the downstream handoff to upload_media, but it omits auth requirements, rate limits, generation cost/performance, provider behavior, and failure modes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tightly written sentences with no wasted words. The core action and output are front-loaded, followed by the downstream workflow and prompt preference.

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?

For a tool with no annotations, no output schema, and only 25% schema description coverage, the description covers the return format and upload_media workflow. However, it omits the aiProvider parameter entirely and does not describe generation constraints or side effects, so it is adequate but incomplete.

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 low at 25%, so the description must compensate. It adds practical meaning for prompt and image dimensions via 'from a prompt (recommended 640x373)' and prompt style guidance ('Prefer realistic photos'), but it never names width, height, or aiProvider, leaving gaps in parameter semantics.

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: 'Generate billboard artwork from a prompt.' It distinguishes itself from media-storage siblings by naming upload_media as the downstream tool, so an agent can identify its role without opening the schema.

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?

It gives clear usage context: use a prompt, recommended dimensions of 640x373, prefer realistic photos, and pass the returned base64 data URIs to upload_media. It does not state when not to use this tool or compare it to an alternative image-generation tool, but the workflow is clear.

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