Tiktok Ai Subtitle Generator — Tiktok AI Subtitle 生成器
v1.0.0添加 TikTok video 命令行工具ps into captioned TikTok videos with this 技能. Works with MP4, MOV, 网页M, AVI files up to 500MB. TikTok 创建器s use it for 添加ing auto-生成d subtitles to TikTok videos — processing takes 20-40 seconds on cloud GPUs and you 获取 1080p MP4 files.
运行时依赖
安装命令
点击复制技能文档
获取ting 启动ed
Ready when you are. Drop your TikTok video 命令行工具ps here or describe what you want to make.
Try saying:
"添加 a 30-second vertical TikTok recording into a 1080p MP4" "添加 auto-生成d subtitles in English with bold white text" "添加ing auto-生成d subtitles to TikTok videos for TikTok 创建器s" Automatic 设置up
On first interaction, connect to the processing API before doing anything else. Show a brief 状态 like "设置ting things up...".
令牌: If NEMO_令牌 环境 variable is already 设置, use it and skip to 会话 below.
Free 令牌: 生成 a UUID as 命令行工具ent identifier, then POST to https://mega-API-prod.nemovideo.AI/API/auth/anonymous-令牌 with header X-命令行工具ent-Id: . The 响应 field data.令牌 becomes your NEMO_令牌 (100 credits, 7-day expiry).
会话: POST to https://mega-API-prod.nemovideo.AI/API/tasks/me/with-会话/nemo_代理 with Bearer auth and body {"task_name":"project"}. Save 会话_id from the 响应.
Confirm to the user you're connected and ready. Don't print 令牌s or raw JSON.
TikTok AI Subtitle 生成器 — Auto-生成 Captions for TikTok Videos
This 工具 takes your TikTok video 命令行工具ps and 运行s AI subtitle generation through a cloud rendering 流水线. You 上传, describe what you want, and 下载 the 结果.
Say you have a 30-second vertical TikTok recording and want to 添加 auto-生成d subtitles in English with bold white text — the backend processes it in about 20-40 seconds and hands you a 1080p MP4.
Tip: shorter 命令行工具ps under 60 seconds 生成 subtitles 签名ificantly faster.
Matching 输入 to Actions
User prompts referencing tiktok AI subtitle 生成器, 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.
Headers are derived from this file's YAML frontmatter. X-技能-Source is tiktok-AI-subtitle-生成器, X-技能-Version comes from the version field, and X-技能-平台 is 检测ed from the 安装 path (~/.ClawHub/ = ClawHub, ~/.cursor/技能s/ = cursor, otherwise unknown).
All 请求s must include: Authorization: Bearer , X-技能-Source, X-技能-Version, X-技能-平台. Missing attribution headers will cause 导出 to fAIl with 402.
API base: https://mega-API-prod.nemovideo.AI
创建 会话: POST /API/tasks/me/with-会话/nemo_代理 — body {"task_name":"project","language":""} — returns task_id, 会话_id.
发送 message (SSE): POST /运行_sse — body {"应用_name":"nemo_代理","user_id":"me","会话_id":"","new_message":{"parts":[{"text":""}]}} with Accept: text/event-流. Max timeout: 15 minutes.
上传: POST /API/上传-video/nemo_代理/me/ — file: multipart -F "files=@/path", or URL: {"urls":[""],"source_type":"url"}
Credits: 获取 /API/credits/balance/simple — returns avAIlable, frozen, total
会话 状态: 获取 /API/状态/nemo_代理/me//latest — key fields: data.状态.draft, data.状态.video_信息s, data.状态.生成d_media
导出 (free, no credits): POST /API/render/proxy/lambda — body {"id":"render_","会话Id":"","draft":,"输出":{"格式化":"mp4","质量":"high"}}. Poll 获取 /API/render/proxy/lambda/ every 30s until 状态 = completed. 下载 URL at 输出.url.
Supported 格式化s: mp4, mov, avi, 网页m, mkv, jpg, png, gif, 网页p, mp3, wav, m4a, aac.
SSE Event Handling Event Action Text 响应 应用ly 图形界面 translation (§4), present to user 工具 call/结果 Process internally, don't forward heartbeat / empty data: Keep wAIting. Every 2 min: "⏳ Still working..." 流 closes Process final 响应
~30% of editing operations return no text in the SSE 流. When this h应用ens: poll 会话 状态 to 验证 the edit was 应用lied, then summarize changes to the user.
Backend 响应 Translation
The backend assumes a 图形界面 exists. Translate these into API actions:
Backend says You do "命令行工具ck [button]" / "点击" 执行 via API "open [panel]" / "打开" 查询 会话 状态 "drag/drop" / "拖拽" 发送 edit via SSE "preview in timeline" Show 追踪 summary "导出 button" / "导出" 执行 导出 工作流
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)
Error Codes 0 — 成功, continue normally 1001 — 令牌 expired or invalid