opencode Skill

muapi-music-video

Build a short music video from a song theme — N keyframes, animate each, generate matching music.

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samuraigpt/generative-media-skills 4295 492 forks MIT Updated 16d ago

Part of samuraigpt/generative-media-skills — 72 skills

Install

skills CLI npx skills add https://github.com/SamurAIGPT/Generative-Media-Skills/tree/main/library/motion/music-video

Claude Code

claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install samuraigpt-generative-media-skills@llmmart

Git git clone https://github.com/SamurAIGPT/Generative-Media-Skills.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole samuraigpt/generative-media-skills collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

Music Video

Build a short music video from a song theme — N keyframes, animate each, generate matching music.

Inputs

Name	Type	Required	Default	Description
`theme`	text	yes	—	Song / video theme (e.g. "lonely robot finds a friend, hopeful").
`scenes`	int	no	3	Number of scenes (each becomes a 5s clip).
`music_style`	text	no	ambient cinematic, instrumental, slow tempo, warm	Suno-style tags for the soundtrack.
`visual_style`	text	no	cinematic, photoreal, soft volumetric light, 16:9

Steps

Build one the plan covering:

Layer A (parallel) — N keyframes + 1 music track all at once.
- For each scene 1..N: muapi image generate with a beat-specific prompt + {{visual_style}}, model=nano-banana-pro (these feed video gen).
- One muapi audio create (kind=music) using {{music_style}}, duration = N × 5 + a 2s tail.
Layer B (parallel, depends on Layer A) — animate each keyframe.
- For each scene: muapi video from-image with image=$nX.url, model=veo3.1-image-to-video, duration=5, prompt=scene-specific motion direction.
Return:
- The scene keyframes (asset ids in order).
- The animation clips (asset ids in order).
- The music track asset id.
- A short summary describing the cut order.

Notes

Keep character continuity by repeating the character description in every scene prompt verbatim.
Don't auto-confirm any single video call > 50 cr — those need the user's nod (the loop will prompt automatically).
If a scene's muapi video from-image fails after failover, fall back to muapi video generate (text-to-video) for that scene only.

Trigger Keywords

music video, mv, video story, song visualization

Notes for the Executing Agent

This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call muapi CLI commands. Use muapi auth configure first if MUAPI_API_KEY is unset.
For model IDs without a CLI alias yet, fall back to the raw endpoint via curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}' and poll with muapi predict wait <request_id>.
Substitute {{input_name}} placeholders with the user's actual inputs before issuing each call.

Files (generative-media-skills)

SKILL.md 2.5 KB

---
slug: muapi-music-video
name: muapi-music-video
version: "1.0.0"
description: Build a short music video from a song theme — N keyframes, animate each, generate matching music.
acceptLicenseTerms: true
---


# Music Video

**Build a short music video from a song theme — N keyframes, animate each, generate matching music.**

## Inputs

| Name | Type | Required | Default | Description |
|:---|:---|:---|:---|:---|
| `theme` | text | yes | — | Song / video theme (e.g. "lonely robot finds a friend, hopeful"). |
| `scenes` | int | no | 3 | Number of scenes (each becomes a 5s clip). |
| `music_style` | text | no | ambient cinematic, instrumental, slow tempo, warm | Suno-style tags for the soundtrack. |
| `visual_style` | text | no | cinematic, photoreal, soft volumetric light, 16:9 |  |


## Steps

Build one the plan covering:

1. **Layer A (parallel)** — N keyframes + 1 music track all at once.
   - For each scene 1..N: `muapi image generate` with a beat-specific prompt +
     `{{visual_style}}`, model=nano-banana-pro (these feed video gen).
   - One `muapi audio create` (kind=music) using `{{music_style}}`, duration =
     N × 5 + a 2s tail.
2. **Layer B (parallel, depends on Layer A)** — animate each keyframe.
   - For each scene: `muapi video from-image` with `image=$nX.url`, model=veo3.1-image-to-video,
     duration=5, prompt=scene-specific motion direction.
3. Return:
   - The scene keyframes (asset ids in order).
   - The animation clips (asset ids in order).
   - The music track asset id.
   - A short summary describing the cut order.

## Notes
- Keep character continuity by repeating the character description in every
  scene prompt verbatim.
- Don't auto-confirm any single video call > 50 cr — those need the user's
  nod (the loop will prompt automatically).
- If a scene's `muapi video from-image` fails after failover, fall back to
  `muapi video generate` (text-to-video) for that scene only.

## Trigger Keywords

`music video`, `mv`, `video story`, `song visualization`


---

## Notes for the Executing Agent

- This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call `muapi` CLI commands. Use `muapi auth configure` first if `MUAPI_API_KEY` is unset.
- For model IDs without a CLI alias yet, fall back to the raw endpoint via `curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}'` and poll with `muapi predict wait <request_id>`.
- Substitute `{{input_name}}` placeholders with the user's actual inputs before issuing each call.