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text_to_video

Turn text prompts into videos with HappyHorse models on RunAPI. Returns task ID and output URLs for managing generation.

Instructions

Create a HappyHorse task on RunAPI (text to video). Returns a task id, status, and output URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNo
waitNoPoll until the task reaches a terminal status.
modelNoRunAPI model slug for this model line.
promptNo
timeout_msNo
aspect_ratioNo
callback_urlNo
duration_secondsNo
poll_interval_msNo
output_resolutionNo
reference_image_urlsNo
Behavior2/5

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

There are no annotations, so the description must disclose behavioral traits. It mentions 'Returns a task id, status, and output URLs,' which gives some clue about the asynchronous nature, but it doesn't explain side effects, required auth, costs, or how long the task takes. Thus, it's minimally informative.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The entire description is one 14-word sentence that front-loads the verb and resource. It's efficient and every word contributes to the core message.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (11 parameters, 0 required, no output schema, no annotations), this high-level description is insufficient. It doesn't explain the task lifecycle, how to specify inputs, what the output URLs represent, or how this relates to get_task. The agent would be left guessing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 11 parameters with only 18% description coverage, and the tool description does not explain any parameters. It doesn't clarify which model to choose, what prompt format is expected, or what the options mean. The description adds no meaning beyond the bare field names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Create' and identifies the resource as a 'HappyHorse task on RunAPI' with the scope 'text to video,' which clearly distinguishes it from siblings like image_to_video and edit_video. It also states the return type (task id, status, output URLs).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'text to video' clearly implies the tool is for generating video from text prompts, which provides clear context relative to image_to_video. However, it doesn't explicitly mention alternatives or exclusions, so it falls slightly short of full guidance.

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

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