text_to_video_create_video

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

With no annotations provided, the description carries the full burden. It discloses the async nature (starts a job and returns id plus credits_charged immediately), provides the polling/wait helper path, explains the cost model (credits for rendered frames), and notes free-tier resolution limits. It does not cover rate limits or error handling, but covers the most critical behavioral aspects.

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 well-structured with clear sections ('What this API does', 'Good for', 'How it works', etc.) and includes a dedicated 'MCP guidance' block that is highly useful for an agent. While lengthy, each section adds value and the most important information (purpose, async behavior) is front-loaded. It is not overly verbose, though it could be trimmed slightly.

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 (async, many model options, multiple parameters), the description covers the essential flow: upload inputs, create job, poll for completion, and download. It references the wait_for_video_project helper and mentions cost and resolution restrictions. With an output schema present, return value details are not needed in the description. Minor gaps like error handling and rate limits exist but are not critical.

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 86%, so the schema already documents most parameters in detail (including model-specific support). The description adds some context beyond the schema, such as the free-tier 576px resolution limit, but does not elaborate on individual parameters beyond what the schema provides. It mentions 'extra fields' generically without specifics, so it does not fully compensate for the remaining 14% but is adequate given 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 explicitly states it creates text-to-video programmatically, mirroring the browser feature. It clearly differentiates from sibling video tools like image_to_video and audio_to_video by naming 'Text To Video' and describing the async job creation. The verb 'create' and resource 'video' are specific and unambiguous.

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 'Good for' section lists automation, batch processing, and integration, and the 'How it works' steps give a clear workflow. However, it does not explicitly state when to prefer this tool over alternatives like image_to_video or audio_to_video; the distinction is only implied by the name. It also mentions input types ambiguously ('video, image, or audio') which could confuse an agent deciding between tools.

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