Editor Kids
/install editor-kids
Getting Started
Got raw video footage to work with? Send it over and tell me what you need — I'll take care of the AI kids video editing.
Try saying:
- "edit a 2-minute birthday party recording into a 1080p MP4"
- "cut out boring parts, add fun transitions and upbeat background music for kids"
- "editing family and kids videos with fun effects and music for parents and family content creators"
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: \x3Cuuid>. 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.
Editor Kids — Edit and Export Kids Videos
Drop your raw video footage in the chat and tell me what you need. I'll handle the AI kids video editing on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a 2-minute birthday party recording, ask for cut out boring parts, add fun transitions and upbeat background music for kids, 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 3 minutes process faster and give cleaner AI edit results.
Matching Input to Actions
User prompts referencing editor kids, 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:
- Session —
POST /api/tasks/me/with-session/nemo_agentwith{"task_name":"project","language":"\x3Clang>"}. Gives you asession_id. - Chat (SSE) —
POST /run_ssewithsession_idand your message innew_message.parts[0].text. SetAccept: text/event-stream. Up to 15 min. - Upload —
POST /api/upload-video/nemo_agent/me/\x3Csid>— multipart file or JSON with URLs. - Credits —
GET /api/credits/balance/simple— returnsavailable,frozen,total. - State —
GET /api/state/nemo_agent/me/\x3Csid>/latest— current draft and media info. - Export —
POST /api/render/proxy/lambdawith render ID and draft JSON. PollGET /api/render/proxy/lambda/\x3Cid>every 30s forcompletedstatus 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:editor-kidsX-Skill-Version: from frontmatterversionX-Skill-Platform: detect from install path (~/.clawhub/→clawhub,~/.cursor/skills/→cursor, elseunknown)
Every API call needs Authorization: Bearer \x3CNEMO_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)
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
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 normally1001— token expired or invalid; re-acquire via/api/auth/anonymous-token1002— session not found; create a new one2001— out of credits; anonymous users get a registration link with?bind=\x3Cid>, registered users top up4001— unsupported file type; show accepted formats4002— file too large; suggest compressing or trimming400— missingX-Client-Id; generate one and retry402— free plan export blocked; not a credit issue, subscription tier429— rate limited; wait 30s and retry once
Common Workflows
Quick edit: Upload → "cut out boring parts, add fun transitions and upbeat background music for kids" → 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 "cut out boring parts, add fun transitions and upbeat background music for kids" — 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 devices and sharing platforms.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install editor-kids - 安装完成后,直接呼叫该 Skill 的名称或使用
/editor-kids触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Editor Kids 是什么?
edit raw video footage into kid-friendly edited videos with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. parents and family content creators... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 70 次。
如何安装 Editor Kids?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install editor-kids」即可一键安装,无需额外配置。
Editor Kids 是免费的吗?
是的,Editor Kids 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Editor Kids 支持哪些平台?
Editor Kids 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Editor Kids?
由 whitejohnk-26(@whitejohnk-26)开发并维护,当前版本 v1.0.0。