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

Annotations only supply openWorldHint, so the description carries most of the burden. It usefully discloses the asynchronous contract (returns a request ID retrieved later via fetch-video), which is real added value. It omits cost, latency, auth, and what happens on failures, so it is adequate but incomplete.

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?

Three short sentences, front-loaded with the core action and then the async retrieval path. No filler, though the middle sentence largely restates the first.

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 12-parameter generation tool with no output schema, the description covers the essential input-modify-then-fetch loop. It does not note that three parameters are required, nor explain model selection or duration/aspect-ratio interactions, leaving gaps an agent must fill from the schema.

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 every one of the 12 parameters is already documented in the schema. The description adds no syntax, format, or interaction detail (e.g. how init_image pairs with image_timestamps) beyond that, 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 ('Transform existing videos with AI') and clarifies that it takes an input video and modifies it per a prompt. This implicitly separates it from text-to-video and image-to-video siblings, though no sibling is named explicitly.

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?

Usage is implied by 'existing videos' and 'based on the prompt', and it hints at the async workflow by pointing to fetch-video. However there is no explicit when/when-not guidance or statement of prerequisites such as which model IDs are valid or the minimum duration.

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