/install caption-generator-downfall
Getting Started
Ready when you are. Drop your video clips here or describe what you want to make.
Try saying:
- "remove a 2-minute YouTube video with burned-in captions into a 1080p MP4"
- "remove or disable the auto-generated captions from this video"
- "removing unwanted captions from existing videos for 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.
Caption Generator Downfall — Remove or Fix Video Captions
Drop your video clips in the chat and tell me what you need. I'll handle the caption removal editing on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a 2-minute YouTube video with burned-in captions, ask for remove or disable the auto-generated captions from this video, 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 — if captions are burned in rather than a separate track, re-export from source without the subtitle layer for cleaner results.
Matching Input to Actions
User prompts referencing caption generator downfall, 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.
Headers are derived from this file's YAML frontmatter. X-Skill-Source is caption-generator-downfall, 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).
Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.
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)
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
Tips and Tricks
The backend processes faster when you're specific. Instead of "make it look better", try "remove or disable the auto-generated captions from this video" — 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 platform compatibility.
Common Workflows
Quick edit: Upload → "remove or disable the auto-generated captions from this video" → 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 caption-generator-downfall - 安装完成后,直接呼叫该 Skill 的名称或使用
/caption-generator-downfall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
Caption Generator Downfall 是什么?
Get clean captionless videos ready to post, without touching a single slider. Upload your video clips (MP4, MOV, AVI, WebM, up to 500MB), say something like... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 80 次。
如何安装 Caption Generator Downfall?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install caption-generator-downfall」即可一键安装,无需额外配置。
Caption Generator Downfall 是免费的吗?
是的,Caption Generator Downfall 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Caption Generator Downfall 支持哪些平台?
Caption Generator Downfall 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 Caption Generator Downfall?
由 tk8544-b(@tk8544-b)开发并维护,当前版本 v1.0.0。