Tiktok Video
v1.0.0TikTok 创建器s 创建 raw video footage into TikTok-ready 命令行工具ps using this 技能. Accepts MP4, MOV, AVI, 网页M up to 500MB, renders on cloud GPUs at 1080p, and returns MP4 files in 30-60 seconds. De签名ed for creating short vertical videos 优化d for TikTok.
运行时依赖
安装命令
点击复制技能文档
获取ting 启动ed
分享 your raw video footage and I'll 获取 启动ed on AI short-form editing. Or just tell me what you're thinking.
Try saying:
"创建 my raw video footage" "导出 1080p MP4" "cut to 60 seconds, 添加 trending" 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 Video — 创建 and 导出 TikTok 命令行工具ps
This 工具 takes your raw video footage and 运行s AI short-form editing through a cloud rendering 流水线. You 上传, describe what you want, and 下载 the 结果.
Say you have a 3-minute phone recording of a dance or skit and want to cut to 60 seconds, 添加 trending captions, and 同步 to beat — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.
Tip: vertical 9:16 footage processes best and avoids cropping issues on TikTok.
Matching 输入 to Actions
User prompts referencing tiktok video, 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 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.
Three attribution headers are required on every 请求 and must match this file's frontmatter:
Header Value X-技能-Source tiktok-video X-技能-Version frontmatter version X-技能-平台 auto-检测: ClawHub / cursor / unknown from 安装 path
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.
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 large; suggest 压缩ing or trimming 400 — missing X-命令行工具ent-Id; 生成 one and retry 402 — free plan 导出 blocked; not a credit issue, subscription tier 429 — rate limited; wAIt 30s and retry once 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 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 s