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pika_generate_video

Generate an AI video from a text prompt and optionally animate an image. Returns a generation ID to track progress.

Instructions

Generate a creative AI video from a text prompt using Pika. Optionally animate an input image. Returns a generation_id to poll for completion.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyYesPika API key
promptYesText description of the video to generate
image_urlNoURL of an image to animate
styleNoStyle name or ID (use pika_list_styles to browse options)
durationNoVideo duration in seconds
aspect_ratioNoe.g. 16:9, 9:16, 1:1
negative_promptNoWhat to avoid in the video
motionNoMotion intensity 1-4 (default: 2)
seedNoRandom seed for reproducibility
Behavior3/5

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

Discloses the core behavior (generation, optional image animation, returned generation_id) but omits details on asynchronous nature, rate limits, failure modes, or required permissions beyond the api_key parameter. No annotations force full burden on description.

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?

Two sentences that efficiently convey the main action, optional feature, and return value. Front-loaded with the core purpose. No extraneous information.

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

Completeness3/5

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

Adequate for a simple generation tool with many parameters, but lacks context on parameter usage (e.g., how duration or style affect output) and does not mention the related polling tool (pika_get_generation).

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

Parameters3/5

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

Schema coverage is 100% with good parameter descriptions. The description adds value by clarifying the return value (generation_id) which is not in the schema, but does not further explain parameters beyond the schema.

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

Purpose4/5

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

The description clearly states it generates an AI video from text, with optional image animation, and notes the return of a generation_id. However, it does not differentiate from sibling tools like kling_generate_video or runway_generate_video.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool vs alternatives or prerequisites. The description implies usage by mentioning optional animation and polling, but lacks when-not or alternative references.

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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