Create a single image from a text prompt using Replicate AI models, with optional controls for size, seed, and guidance.
Generate a single image from a text prompt using Replicate AI models.
| Name | Required | Description | Default |
|---|---|---|---|
| seed | No | ||
| width | No | ||
| height | No | ||
| prompt | Yes | ||
| model_name | No | ||
| guidance_scale | No | ||
| negative_prompt | No | ||
| num_inference_steps | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It discloses only the provider (Replicate) and that one image is produced; it says nothing about cost, latency, model selection behavior, reproducibility via seed, or failure modes.
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?
A single well-formed sentence with zero waste, front-loading the verb and resource. It is efficient, though its brevity stems partly from under-specification rather than tight editing.
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?
An output schema exists, so return values need not be described. However, for an 8-parameter generative tool with no annotations and 0% schema coverage, the description leaves the agent without enough information to tune parameters or anticipate behavior.
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% for 8 parameters, and the schema exposes only bare titles. The description clarifies only 'prompt' (text prompt) and adds nothing about seed, width, height, model_name, guidance_scale, negative_prompt, or num_inference_steps.
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?
States a specific verb (generate), resource (image), scope (single), input type (text prompt), and backend (Replicate AI models). The word 'single' implicitly distinguishes it from generate_image_batch, though no sibling is named explicitly.
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?
No when-to-use guidance beyond the implicit 'single image' scope. Nothing tells the agent when to prefer this over generate_from_reference_image or edit_image, and no prerequisites or exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.