Agent skill · Media & Video

libtv-video

Seedance 2.0 video & image generation via LibTV Gateway - AI text-to-video, image-to-video, video continuation, style transfer, and text-to-image using Seedance 2.0 model. Also supports Kling 3.0, Wan 2.6, Midjourney, Seedream 5.0. Trigger phrases: seedance, generate video, make a video, generate image, make an image, draw, libtv, liblib.

nexu95,528★ · +2,037/wk · 5 repos on radarProfile →
claude-codecodexships scriptsMIT
Install
npx skills add nexu-io/nexu --skill libtv-video --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 14 KB
Bundled scripts: yes
Path: apps/desktop/static/bundled-skills/libtv-video/SKILL.md
Open the folder on GitHub →
Where it comes from
Source: nexu-io/nexu
Stars: 3,239
Language: TypeScript
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# LibTV - Image & Video Generation (Seedance 2.0) Generate AI **images** and **videos** through one bundled LibTV skill, powered by Seedance 2.0. Supports text-to-image, image-to-image, text-to-video, and image-to-video workflows, via both Nexu-managed Seedance execution and direct LibTV execution with a user-owned `sk-libtv-...` key. Key routing: - `mgk_...` keys use Nexu-managed Seedance through `https://seedance.nexu.io/` - `sk-libtv-...` keys use direct LibTV OpenAPI through `https://im.liblib.tv` Delivery architecture (currently Feishu only): - `create-session` captures `OPENCLAW_CHANNEL_TYPE` + `OPENCLAW_CHAT_ID`, persists them as the session's `delivery` block, forks a detached `wait-and-deliver` background process via `subprocess.Popen(..., start_new_session=True)`, and returns immediately with a single-line JSON submit confirmation on stdout. - The forked waiter polls the upstream LibTV API (Seedance gateway or direct LibTV) and, on terminal success, shells out to `feishu_send_video.py` — the same proven helper used by `medeo-video` — which downloads each result URL, uploads it to Feishu's file API, and posts a native media message to the originating chat. - The waiter's o

What's inside
Steps it walks through
  1. Requirements
  2. First-Time Setup
  3. Pre-Generation Check (must run before each generation)
  4. Core Principle: Relay, Don't Create
  5. Video / Image Generation (async, non-blocking)
  6. CRITICAL: always pass --channel and --chat-id
  7. Text-Only Generation
  8. Image+Text Generation (image-to-video)
  9. Continue in Existing Session
  10. After Submission
  11. When the User Asks "Is my video ready?"
  12. Session Recovery (after memory loss / agent restart)
  13. Presenting Results
  14. URL Rules
Ships with 2 files
  • scripts/feishu_send_video.py
  • scripts/libtv_video.py
Commands it runs
python3 scripts/libtv_video.py update-ratio --video-ratio 9:16
python3 scripts/libtv_video.py create-session "user's video description" \
python3 scripts/libtv_video.py upload --file /path/to/image.png
python3 scripts/libtv_video.py create-session "user's description reference: {oss_url}"
python3 scripts/libtv_video.py create-session "new description" \
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About this skill
What does the libtv-video skill do?

Seedance 2.0 video & image generation via LibTV Gateway - AI text-to-video, image-to-video, video continuation, style transfer, and text-to-image using Seedance 2.0 model. Also supports Kling 3.0, Wan 2.6, Midjourney, Seedream 5.0. Trigger phrases: seedance, generate video, make a video, generate image, make an image, draw, libtv, liblib.

How do I install it?

Run `npx skills add nexu-io/nexu --skill libtv-video --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From nexu-io/nexu, a repository with 3,239 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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