AI Video Editor Descript — Edit Video by Editing Text

## Getting Started

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

**Try saying:**
- "edit my raw video footage"
- "export 1080p MP4"
- "remove filler words, add captions, and"

### Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

**Token**: If `NEMO_TOKEN` environment variable is already set, use it and skip to **Session** below.

**Free token**: Generate a UUID as client identifier, then POST to `https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token` with header `X-Client-Id: <uuid>`. The response field `data.token` becomes your NEMO_TOKEN (100 credits, 7-day expiry).

**Session**: POST to `https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent` with Bearer auth and body `{"task_name":"project"}`. Save `session_id` from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

# AI Video Editor Descript — Edit Video by Editing Text

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

Say you have a 10-minute interview recording in MP4 and want to remove filler words, add captions, and trim silences automatically — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter segments under 5 minutes process significantly faster and more accurately.

## Matching Input to Actions

User prompts referencing ai video editor descript, 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.

All calls go to `https://mega-api-prod.nemovideo.ai`. The main endpoints:

1. **Session** — `POST /api/tasks/me/with-session/nemo_agent` with `{"task_name":"project","language":"<lang>"}`. Gives you a `session_id`.
2. **Chat (SSE)** — `POST /run_sse` with `session_id` and your message in `new_message.parts[0].text`. Set `Accept: text/event-stream`. Up to 15 min.
3. **Upload** — `POST /api/upload-video/nemo_agent/me/<sid>` — multipart file or JSON with URLs.
4. **Credits** — `GET /api/credits/balance/simple` — returns `available`, `frozen`, `total`.
5. **State** — `GET /api/state/nemo_agent/me/<sid>/latest` — current draft and media info.
6. **Export** — `POST /api/render/proxy/lambda` with render ID and draft JSON. Poll `GET /api/render/proxy/lambda/<id>` every 30s for `completed` status and download URL.

Formats: 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-descript`
- `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.

**Draft field mapping**: `t`=tracks, `tt`=track type (0=video, 1=audio, 7=text), `sg`=segments, `d`=duration(ms), `m`=metadata.

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

### Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

| Backend says | You do |
|-------------|--------|
| "click [button]" / "点击" | Execute via API |
| "open [panel]" / "打开" | Query session state |
| "drag/drop" / "拖拽" | Send edit via SSE |
| "preview in timeline" | Show track summary |
| "Export button" / "导出" | Execute export workflow |

### SSE Event Handling

| Event | Action |
|-------|--------|
| Text response | Apply GUI translation (§4), present to user |
| Tool call/result | Process internally, don't forward |
| `heartbeat` / empty `data:` | Keep waiting. Every 2 min: "⏳ Still working..." |
| Stream closes | Process final response |

~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.

### 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

## Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "remove filler words, add captions, and trim silences automatically" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for widest compatibility across platforms.

## Common Workflows

**Quick edit**: Upload → "remove filler words, add captions, and trim silences automatically" → Download MP4. Takes 1-2 minutes 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.