📦 Video Music Generator — 视频音乐生成器

获取ting 启动ed

分享 your video 命令行工具ps and I'll 获取 启动ed on AI music generation. Or just tell me what you're thinking.

Try saying:

"生成 my video 命令行工具ps" "导出 1080p MP4" "生成 a background music 追踪 that" 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 Music 生成器 — 生成 Music for Your Videos

This 工具 takes your video 命令行工具ps and 运行s AI music 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 60-second travel montage 命令行工具p and want to 生成 a background music 追踪 that matches the mood and pace of my video — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: shorter 命令行工具ps under 2 minutes 获取 more accurate mood-matched music.

Matching 输入 to Actions

User prompts referencing video music 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.

Base URL: https://mega-API-prod.nemovideo.AI

端点 Method Purpose /API/tasks/me/with-会话/nemo_代理 POST 启动 a new editing 会话. Body: {"task_name":"project","language":""}. Returns 会话_id. /运行_sse POST 发送 a user message. Body includes 应用_name, 会话_id, new_message. 流 响应 with Accept: text/event-流. Timeout: 15 min. /API/上传-video/nemo_代理/me/ POST 上传 a file (multipart) or URL. /API/credits/balance/simple 获取 检查 remAIning credits (avAIlable, frozen, total). /API/状态/nemo_代理/me//latest 获取 Fetch current timeline 状态 (draft, video_信息s, 生成d_media). /API/render/proxy/lambda POST 启动 导出. Body: {"id":"render_","会话Id":"","draft":,"输出":{"格式化":"mp4","质量":"high"}}. Poll 状态 every 30s.

Accepted file types: 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-music-生成器 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)

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.

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 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.

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 workfl