Remove backgrounds from images with Recraft models, returning a task ID, status, and output URLs.
Create a Recraft task on RunAPI (remove background). Returns a task id, status, and output URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| wait | No | Poll until the task reaches a terminal status. | |
| model | No | RunAPI model slug for this model line. | |
| timeout_ms | No | ||
| callback_url | No | Declared type: string. | |
| poll_interval_ms | No | ||
| source_image_url | Yes | Declared type: string. |
Changes observed during successful MCP inspections.
v0.2.0Input schema / additionalPropertiesPrevious value: -falseNew value: +{}Input schema / properties / callback_urlAdded value: +{
+ "description": "Declared type: string.",
+ "type": "string"
+}Input schema / properties / model / enumRemoved value: -[
- "recraft-remove-background"
-]Input schema / properties / poll_interval_ms / maximumAdded value: +9007199254740991Input schema / properties / source_image_url / descriptionAdded value: +"Declared type: string."Input schema / properties / source_image_url / typeAdded value: +"string"Input schema / properties / timeout_ms / maximumAdded value: +9007199254740991Input schema / requiredAdded value: +[
+ "source_image_url"
+]v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that a task is created and what the response generally contains (task id, status, output URLs), which is useful. However, it omits behavioral traits like async polling behavior, whether the operation is idempotent, what happens on failure, or any rate limits.
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?
Two concise clauses, front-loaded with the action and the backend target. No waste, and the response contents are noted tersely.
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?
Given 6 parameters, 1 required, no annotations, and no output schema, the description provides basic context about the return shape but leaves gaps: it doesn't explain async behavior, timeout handling, or how wait and poll_interval_ms interact. It is adequate but incomplete for a task-based asynchronous tool.
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 67%, above the baseline threshold. The description adds no parameter-level meaning beyond what the schema provides. With 6 parameters and only 1 required, an agent could benefit from knowing more about wait, model, and callback_url, but the schema covers several of these.
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?
Names a specific verb+resource ('remove background') and states the backend operation ('Create a Recraft task on RunAPI'). It distinguishes itself from siblings like upscale_image and get_task, though it doesn't explicitly reference them.
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, no prerequisites, no pointer to alternatives. The presence of sibling tools like upscale_image and get_task makes routing ambiguous, yet the description offers no selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.