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

With no annotations provided, the description carries the full behavioral disclosure burden. It does this excellently: it explicitly states the tool starts an async job, returns `id` and `credits_charged` immediately, requires waiting or polling, lists terminal statuses, describes `downloads` URLs, and gives detailed `exact_download_urls` behavior. It also discloses file-path pitfalls and recommends the upload flow.

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 one-line purpose followed by focused MCP guidance. The bullets are somewhat long, but every sentence carries necessary operational detail for a complex async tool. It is front-loaded with the core purpose and then dives into actionable behavior, striking a good balance for its 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?

The description covers the most important operational context: async behavior, return shape at submission, how to retrieve results, terminal statuses, download URL handling, and file-path selection. Since an output schema exists, detailed return value documentation is not required. The description is complete enough for an agent to invoke the tool and handle the follow-up workflow correctly.

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 coverage is high at 86%, and the schema already documents parameters thoroughly, so the baseline is 3. The description adds meaningful value by explaining how to handle `*_file_path` values, specifically recommending Magic Hour file paths or upload-URL returned paths and warning against hotlinked URLs. This directly aids parameter use beyond the schema.

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 clear verb and resource: 'Edit images with AI.' This distinguishes the tool from generative image creation or upscaling at a basic level. However, it does not explicitly differentiate from sibling image-editing tools like ai_face_editor_edit_image or body_swap_create_image, leaving some ambiguity for an agent choosing among similar tools.

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 explains how to use the tool (async job, wait helper, polling) but does not provide explicit when-to-use versus alternatives guidance. It implies usage by saying 'Edit images,' but there are no exclusions or sibling comparisons. An agent would need to infer selection criteria from the name and schema rather than from clear guidance.

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