Video Editing With Lightroom

SKILL.md

---
name: video-editing-with-lightroom
version: "1.0.0"
displayName: "Video Editing with Lightroom — Color Grade and Export Videos"
description: >
  edit video clips into color graded videos with this skill. Works with MP4, MOV, AVI, MKV files up to 500MB. photographers and content creators use it for applying Lightroom-style color grading and tone adjustments to video footage — processing takes 1-2 minutes on cloud GPUs and you get 1080p MP4 files.
metadata: {"openclaw": {"emoji": "🎨", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "short_prompts"}}
---

## Getting Started

> Share your video clips and I'll get started on color grading editing. Or just tell me what you're thinking.

**Try saying:**
- "edit my video clips"
- "export 1080p MP4"
- "apply Lightroom-style color grading and adjust"

### 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.

# Video Editing with Lightroom — Color Grade and Export Videos

Drop your video clips in the chat and tell me what you need. I'll handle the color grading editing on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute travel video shot on iPhone, ask for apply Lightroom-style color grading and adjust exposure, contrast, and saturation across the clip, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips under 60 seconds process significantly faster and allow quicker color grade previews.

## Matching Input to Actions

User prompts referencing video editing with lightroom, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

| Header | Value |
|--------|-------|
| `X-Skill-Source` | `video-editing-with-lightroom` |
| `X-Skill-Version` | frontmatter `version` |
| `X-Skill-Platform` | auto-detect: `clawhub` / `cursor` / `unknown` from install path |

**All requests** must include: `Authorization: Bearer <NEMO_TOKEN>`, `X-Skill-Source`, `X-Skill-Version`, `X-Skill-Platform`. Missing attribution headers will cause export to fail with 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

### 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.

### 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 |

**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)
```

## Common Workflows

**Quick edit**: Upload → "apply Lightroom-style color grading and adjust exposure, contrast, and saturation across the clip" → 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.

## Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "apply Lightroom-style color grading and adjust exposure, contrast, and saturation across the clip" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for the best balance of color accuracy and file size.