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Generate image or video

vicsee_generate

Generate AI images or videos asynchronously by submitting a task and polling for the result. Supports text-to-image, image-to-video, reference-to-video, and video editing models.

Instructions

Create an AI image or video with VicSee. Generation is ASYNCHRONOUS: this returns a task id immediately, then poll vicsee_get_task with that id until status is "completed" (the result URL appears in result.url) or "failed". Use vicsee_list_models to pick a model and see its valid options. For image-to-video / image-to-image, pass source images in image_urls. For reference-to-video models (e.g. "seedance-2-0-reference-to-video"), pass references in reference_image_urls / reference_video_urls / reference_audio_urls and refer to them positionally in the prompt as @Image1, @Image2, … IMAGE inputs (image_urls, reference_image_urls) may be a public https URL, a local file path (this server reads and base64-encodes it for you), or a base64 data URI. VIDEO/AUDIO inputs (reference_video_urls, reference_audio_urls) must be public https URLs. For video-edit models (e.g. "happyhorse-video-edit"), pass the source clip in video_url and optionally set audio_setting ("auto" or "origin").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYesModel id from vicsee_list_models, e.g. "nano-banana-pro-text-to-image" or "seedance-2-0-text-to-video"
promptNoText prompt (required for most models)
image_urlsNoSource image(s) for image-to-video / image-to-image. Each may be a public https URL, a local file path (this server reads and base64-encodes it for you), or a base64 data URI.
reference_image_urlsNoReference-to-video only: up to 7 reference images. Each may be a public https URL, a local file path (this server reads and base64-encodes it for you), or a base64 data URI. Refer to them in the prompt as @Image1, @Image2, …
reference_video_urlsNoReference-to-video only: up to 3 public https video URLs (2-15s each, ≤15s total).
reference_audio_urlsNoReference-to-video only: up to 3 public https audio URLs.
video_urlNoVideo-edit models (e.g. "happyhorse-video-edit") only: one public https video URL, 3-15s, to edit.
audio_settingNoVideo-edit models only: "auto" (regenerate audio) or "origin" (keep the source audio).
durationNoVideo length in seconds (e.g. 5, 6, 10, 15) — video models only
aspect_ratioNoe.g. "16:9", "9:16", "1:1", "landscape", "portrait"
resolutionNoe.g. "1K", "2K", "4K", "720P", "1080P"
output_formatNoImage output format, e.g. "png" or "jpeg"
audioNoEnable native audio (supported video models)
extraNoAny additional model-specific params (see the model's options from vicsee_list_models)
Behavior4/5

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

Discloses asynchronous generation, immediate task id return, polling needed for result, and input format rules (public URLs, local paths, base64). No contradiction with annotations.

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?

Well-structured with logical sections (async, model selection, input types). Concise but not terse; every sentence adds value. Could be slightly more compact but effective.

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?

Comprehensive for a complex tool with 14 parameters: covers async behavior, polling, model selection, input formats, constraints for all model categories, and edge cases like video-edit audio settings.

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

Parameters4/5

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

Schema coverage is 100%, but description adds valuable context: positional referencing for references, constraints on video/audio URLs, and explanation of audio_setting options.

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?

Clearly states 'Create an AI image or video with VicSee.' and distinguishes from siblings by mentioning async behavior, polling, and model selection using vicsee_list_models.

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?

Provides explicit guidance for different model types (image-to-video, reference-to-video, video-edit) and input requirements. Does not explicitly list when not to use, but context is clear.

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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