Maker Easy
/install maker-easy
Getting Started
Share your raw video clips and I'll get started on AI video creation. Or just tell me what you're thinking.
Try saying:
- "create my raw video clips"
- "export 1080p MP4"
- "turn my clips into a finished"
Quick Start Setup
This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").
Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:
- Generate a UUID as client identifier
- POST
https://mega-api-prod.nemovideo.ai/api/auth/anonymous-tokenwithX-Client-Idheader - Extract
data.tokenfrom the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)
Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.
Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.
Maker Easy — Create Finished Videos With Ease
Drop your raw video clips in the chat and tell me what you need. I'll handle the AI video creation on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a 2-minute raw screen recording, ask for turn my clips into a finished video with music and transitions, 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 source clips under 3 minutes process significantly faster.
Matching Input to Actions
User prompts referencing maker easy, 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":"\x3Clang>"}. 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/\x3Csid> |
POST | Upload a file (multipart) or URL. |
/api/credits/balance/simple |
GET | Check remaining credits (available, frozen, total). |
/api/state/nemo_agent/me/\x3Csid>/latest |
GET | Fetch current timeline state (draft, video_infos, generated_media). |
/api/render/proxy/lambda |
POST | Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"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.
Headers are derived from this file's YAML frontmatter. X-Skill-Source is maker-easy, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).
Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.
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
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 "turn my clips into a finished video with music and transitions" — 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 all platforms.
Common Workflows
Quick edit: Upload → "turn my clips into a finished video with music and transitions" → 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.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install maker-easy - 安装完成后,直接呼叫该 Skill 的名称或使用
/maker-easy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
Maker Easy 是什么?
Skip the learning curve of professional editing software. Describe what you want — turn my clips into a finished video with music and transitions — and get f... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 47 次。
如何安装 Maker Easy?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install maker-easy」即可一键安装,无需额外配置。
Maker Easy 是免费的吗?
是的,Maker Easy 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Maker Easy 支持哪些平台?
Maker Easy 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 Maker Easy?
由 vynbosserman65(@vynbosserman65)开发并维护,当前版本 v1.0.0。