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jtxmp
by jtxmp

generate_image

Generate images from text prompts via OpenRouter using quality presets or explicit model IDs, with style, size, and aspect ratio options.

Instructions

Generate an image from a text prompt via OpenRouter. Supports quality presets (fast/balanced/quality) or explicit model IDs. For best results, expand brief prompts with details about composition, lighting, color palette, and mood before calling — unless the user explicitly asked for a simple/minimal prompt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of image variations to generate (1-4). Ask the user how many they want before generating.
modelNoExplicit OpenRouter model ID — overrides quality preset
styleNoVisual style preset to prepend to the prompt
promptYesWhat to generate
qualityNoQuality preset: fast (cheap/quick), balanced (default), quality (best output)balanced
image_sizeNoOutput image size
output_pathNoOptional path to save the PNG. Can be a full file path or a directory (auto-names the file)
aspect_ratioNoOutput aspect ratio

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the OpenRouter backend and the meaning of the quality presets (cheap/quick vs best output), which is useful. But it omits cost implications, latency, rate limits, and whether the result is returned inline or only via output_path.

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 sentences, zero filler, front-loaded with the core action and backend. The prompt-expansion caveat follows logically and is appropriately short.

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 an 8-parameter generation tool with no output schema, the definition should clarify what is returned (image bytes, URL, or a saved file path) and how output_path changes that. The model/preset relationship is covered, but this return-shape gap leaves the definition only adequate.

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 all 8 parameters are already documented in the schema, establishing a baseline of 3. The description adds one cross-parameter nuance (model overrides the quality preset) that the schema only hints at, but doesn't explain output_path behavior or aspect-ratio/size interaction.

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 (generate an image) plus the backend (OpenRouter), and distinguishes its two configuration paths (quality presets vs explicit model IDs). An agent can tell it apart from edit_image, batch_images, and list_image_models without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Offers concrete advice on when to expand a prompt and when not to (simple/minimal user request), which is real usage guidance. However, it says nothing about when to use this tool versus edit_image or batch_images, nor about cost/prerequisite conditions implied by check_balance being a sibling.

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