vadyu_generate_video_ad

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

With no annotations, the description must carry the full behavioral burden. It usefully discloses cost behavior – 'Deterministic text_card and logo_outro blocks consume 0 AI render credits' – which is real economic context. But it says nothing about whether generation is asynchronous, what the tool returns (job ID? URL?), expected wait time, authentication, or rate limits, all of which matter for a long-running render operation.

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 output mode is front-loaded in the first sentence, followed by the two composition systems, and the credit-cost note is placed last. It is dense but every sentence carries information; the 80-preset enumeration is left to the schema rather than dumped into the description. Slightly heavy in one paragraph but efficient overall.

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 an 18-parameter, no-annotation, no-output-schema generation tool, the description covers inputs and credit economics reasonably, but omits the return value and async behavior entirely. An agent does not know whether this call blocks, returns a video URL, or enqueues a job that must be polled with vadyu_get_video_status. That is a material completeness gap.

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 all 18 parameters in detail. The description mentions image_url, image_base64, recipes, blocks and formats, but adds no syntax, precedence, or formatting detail beyond what the schema provides. Baseline 3 is appropriate.

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: 'Generate a commercial AI product video ad from a product photo URL (image_url) or base64 image.' It also names the three input modes (recipes, custom blocks, storyboards). It does not explicitly contrast with siblings like vadyu_list_recipes or vadyu_get_video_status, but the function is distinct enough that an agent can tell it apart.

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 explains that the tool 'supports both' recipes and custom blocks and 'multi-beat storyboards', which implies three usage paths, but it gives no explicit when-to-use guidance (e.g., when to pick a recipe vs. a storyboard vs. custom blocks). The schema says the sequence is 'used when recipe and blocks are omitted', but that routing logic is not surfaced in the description.

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