media-craft-skill_skill

This skill helps you generate and edit media using the obra CLI, delivering ready-to-download images, videos, or music.

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GitHub Stars

3

Bundled Files

3 weeks ago

Catalog Refreshed

2 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstart where the catalogue uses aiagentskills.

npx veilstart add skill nanhesam/media-craft-skill --skill media-craft-skill

  • LICENSE1.0 KB
  • README.md1.1 KB
  • SKILL.md9.4 KB

Overview

This skill integrates the obra CLI into an AI agent to generate, edit, transform, and enhance images, videos, and music. It centralizes common media workflows—text-to-image, image-to-video, upscaling, background removal, music generation, and more—under a consistent async-task pattern. Use it whenever a user requests creation or programmatic manipulation of media assets.

How this skill works

Commands are executed through the obra CLI and follow a uniform task model: submit a job, wait for JSON output, and download outputs. Prefer synchronous runs with --wait --json to receive structured results and direct output URLs; use -o <path> to save files immediately. For async use, obra returns a task ID you can poll with obra status <id> --wait --json and then retrieve with obra download <id> -o <dir>.

When to use it

  • Generate images from text prompts (text-to-image) or refine an existing photo (image-to-image).
  • Create or edit videos: text-to-video, image-to-video, video-to-video, motion control, or AI avatars.
  • Produce music, vocals, lyrics, synchronized timestamps, or generate music videos using prior audio tasks.
  • Enhance assets: upscaling, background removal, reframing/outpainting, watermark removal.
  • Automate multi-step pipelines: generate an image, convert to video, then upscale or add audio.

Best practices

  • Always call obra with --wait --json unless the user explicitly requests async behavior to get structured outputs.
  • Use -o <path> when the user wants a local file saved immediately to avoid extra download steps.
  • Write detailed, specific prompts and include parameters (aspect_ratio, seed, negative_prompt) for predictable results.
  • Query obra <type> list and obra <type> info <model> to verify model capabilities and parameter names before running jobs.
  • Chain tasks by capturing task IDs and output URLs from JSON to feed into subsequent steps (e.g., generate -> upscale -> music video).

Example use cases

  • Create a 16:9 cyberpunk cityscape image using a specific text-to-image model and save it locally.
  • Turn a product photo into a scene extension (outpaint) and remove the background for ecommerce assets.
  • Generate an upbeat instrumental track, then create a synchronized music video using the music task IDs.
  • Convert a smartphone clip to an anime-style video, then upscale it for presentation.
  • Produce a talking-head AI avatar video from a headshot and an audio script.

FAQ

Use --wait --json by default to receive a single, structured response with output URLs and metadata. Use async mode only when you need non-blocking submission and plan to poll the task ID later.

How do I supply an input image for edits?

Pass a publicly accessible image URL via --param image_urls=<url> for image-to-image or editing models; local paths are not accepted as image_urls.

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