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

With no annotations, the description carries the full burden and does disclose the key behavioral trait: this is non-destructive — it creates a new version and preserves the original. It also names the underlying model. It omits auth/cost/async details, but the destructive-vs-safe distinction is the most important disclosure and it is present.

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?

Front-loaded with the purpose, then usage constraints, then the non-destructive behavior and model. Every sentence adds information; the trailing model identifier is the only slightly expendable element, but it aids transparency.

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?

For a 4-param tool with no annotations and no output schema, the description covers purpose, usage, and the key behavioral outcome ('new version on the media doc'). It could say more about what the caller receives (e.g., a new media ID) and any async/auth requirements, but it is broadly complete.

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 schema already documents mediaId, editPrompt, model, and workspaceId. The description references the media ID and text prompt but adds no format or syntax beyond what the schema provides, matching the baseline 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?

States a specific verb+resource ('Edit an existing image using AI') and scopes it to existing images, which naturally distinguishes it from generate_image, render_image, and upscale_image. The outcome description ('Creates a new version on the media doc') makes the operation 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?

Provides an explicit when-to-use constraint ('only when the user explicitly asks to modify an existing image') and a frequency warning ('Use sparingly'). It does not name a specific alternative to route to, but the 'existing image' scoping implicitly separates it from generation tools.

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