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

The description discloses behavioral details beyond annotations: 'Submits, polls, and returns the edited image URL(s)', cost (6 cr per call), number of variations (2), expected latency (~30s), and the upstream URL-spaces/parentheses failure caveat. These are not captured by the annotations, which only state readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false, so the description adds substantial transparency.

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 opening paragraph is front-loaded and direct, with useful examples. The model selection guide is lengthy but well-organized and earns its place given the number of model choices; a small redundancy (default model restated) prevents a perfect score.

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 9 parameters, no output schema, and a complex multi-model decision, the description is remarkably complete: it covers return values (edited image URLs), polling behavior, costs, timing, source URL constraints, and model-specific guidance. It is sufficient for an agent to select and invoke the tool correctly in most scenarios.

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 100%, so the baseline is 3. The description adds extra meaning by explaining model trade-offs (cost, speed, quality), noting that `imageUrl` must be a 'clean URL', and describing default model behavior. It doesn't deeply elaborate every parameter (e.g., `quality`, `renderingSpeed`), but it compensates beyond the schema for the most important ones.

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 a specific verb+resource: 'Edits an existing image guided by a text prompt.' It then gives concrete examples ('add a moon to the sky', 'swap the background for a neon city') and clarifies required inputs (`imageUrl` plus `prompt`), which clearly distinguishes it from siblings like `aetherwave_generate_image` or `aetherwave_remove_background`.

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?

It provides an explicit model selection guide with when-to-use rules ('Need a single deterministic output... -> seedream-v4-edit', 'NSFW edits -> wan-2.5-spicy-i2i') and a default fallback ('If the user simply says "edit this image"... default to grok-imagine-i2i'). It also directs users to `list_image_models` for the full lineup, offering clear alternatives.

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