Ai Video Editor By Text

SKILL.md

---
name: ai-video-editor-by-text
version: "1.0.0"
displayName: "AI Video Editor by Text — Edit Videos with Text Commands"
description: >
  Turn a 2-minute interview recording into 1080p edited MP4 clips just by typing what you need. Whether it's editing videos by typing plain-text instructions instead of using a timeline or quick social content, drop your raw video footage and describe the result you want. No timeline dragging, no export settings — 30-60 seconds from upload to download.
metadata: {"openclaw": {"emoji": "✂️", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "short_prompts"}}
---

## Getting Started

> Share your raw video footage and I'll get started on text-command AI editing. Or just tell me what you're thinking.

**Try saying:**
- "edit my raw video footage"
- "export 1080p MP4"
- "cut the pauses, add a title"

### First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

**Authentication**: Check if `NEMO_TOKEN` is set in the environment. If it is, skip to step 2.

1. **Obtain a free token**: Generate a random UUID as client identifier. POST to `https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token` with header `X-Client-Id` set to that UUID. The response `data.token` is your NEMO_TOKEN — 100 free credits, valid 7 days.
2. **Create a session**: POST to `https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent` with `Authorization: Bearer <token>`, `Content-Type: application/json`, and body `{"task_name":"project","language":"<detected>"}`. Store the returned `session_id` for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

# AI Video Editor by Text — Edit Videos with Text Commands

This tool takes your raw video footage and runs text-command AI editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 2-minute interview recording and want to cut the pauses, add a title card at the start, and fade to black at the end — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: be specific in your text commands — 'remove the first 10 seconds' works better than 'trim the beginning'.

## Matching Input to Actions

User prompts referencing ai video editor by text, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

| User says... | Action | Skip SSE? |
|-------------|--------|----------|
| "export" / "导出" / "download" / "send me the video" | → §3.5 Export | ✅ |
| "credits" / "积分" / "balance" / "余额" | → §3.3 Credits | ✅ |
| "status" / "状态" / "show tracks" | → §3.4 State | ✅ |
| "upload" / "上传" / user sends file | → §3.2 Upload | ✅ |
| Everything else (generate, edit, add BGM…) | → §3.1 SSE | ❌ |

## Cloud Render Pipeline Details

Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.

Base URL: `https://mega-api-prod.nemovideo.ai`

| Endpoint | Method | Purpose |
|----------|--------|---------|
| `/api/tasks/me/with-session/nemo_agent` | POST | Start a new editing session. Body: `{"task_name":"project","language":"<lang>"}`. Returns `session_id`. |
| `/run_sse` | POST | Send a user message. Body includes `app_name`, `session_id`, `new_message`. Stream response with `Accept: text/event-stream`. Timeout: 15 min. |
| `/api/upload-video/nemo_agent/me/<sid>` | POST | Upload a file (multipart) or URL. |
| `/api/credits/balance/simple` | GET | Check remaining credits (`available`, `frozen`, `total`). |
| `/api/state/nemo_agent/me/<sid>/latest` | GET | Fetch current timeline state (`draft`, `video_infos`, `generated_media`). |
| `/api/render/proxy/lambda` | POST | Start export. Body: `{"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}`. Poll status every 30s. |

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Skill attribution — read from this file's YAML frontmatter at runtime:
- `X-Skill-Source`: `ai-video-editor-by-text`
- `X-Skill-Version`: from frontmatter `version`
- `X-Skill-Platform`: detect from install path (`~/.clawhub/` → `clawhub`, `~/.cursor/skills/` → `cursor`, else `unknown`)

Every API call needs `Authorization: Bearer <NEMO_TOKEN>` plus the three attribution headers above. If any header is missing, exports return 402.

### Error Codes

- `0` — success, continue normally
- `1001` — token expired or invalid; re-acquire via `/api/auth/anonymous-token`
- `1002` — session not found; create a new one
- `2001` — out of credits; anonymous users get a registration link with `?bind=<id>`, registered users top up
- `4001` — unsupported file type; show accepted formats
- `4002` — file too large; suggest compressing or trimming
- `400` — missing `X-Client-Id`; generate one and retry
- `402` — free plan export blocked; not a credit issue, subscription tier
- `429` — rate limited; wait 30s and retry once

### Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty `data:` lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll `/api/state` to confirm the timeline changed, then tell the user what was updated.

### Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

- "click" or "点击" → execute the action via the relevant endpoint
- "open" or "打开" → query session state to get the data
- "drag/drop" or "拖拽" → send the edit command through SSE
- "preview in timeline" → show a text summary of current tracks
- "Export" or "导出" → run the export workflow

Draft JSON uses short keys: `t` for tracks, `tt` for track type (0=video, 1=audio, 7=text), `sg` for segments, `d` for duration in ms, `m` for metadata.

Example timeline summary:
```
Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)
```

## Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut the pauses, add a title card at the start, and fade to black at the end" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.

Export as MP4 for widest compatibility across platforms and devices.

## Common Workflows

**Quick edit**: Upload → "cut the pauses, add a title card at the start, and fade to black at the end" → Download MP4. Takes 30-60 seconds for a 30-second clip.

**Batch style**: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.

**Iterative**: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.