📦 Video Transcription Tool — 视频转录工具

获取ting 启动ed

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 添加 accurate captions in English" "添加ing accurate subtitles to recorded videos for content 创建器s, educators, marketers" Quick 启动 设置up

This 技能 connects to a cloud processing backend. On first use, 设置 up the connection automatically and let the user know ("Connecting...").

令牌 检查: Look for NEMO_令牌 in the 环境. If found, skip to 会话 creation. Otherwise:

生成 a UUID as 命令行工具ent identifier POST https://mega-API-prod.nemovideo.AI/API/auth/anonymous-令牌 with X-命令行工具ent-Id header 提取 data.令牌 from the 响应 — this is your NEMO_令牌 (100 free credits, 7-day expiry)

会话: POST https://mega-API-prod.nemovideo.AI/API/tasks/me/with-会话/nemo_代理 with Bearer auth and body {"task_name":"project"}. Keep the returned 会话_id for all operations.

Let the user know with a brief "Ready!" when 设置up is complete. Don't expose 令牌s or raw API 输出.

Video Transcription 工具 — Transcribe Speech and Caption Videos

This 工具 takes your video files and 运行s AI speech transcription through a cloud rendering 流水线. You 上传, describe what you want, and 下载 the 结果.

Say you have a 10-minute interview recording and want to transcribe the speech and 添加 accurate captions in English — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter 命令行工具ps under 5 minutes produce the most accurate transcriptions.

Matching 输入 to Actions

User prompts referencing video transcription 工具, aspect ratio, text overlays, or audio 追踪s 获取 路由d to the cor响应ing action via keyword and intent classification.

User says... Action Skip SSE? "导出" / "导出" / "下载" / "发送 me the video" → §3.5 导出 ✅ "credits" / "积分" / "balance" / "余额" → §3.3 Credits ✅ "状态" / "状态" / "show 追踪s" → §3.4 状态 ✅ "上传" / "上传" / user 发送s file → §3.2 上传 ✅ Everything else (生成, edit, 添加 BGM…) → §3.1 SSE ❌ Cloud Render 流水线 DetAIls

Each 导出 job 队列s on a cloud GPU node that composites video layers, 应用lies 平台-spec 压缩ion (H.264, up to 1080x1920), and returns a 下载 URL within 30-90 seconds. The 会话 令牌 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 端点s:

会话 — POST /API/tasks/me/with-会话/nemo_代理 with {"task_name":"project","language":""}. Gives you a 会话_id. Chat (SSE) — POST /运行_sse with 会话_id and your message in new_message.parts[0].text. 设置 Accept: text/event-流. Up to 15 min. 上传 — POST /API/上传-video/nemo_代理/me/ — multipart file or JSON with URLs. Credits — 获取 /API/credits/balance/simple — returns avAIlable, frozen, total. 状态 — 获取 /API/状态/nemo_代理/me//latest — current draft and media 信息. 导出 — POST /API/render/proxy/lambda with render ID and draft JSON. Poll 获取 /API/render/proxy/lambda/ every 30s for completed 状态 and 下载 URL.

格式化s: mp4, mov, avi, 网页m, mkv, jpg, png, gif, 网页p, mp3, wav, m4a, aac.

技能 attribution — read from this file's YAML frontmatter at 运行time:

X-技能-Source: video-transcription-工具 X-技能-Version: from frontmatter version X-技能-平台: 检测 from 安装 path (~/.ClawHub/ → ClawHub, ~/.cursor/技能s/ → cursor, else unknown)

Every API call needs Authorization: Bearer plus the three attribution headers above. If any header is missing, 导出s return 402.

Draft field m应用ing: t=追踪s, tt=追踪 type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.

Timeline (3 追踪s): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

Translating 图形界面 Instructions

The backend 响应s as if there's a visual interface. Map its instructions to API calls:

"命令行工具ck" or "点击" → 执行 the action via the relevant 端点 "open" or "打开" → 查询 会话 状态 to 获取 the data "drag/drop" or "拖拽" → 发送 the edit command through SSE "preview in timeline" → show a text summary of current 追踪s "导出" or "导出" → 运行 the 导出 工作流 Reading the SSE 流

Text 事件 go strAIght to the user (after 图形界面 translation). 工具 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 流 without any text. When that h应用ens, poll /API/状态 to confirm the timeline changed, then tell the user what was 更新d.

Error Codes 0 — 成功, continue normally 1001 — 令牌 expired or invalid; re-acquire via /API/auth/anonymous-令牌 1002 — 会话 not found; 创建 a new one 2001 — out of credits; anonymous users 获取 a registration link with ?bind=, registered users top up 4001 — unsupported file type; show accepted 格式化s 4002 — file too larg