Create images from text prompts using Cloudflare Workers AI and save them as PNG files with adjustable model, dimensions, and output path.
Generate an image with Cloudflare Workers AI and save it as a PNG file.
| Name | Required | Description | Default |
|---|---|---|---|
| seed | No | ||
| model | No | flux-2-klein-4b | |
| steps | No | ||
| width | No | ||
| height | No | ||
| prompt | Yes | ||
| guidance | No | ||
| overwrite | No | ||
| output_path | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It usefully discloses that the tool writes a PNG file, but says nothing about authentication, rate limits, whether existing files are overwritten, where files are saved, or what happens on failure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with no wasted words and the core action is front-loaded. Its brevity is appropriate structurally, though the sentence is too terse to cover the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists and return values need not be explained, the description is still incomplete for a 9-parameter tool with zero schema descriptions and no annotations. It omits any explanation of model choice, image dimensions, seed behavior, or output path handling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no information about any of the 9 parameters. Parameters like seed, steps, guidance, width, height, model, overwrite, and output_path are completely undocumented in both the schema and description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Generate'), resource ('an image'), backend ('Cloudflare Workers AI'), and side effect ('save it as a PNG file'). An agent can immediately understand what the tool does 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. The description only implies usage through the verb 'Generate', leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.