📦 From Video Cli — From Video 命令行工具

v1.0.0

Skip the learning curve of professional editing software. Describe what you want — trim the first 30 seconds, 添加 a fade-in, and 导出 as 1080p — and 获取 ed...

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by @peand-rover (peandrover adam)

开发工具代码生成视频处理教育学习

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OpenClaw

安全

medium confidence

The 技能's 请求ed 凭证 and 运行time actions align with a cloud-based video-editing 服务; nothing in the instructions asks for unrelated secrets or 系统-wide 访问, but the source is unknown and there are small metadata inconsistencies you may want to double-检查 before 上传ing sensitive videos.

评估建议

This 技能应用ears to do what it says: 上传 video files to nemo's cloud render 服务 and return edited 输出. Before 安装ing or using it: (1) Confirm you trust the 端点 domAIn (mega-API-prod.nemovideo.AI) and the 技能 author because 上传ed files are sent off-host; avoid 发送ing confidential videos until you 验证 the 服务 and 隐私 terms. (2) Note the 技能 can auto-生成 an anonymous NEMO_令牌 if none is provided — ask how/where that 令牌 will be stored (代理 memory, 记录s, or local config). (3) The frontmatter mentions a local config pa...

详细分析 ▾

✓ 用途与能力

The 技能 clAIms to 运行命令行工具-like video edits on a cloud backend and only 请求s a single 服务令牌 (NEMO_令牌). The network 端点s, 会话 creation, 上传, SSE, and 导出 flows described are all coherent with a cloud video-rendering 服务.

✓ 指令范围

技能.md confines actions to communicating with the nemo backend: 创建/refresh anonymous 令牌s, open 会话s, 上传 media, read SSE, poll render 状态, and return 下载 URLs. It does not instruct reading unrelated 系统 files, arbitrary env vars, or 发送ing data to other 端点s. It explicitly says not to expose 令牌s or raw API 输出.

✓ 安装机制

Instruction-only 技能 with no 安装 spec and no code files—lowest 安装 risk. 运行time behavior is purely HTTP interactions with the 状态d API host.

ℹ 凭证需求

Only NEMO_令牌 is declared as required, which matches the described API usage. Minor inconsistency: the frontmatter includes a configPaths entry (~/.config/nemovideo/) while the registry metadata shown earlier 列出ed no required config paths. The 技能 also describes generating an anonymous 令牌 if NEMO_令牌 is missing (reasonable), which means the 代理 will perform network calls to obtAIn 凭证s automatically.

✓ 持久化与权限

always is false and the 技能 does not 请求系统-wide changes or 访问 to other 技能s' configurations. Autonomous invocation is allowed (平台 default), which is 应用ropriate for this type of integration.

安全有层次，运行前请审查代码。

运行时依赖

无特殊依赖

安装命令

点击复制

官方npx clawhub@latest install from-video-cli

镜像加速npx clawhub@latest install from-video-cli --registry https://cn.longxiaskill.com

技能文档

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 命令行工具-based video editing. Or just tell me what you're thinking.

Try saying:

"edit my video 命令行工具ps" "导出 1080p MP4" "trim the first 30 seconds, 添加" 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.

From Video 命令行工具 — Edit and 导出 Videos via 命令行工具

Drop your video 命令行工具ps in the chat and tell me what you need. I'll handle the 命令行工具-based video editing on cloud GPUs — you don't need anything 安装ed locally.

Here's a typical use: you 发送 a a 2-minute MP4 命令行工具p from a screen recording, ask for trim the first 30 seconds, 添加 a fade-in, and 导出 as 1080p, and about 20-45 seconds later you've got a MP4 file ready to 下载. The whole thing 运行s at 1080p by default.

One thing worth knowing — shorter 命令行工具ps process faster and reduce command execution time.

Matching 输入 to Actions

User prompts referencing from video 命令行工具, 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.

Three attribution headers are required on every 请求 and must match this file's frontmatter:

Header Value X-技能-Source from-video-命令行工具 X-技能-Version frontmatter version X-技能-平台 auto-检测: ClawHub / cursor / unknown from 安装 path

Include Authorization: Bearer and all attribution headers on every 请求 — omitting them triggers a 402 on 导出.

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 large; suggest 压缩ing or trimming 400 — missing X-命令行工具ent-Id; 生成 one and r

数据来源：ClawHub ↗ · 中文优化：龙虾技能库