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gwmage

Rootr MCP Server

Generate an image from a text prompt (for a slide)

rootr_generate_image

Generate AI-powered images from text prompts for Rootr presentations. Returns image details to embed in slides, eliminating placeholders.

Instructions

Generate an image from a text prompt with AI (Gemini) and store it as a workspace attachment. Use this when building a Rootr (루터) presentation so slides get real, on-brand visuals instead of empty image placeholders — generate the image, then put the returned url into a slide image's src via rootr_update_presentation_slide (image or images[]). Returns { id, url, filename, mimeType, size }. Prompt tips: describe a clean, flat, presentation-ready illustration; specify colors to match the deck theme; and say "no text" — baked-in text is not indexed and often renders wrong (put the meaning in the slide title/blocks instead, and always give the image an alt caption). Consumes AI credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nodeIdNoPresentation/node id to attach the image to (permission-checked)
promptYesEnglish image description; ask for "no text" in the image
workspaceNoWorkspace id; defaults to ROOTR_WORKSPACE/config
Behavior4/5

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

Annotations indicate it is not read-only and not destructive. The description adds that it consumes AI credits and stores images as workspace attachments, providing helpful behavioral context beyond annotations.

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 description is slightly long but well-structured, front-loading the primary action and usage context. Each sentence adds value, though it could be trimmed slightly.

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?

The description covers the return value structure, how to use the result in slide images, and prompt tips. It lacks mention of error conditions or file size limits, but for basic usage it is complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All three parameters have descriptions in the schema (100% coverage). The description adds valuable tips for the `prompt` parameter (e.g., clean, flat illustration, colors, no text) and explains the role of `nodeId` (permission-checked) and `workspace` (default behavior).

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 clearly states the tool generates an image from a text prompt using AI, stores it as a workspace attachment, and returns a URL for use in slides. It distinguishes itself from the sibling tool `rootr_remove_image_background` by focusing on generation for presentation visuals.

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?

The description explicitly says 'Use this when building a Rootr presentation' and provides detailed prompt tips (e.g., 'no text', specify colors). It does not explicitly exclude alternative uses, but the context is sufficiently clear.

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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