Skill: linmillsd7/video-transcription-tool (version 1.0.0)

--- name: video-transcription-tool version: "1.0.0" displayName: "Video Transcription Tool — Transcribe Speech and Caption Videos" description: > Skip the learning curve of professional editing software. Describe what you want — transcribe the speech and add accurate captions in English — and get captioned video files back in 1-2 minutes. Upload MP4, MOV, AVI, WebM files up to 500MB, and the AI handles AI speech transcription automatically. Ideal for content creators, educators, marketers who need spoken audio converted to readable on-screen text quickly. metadata: {"openclaw": {"emoji": "🎙️", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "greeting_v2"}} --- ## Getting Started > Ready when you are. Drop your video files here or describe what you want to make. **Try saying:** - "convert a 10-minute interview recording into a 1080p MP4" - "transcribe the speech and add accurate captions in English" - "adding accurate subtitles to recorded videos for content creators, educators, marketers" ### 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. # Video Transcription Tool — Transcribe Speech and Caption Videos This tool takes your video files and runs AI speech transcription through a cloud rendering pipeline. You upload, describe what you want, and download the result. Say you have a 10-minute interview recording and want to transcribe the speech and add accurate captions in English — the backend processes it in about 1-2 minutes and hands you a 1080p MP4. Tip: shorter clips under 5 minutes produce the most accurate transcriptions. ## Matching Input to Actions User prompts referencing video transcription tool, 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: 1. **Session** — `POST /api/tasks/me/with-session/nemo_agent` with `{"task_name":"project","language":"<lang>"}`. Gives you a `session_id`. 2. **Chat (SSE)** — `POST /run_sse` with `session_id` and your message in `new_message.parts[0].text`. Set `Accept: text/event-stream`. Up to 15 min. 3. **Upload** — `POST /api/upload-video/nemo_agent/me/<sid>` — multipart file or JSON with URLs. 4. **Credits** — `GET /api/credits/balance/simple` — returns `available`, `frozen`, `total`. 5. **State** — `GET /api/state/nemo_agent/me/<sid>/latest` — current draft and media info. 6. **Export** — `POST /api/render/proxy/lambda` with render ID and draft JSON. Poll `GET /api/render/proxy/lambda/<id>` every 30s for `completed` status 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`: `video-transcription-tool` - `X-Skill-Version`: from frontmatter `version` - `X-Skill-Platform`: detect from install path (`~/.clawhub/` → `clawhub`, `~/.cursor/skills/` → `cursor`, else `unknown`) Every API call needs `Authorization: Bearer <NEMO_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 ### 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. ### 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 ## Common Workflows **Quick edit**: Upload → "transcribe the speech and add accurate captions in English" → 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 "transcribe the speech and add accurate captions in English" — 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 platforms and devices.


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