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Skillv1.0.0

video-upscaler

Intelligently upscale and enhance videos to cinematic quality using a multi-model backend (Topaz, SeedVR2).

by wells1137(0) 0 installs
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About

Imported from wells1137/media-skills (skills/video-upscaler/SKILL.md). Install upstream with npx skills add wells1137/media-skills --skill video-upscaler. Copyright stays with the author.

Summary

The Video Upscaler skill provides professional-grade video quality enhancement by leveraging a powerful, multi-model backend. It intelligently selects the best AI model (Topaz, SeedVR2, etc.) based on the user-defined profile to achieve optimal results, transforming low-resolution or noisy footage into crisp, cinematic-quality video.

This skill abstracts away the complexity of choosing and configuring different AI upscaling models. Instead of dealing with dozens of technical parameters, the user simply chooses a high-level goal, and the skill handles the rest.

Features

  • Multi-Model Backend: Dynamically routes requests to the best model for the job (Topaz, SeedVR2, etc.) via a unified API.
  • Profile-Based Enhancement: Offers a range of pre-configured profiles for common use cases, from standard 2x upscaling to 4K cinematic conversion and 60 FPS frame boosting.
  • Asynchronous by Design: Handles long-running video processing jobs without blocking the agent.
  • Simple Interface: Requires only a video URL and a profile name to start.

How It Works

The skill operates in a simple, two-step asynchronous workflow:

  1. Submit Job: The agent calls the /upscale endpoint with a video URL and a profile name. The service validates the request, selects the appropriate AI model, and submits the job to the fal.ai backend. It immediately returns a task_id.

  2. Poll for Status: The agent uses the task_id to periodically call the /status/{task_id} endpoint. The status will be queued, in_progress, or completed. Once completed, the response will contain the URL of the final, upscaled video.

Available Profiles

Profile Name Description
standard_x2 2x upscale using Topaz Proteus v4. Best all-around quality for live-action footage.
cinema_4k Upscale to 4K (2160p) using SeedVR2. Best for cinematic content requiring temporal consistency.
frame_boost_60fps 2x upscale + frame interpolation to 60 FPS using Topaz Apollo v8. Best for sports and action.
ai_video_enhance 4x upscale using Topaz. Best for AI-generated videos that need resolution boosting.
web_optimized Upscale to 1080p with web-optimized H264 output. Best for social media and web publishing.

End-to-End Example

User Request: "Enhance this video to 4K cinematic quality: [video_url]"

1. Agent -> Skill (Submit Job)

The agent identifies the user's intent and calls the /upscale endpoint with the cinema_4k profile.

curl -X POST http://<your_backend_url>/upscale \
  -H "Content-Type: application/json" \
  -d 
    "video_url": "[video_url]",
    "profile": "cinema_4k"
  }

Response:

{
  "task_id": "a1b2c3d4-e5f6-7890-1234-567890abcdef",
  "model_used": "fal-ai/seedvr/upscale/video",
  "profile": "cinema_4k"
}

2. Agent -> Skill (Poll for Status)

The agent waits and then polls the status endpoint.

curl http://<your_backend_url>/status/a1b2c3d4-e5f6-7890-1234-567890abcdef

Response (In Progress):

{
  "task_id": "a1b2c3d4-e5f6-7890-1234-567890abcdef",
  "status": "in_progress",
  "logs": ["Processing frame 100/1200..."]
}

Response (Completed):

{
  "task_id": "a1b2c3d4-e5f6-7890-1234-567890abcdef",
  "status": "completed",
  "result": {
    "video_url": "https://.../upscaled_video.mp4"
  }
}

3. Agent -> User

The agent delivers the final, upscaled video URL to the user.

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

yaml
targets:
  - https://api.opensmartroute.ai/api/v1/registry/wells1137-media-skills-video-upscaler/manifest   # or paste the manifest below

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

wells1137-media-skills-video-upscaler.ocm.jsonjson
{
  "ocm": "1",
  "id": "wells1137-media-skills-video-upscaler",
  "kind": "skill",
  "name": "video-upscaler",
  "description": "Intelligently upscale and enhance videos to cinematic quality using a multi-model backend (Topaz, SeedVR2).",
  "publisher": "wells1137",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "general"
    ],
    "tags": [
      "skill-md",
      "video",
      "upscale",
      "enhance",
      "topaz",
      "seedvr",
      "4k",
      "quality",
      "github"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "Intelligently upscale and enhance videos to cinematic quality using a multi-model backend (Topaz, SeedVR2)."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "github",
      "repository": "https://github.com/wells1137/media-skills",
      "path": "skills/video-upscaler/SKILL.md",
      "ref": "6329ad5530c9a01a71e8ed50b82e49fd5f4dc8c0",
      "url": "https://github.com/wells1137/media-skills/blob/6329ad5530c9a01a71e8ed50b82e49fd5f4dc8c0/skills/video-upscaler/SKILL.md",
      "key": "wells1137/media-skills/skills/video-upscaler/SKILL.md"
    }
  },
  "instructions": "## Summary\n\nThe **Video Upscaler** skill provides professional-grade video quality enhancement by leveraging a powerful, multi-model backend. It intelligently selects the best AI model (Topaz, SeedVR2, etc.) based on the user-defined profile to achieve optimal results, transforming low-resolution or noisy footage into crisp, cinematic-quality video.\n\nThis skill abstracts away the complexity of choosing and configuring different AI upscaling models. Instead of dealing with dozens of technical parameters, the user simply chooses a high-level goal, and the skill handles the rest.\n\n## Features\n\n- ",
  "cost": {
    "context_tokens": 876
  }
}

Fetch it by URL: GET /api/v1/registry/wells1137-media-skills-video-upscaler/manifest?version=1.0.0

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