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

With no annotations, the description carries the full burden and does well: it discloses cost (1 credit per minute), asynchronous execution with a job_id, the polling tool, and that result links expire in 1 hour. It does not mention auth requirements or what happens if both text and watermark_url are omitted, which keeps it short of a 5.

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?

Four short sentences, front-loaded with what the tool does, followed by cost, async handling, and link expiry. Every sentence earns its place with no redundancy.

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 10-parameter media-mutation tool with no annotations and no output schema, the description covers cost, async behavior, retrieval path, and result longevity. It leaves unstated the edge case of supplying neither text nor watermark_url, a minor gap in an otherwise complete definition.

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 70% and the schema documents most parameters with descriptions, defaults, and ranges. The description only alludes to position/size/opacity at a high level and adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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 and resource ('Put a logo image and/or a line of text on a video') and enumerates the controllable dimensions (position, size, opacity). This is clearly distinguishable from siblings like add_captions, edit_video, or video_color_grade without opening any schema.

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 operational flow (long jobs return a job_id, poll with get_job) but never says when to choose this tool over alternatives such as edit_video or add_captions. Usage is implied by the resource rather than explicitly scoped.

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