Generate Video

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

With no annotations provided, the description fully carries the behavioral transparency burden. It discloses the async processing, auto-polling, processing time estimates, and output features (file path, thumbnail, HTML player). No contradictions exist since annotations are absent.

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 description is front-loaded with the core purpose and structured into two clear paragraphs. It is concise but includes necessary warnings and details. Minor redundancy (e.g., mentioning processing time twice) could be trimmed, but overall efficient.

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 the tool's complexity (13 parameters, nested objects, no output schema), the description adequately covers inputs, behavior, and basic output format. However, it lacks explicit error handling details, failure modes, or return type schema, which would be beneficial for a complex async tool.

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 100%, so parameters are well-documented. The description adds value beyond the schema by summarizing key behaviors (e.g., resolution impact on time, audio generation, thumbnail extraction) and providing a concrete prompt example, which aids agent decision-making.

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 clearly states the tool generates videos using Google Veo 3.1 AI model, specifying duration (4-8 seconds), input types (text prompts with optional images), and outputs (file path, thumbnail, HTML player). It distinguishes itself from siblings like generate_image (image generation) and transcribe (audio processing) by focusing on video creation.

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 implicitly guides usage by noting the async nature and 2-5 minute processing time, but it does not explicitly state when to use this tool versus alternatives like generate_image for static images or when not to use it (e.g., for editing existing videos). The warning and auto-polling note help manage expectations.

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