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generate_image

Create an image from a text description and save it locally. Get the file path to view it, and each request generates only one image to control costs.

Instructions

Generate an image from a text prompt and save it to disk. Call this when the user asks to draw, create, render, illustrate or generate a picture, photo or artwork. Returns the absolute paths of the saved files; pass one to read_image to view it. Each call costs real money, so call it once per explicit user request.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoOutput size as WxH, for example 1024x1024. Some models require at least 3686400 pixels, so 2048x2048 is the safe large size.
modelNoImage model id for this call only. Omit to use the configured default. Call get_config for the available ids and their size constraints.
promptYesWhat to draw, in natural language. Prefer a specific, visual description: style, subject, lighting and composition all help.
outputDirNoDirectory for this call only. Omit to use the configured default.
timeoutMsNoHow long this call may wait, in milliseconds. Omit to use the configured default. The ceiling is 3600000 (one hour).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the side effect of saving to disk, the return format (absolute paths), how to view results (pass to read_image), and the cost implication. This is substantial coverage, though it omits potential timeouts or network behavior that could be relevant given the timeout parameter.

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?

Three sentences with zero fluff. The main action is front-loaded, the trigger conditions follow, and the return/cost note is placed at the end. Every sentence earns its place.

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?

The description is complete for a generate-and-save tool. It explains the return value (paths), how to view results, and the cost constraint. The schema already covers all parameter details, so nothing essential is missing for an agent to call it correctly.

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 100%, so the baseline is 3. The description adds no parameter-specific meaning beyond what the schema already documents; it only rephrases the purpose. It does not compensate for any schema gaps, as there are none, but it also adds no extra insight.

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 an image from a text prompt and save it to disk.' It also lists trigger verbs (draw, create, render, illustrate, etc.) that clearly distinguish it from the video-generating sibling, making the purpose unmistakable.

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 explicitly states when to call ('when the user asks to draw, create, render...') and even adds a cost-based usage rule ('call it once per explicit user request'). However, it does not name alternatives or exclusions (e.g., don't use for video), so it lacks the explicit when-not guidance that would merit a 5.

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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