create_video

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

With no annotations provided, the description fully carries the transparency burden. It discloses key behaviors: returns a job ID, is asynchronous, and may take several minutes. This is critical for setting user expectations. It does not elaborate on failure modes or rate limits, but the disclosed traits go beyond basic schema and give meaningful operational insight.

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 three sentences, immediately leading with the core purpose. Each sentence adds necessary value: what the tool does, what it returns, and how it behaves. No filler or repetition.

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?

The description covers the essential workflow: creating a job and receiving a job ID for later status checks and downloads. It accounts for the asynchronous nature and the lack of an output schema. It doesn't mention all parameter choices, but that's already in the schema. Minor gap: it does not explicitly reference sibling tools like get_video_status or download_video, though the job ID mention implies their use.

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% with detailed descriptions for all four parameters, including enums and defaults. The description adds no extra parameter-specific information beyond what the schema already provides, so it meets the baseline for high schema coverage.

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's purpose: 'Create a new video generation job using OpenAI's Sora model.' It specifies the verb ('create'), resource ('video generation job'), and model context. It also differentiates from sibling tools by focusing on prompt-based creation, while a sibling like create_video_with_image likely handles image-based input.

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 provides clear context: this is the tool for creating a new video generation job from a text prompt using Sora. It does not mention explicit alternatives or exclusions (e.g., using create_video_with_image for image-based prompts), but the context is unambiguously about starting fresh from text. This aligns with a clear usage scenario.

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