Skill: vynbosserman65/ai-video-editor-hindi (version 1.0.0)

--- name: ai-video-editor-hindi version: "1.0.0" displayName: "AI Video Editor Hindi — Edit Hindi Videos with AI" description: > Get edited Hindi videos ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something like "add Hindi subtitles, trim pauses, and add background music", and download 1080p MP4 when it's done. Built for Hindi content creators who move fast and want to edit Hindi videos quickly without professional editing skills. metadata: {"openclaw": {"emoji": "🎬", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "short_prompts"}} --- ## Getting Started > Share your raw video footage and I'll get started on AI Hindi video editing. Or just tell me what you're thinking. **Try saying:** - "edit my raw video footage" - "export 1080p MP4" - "add Hindi subtitles, trim pauses, and" ### 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-token` with `X-Client-Id` header - Extract `data.token` from 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. # AI Video Editor Hindi — Edit Hindi Videos with AI Drop your raw video footage in the chat and tell me what you need. I'll handle the AI Hindi video editing on cloud GPUs — you don't need anything installed locally. Here's a typical use: you send a a 2-minute Hindi vlog recorded on a smartphone, ask for add Hindi subtitles, trim pauses, and add background music, 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 — uploading clips under 5 minutes gives faster and more accurate Hindi subtitle generation. ## Matching Input to Actions User prompts referencing ai video editor hindi, 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. Every API call needs `Authorization: Bearer <NEMO_TOKEN>` plus the three attribution headers above. If any header is missing, exports return 402. Headers are derived from this file's YAML frontmatter. `X-Skill-Source` is `ai-video-editor-hindi`, `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`). **API base**: `https://mega-api-prod.nemovideo.ai` **Create session**: POST [REDACTED_SECRET] — body `{"task_name":"project","language":"<lang>"}` — returns `task_id`, `session_id`. **Send message (SSE)**: POST `/run_sse` — body `{"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}}` with `Accept: text/event-stream`. Max timeout: 15 minutes. **Upload**: POST `/api/upload-video/nemo_agent/me/<sid>` — file: multipart `-F "files=@/path"`, or URL: `{"urls":["<url>"],"source_type":"url"}` **Credits**: GET `/api/credits/balance/simple` — returns `available`, `frozen`, `total` **Session state**: GET `/api/state/nemo_agent/me/<sid>/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_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}`. Poll GET `/api/render/proxy/lambda/<id>` 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 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 ### 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 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 → "add Hindi subtitles, trim pauses, and add background music" → 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 "add Hindi subtitles, trim pauses, and add background music" — 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 YouTube, Instagram, and WhatsApp.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)