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TypeScript
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blockrun_video

Generate short AI videos from text prompts. Submit a prompt and optional seed image or real face asset to produce a short MP4 clip with payment only for successful renders.

Instructions

Generate short AI videos via BlockRun x402 (async, client-polled).

Turns a text prompt (and optional seed image) into a short MP4 clip. The tool submits the job, then polls until the video is ready (typical total wall-time 60-180s; 5 min hard cap). Payment is settled only when upstream returns a finished video — if the job fails or we give up, you are not charged.

Models (Seedance defaults bumped to 720p + synced audio on the gateway):

  • azure/sora-2 ($0.10/sec, 720p + synced audio, text-to-video) — OpenAI Sora 2 via Azure AI Foundry. duration_seconds must be 4, 8, or 12 (4s default -> ~$0.42/clip). No image_url / RealFace.

  • xai/grok-imagine-video ($0.05/sec, 8s default -> $0.42/clip) — stylized, fast

  • bytedance/seedance-1.5-pro (~$0.092/sec, 720p + audio t2v, 5s default up to 10s) — cheapest Seedance, token-priced upstream

  • bytedance/seedance-2.0-fast (~$0.238/sec text · ~$0.140/sec image-to-video, 720p + audio, ~60-80s gen) — sweet-spot price/quality; supports BytePlus RealFace assets

  • bytedance/seedance-2.0 (~$0.298/sec text · ~$0.183/sec image-to-video, 720p + audio Pro) — highest quality; supports BytePlus RealFace assets

RealFace: to generate video of a SPECIFIC real person, first enroll them with blockrun_realface (returns a ta_xxxx asset id), then pass real_face_asset_id here with a Seedance 2.0 model. Mutually exclusive with image_url.

Returns a permanent blockrun-hosted MP4 URL (the gateway mirrors the asset to GCS so URLs don't expire).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesText description of the video to generate. E.g. 'a red apple slowly spinning on a wooden table', 'a hummingbird hovering near a red flower, ultra slow motion'
image_urlNoOptional seed image URL for image-to-video generation
real_face_asset_idNoBytePlus RealFace asset id (from blockrun_realface enroll/list) to generate video of a specific real person. Seedance 2.0 / 2.0-fast only. Mutually exclusive with image_url.
duration_secondsNoDuration to bill for (defaults to the model's default — 8s for xAI, 5s for Seedance; Seedance supports up to 10s).
modelNoVideo model to usexai/grok-imagine-video
agent_idNoAgent identifier for budget tracking and enforcement.

Tool Definition Quality

A4.7/5.0
Behavior5/5

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

With no annotations, the description fully discloses behavioral traits: async polling, typical wall-time (60-180s), hard cap (5 min), conditional payment (charged only on success), permanent URL, and mutual exclusivity of image_url and real_face_asset_id. This exceeds expectations.

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

Conciseness4/5

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

The description is lengthy but well-structured with clear sections for models, RealFace, and return value. Every sentence adds value, though it could be slightly more concise. Given the complexity, the verbosity is justified.

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

Completeness5/5

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

Despite no output schema, the description adequately explains the return (permanent MP4 URL). It covers input, process, constraints, and alternatives comprehensively. For a complex video generation tool, it is fully complete.

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

Parameters5/5

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

Schema coverage is 100%, but the description adds significant meaning beyond schema: it explains model-specific defaults, pricing per second, and constraints (e.g., duration_seconds defaults per model). This enriches understanding of each parameter.

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 clearly states the tool generates short AI videos via BlockRun x402, specifying the verb 'Generate', the resource 'short AI videos', and the async polling mechanism. It distinguishes from siblings like blockrun_image and blockrun_realface by focusing on video generation and RealFace integration.

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 description provides extensive guidance on when to use each model, including pricing, duration defaults, and compatibility. It also explains prerequisites for RealFace videos. While it doesn't explicitly state when not to use the tool, the detailed model comparisons cover alternatives adequately.

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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