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RaedBerjaoui

Vibecoders MCP

by RaedBerjaoui

generate_image

Create an image from a text prompt, save it to an absolute path, and use your configured provider or API key. Guides setup if no provider is configured.

Instructions

Generate an image from a text prompt and save it to an absolute file path. Uses your configured image_gen provider (codex CLI on your ChatGPT plan — no API key — or OpenAI/Gemini with your own key). If none is set up, it tells you how to enable one. Pass an absolute out_path; the saved file path is returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNosize hint for API providers, e.g. 1024x1024
modelNooverride the provider default model
promptYesnatural-language description of the image to generate
out_pathYesABSOLUTE file path to save the PNG to
providerNoforce a specific provider instead of auto-resolving
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that it writes to an absolute path, uses a configured provider, handles missing setup by providing instructions, and returns the saved file path. It does not mention overwrite behavior or error handling in detail, but the core side effects and return value are covered.

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 no fluff: the first states the core action, the second explains provider setup, and the third specifies the path requirement and return value. Information is front-loaded and every sentence earns its place.

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?

For a tool with five parameters, no output schema, and no annotations, the description is quite complete. It covers the purpose, provider setup, path constraint, and return value. It omits edge cases like overwrite behavior and error conditions, but the essential information for correct invocation is present.

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?

The schema already provides 100% coverage for all five parameters with descriptions. The tool description only reiterates that out_path must be absolute, which is already in the schema, so it adds no new semantic value beyond the structured field definitions.

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 specifies the verb (Generate), the object (an image from a text prompt), and the resource (saved to an absolute file path). It distinguishes itself from sibling tools because no other sibling performs image generation, and the mention of the image_gen provider adds specificity.

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?

Provides clear context on provider options (codex CLI, OpenAI/Gemini) and setup fallback behavior, which helps the agent understand prerequisites. However, it does not explicitly name alternative tools or state when NOT to use it, so exclusion criteria are missing.

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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