flux_edit_image

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description says it returns 'Task ID and edited image information including URLs,' but does not clarify whether the operation is asynchronous or synchronous, nor does it mention that users may need to poll with flux_get_task or provide a callback_url to receive results. Given the schema includes a callback_url, the async nature is likely but not disclosed, and the wording may mislead an agent into expecting the edited image immediately.

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 well-structured with a clear opening sentence, a brief paragraph on model suitability, bulleted use cases, an alternative reference, and a returns section. It is front-loaded with the core purpose. However, there is some redundancy among the 'Use this when' bullets (e.g., 'modify or transform' and 'change specific elements'), which slightly reduces efficiency.

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?

The tool has 5 parameters, a rich schema, and an output schema, but the description misses the critical asynchronous workflow context. It does not explain that the operation is likely async, that users may need to poll with get_task or get_tasks_batch, or how the task lifecycle works. This gap is important for an agent to correctly invoke and monitor the edit, despite the schema covering parameter details well.

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?

The input schema has 100% parameter description coverage, including detailed guidance for model selection, size formatting, and prompt examples. The description adds no additional parameter semantics beyond what the schema already provides, so it earns the baseline score of 3.

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 opens with 'Edit an existing image using Flux with a text prompt,' clearly identifying the verb (edit), resource (existing image), and mechanism (Flux and prompt). It explicitly distinguishes itself from the sibling flux_generate_image by stating 'For generating new images from scratch, use flux_generate_image instead,' making purpose and differentiation unambiguous.

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?

The description provides explicit 'Use this when' bullets covering common editing scenarios (transform, change elements, apply styles, add/remove/replace objects). It also names the alternative tool for new image generation, flux_generate_image, making the decision of when to use this tool versus alternatives very clear.

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