Ai Wechat Video
/install ai-wechat-video
Getting Started
Got video clips to work with? Send it over and tell me what you need — I'll take care of the AI video optimization.
Try saying:
- "convert a 60-second product demo video into a 1080p MP4"
- "format this video for WeChat Moments with subtitles and a square crop"
- "converting and formatting videos for sharing on WeChat for WeChat content creators"
Getting Connected
Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".
If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:
- Generate a UUID as client identifier
- POST to
https://mega-api-prod.nemovideo.ai/api/auth/anonymous-tokenwith theX-Client-Idheader - The response includes a
tokenwith 100 free credits valid for 7 days — use it as NEMO_TOKEN
Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.
Tell the user you're ready. Keep the technical details out of the chat.
AI WeChat Video — Format and Export WeChat Videos
Drop your video clips in the chat and tell me what you need. I'll handle the AI video optimization on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a 60-second product demo video, ask for format this video for WeChat Moments with subtitles and a square crop, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.
One thing worth knowing — keep videos under 1 minute to match WeChat Moments playback limits.
Matching Input to Actions
User prompts referencing ai wechat video, 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 requests must include: Authorization: Bearer \x3CNEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.
Three attribution headers are required on every request and must match this file's frontmatter:
| Header | Value |
|---|---|
X-Skill-Source |
ai-wechat-video |
X-Skill-Version |
frontmatter version |
X-Skill-Platform |
auto-detect: clawhub / cursor / unknown from install path |
API base: https://mega-api-prod.nemovideo.ai
Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"\x3Clang>"} — returns task_id, session_id.
Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.
Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}
Credits: GET /api/credits/balance/simple — returns available, frozen, total
Session state: GET /api/state/nemo_agent/me/\x3Csid>/latest — key fields: data.state.draft, data.state.video_infos, data.state.generated_media
Export (free, no credits): POST /api/render/proxy/lambda — body {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s until status = completed. Download URL at output.url.
Supported formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.
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
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 |
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.
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 "format this video for WeChat Moments with subtitles and a square crop" — concrete instructions get better results.
Max file size is 200MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.
Export as MP4 with H.264 codec for best WeChat compatibility.
Common Workflows
Quick edit: Upload → "format this video for WeChat Moments with subtitles and a square crop" → 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.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install ai-wechat-video - 安装完成后,直接呼叫该 Skill 的名称或使用
/ai-wechat-video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
Ai Wechat Video 是什么?
Turn a 60-second product demo video into 1080p WeChat-ready videos just by typing what you need. Whether it's converting and formatting videos for sharing on... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 105 次。
如何安装 Ai Wechat Video?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install ai-wechat-video」即可一键安装,无需额外配置。
Ai Wechat Video 是免费的吗?
是的,Ai Wechat Video 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Ai Wechat Video 支持哪些平台?
Ai Wechat Video 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 Ai Wechat Video?
由 mhogan2013-9(@mhogan2013-9)开发并维护,当前版本 v1.0.0。