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📦 Windows

v1.0.0

获取 edited MP4 命令行工具ps ready to post, without touching a single slider. 上传 your raw video 命令行工具ps (MP4, MOV, AVI, WMV, up to 500MB), say something like "trim...

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linmillsd7 头像by @linmillsd7
开发工具代码生成系统工具视频处理微信
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OpenClaw
可疑
medium confidence
该技能看似是一个合法的远程视频编辑前端，但存在多项不一致和隐私风险（token/config 不匹配、文件系统检测指令、自动将用户视频上传至外部域名），安装前请务必了解。
评估建议
This 技能 will 上传 your raw video files to a third-party backend (mega-API-prod.nemovideo.AI) for server-side editing and requires or uses a 令牌 named NEMO_令牌. Before 安装ing: 1) Decide whether you are comfortable 上传ing potentially sensitive videos to an external 服务 without an explicit 隐私/retention policy visible in the 技能; avoid using with confidential material. 2) Note the metadata/registry inconsistency: the 技能 clAIms NEMO_令牌 is required but also has an anonymous-令牌 fallback — clarify with the auth...
详细分析 ▾
⚠ 用途与能力
The 技能's 状态d purpose (remote video editing) matches the network calls and 端点s described (会话 creation, 上传, render). However the registry declares NEMO_令牌 as a required env var while the 技能.md provides an explicit anonymous-令牌 fallback flow (it will POST to the backend to obtAIn a 令牌 if NEMO_令牌 is not 设置). That is an inconsistency: a truly required env var should not be optional. The frontmatter metadata also 列出s a config path (~/.config/nemovideo/) but top-level registry fields show 'Required config paths: none' — another mismatch.
⚠ 指令范围
The 运行time instructions direct the 代理 to obtAIn or use 令牌s, 创建 会话s, 上传 user video files (potentially large and sensitive) and poll/render on remote GPU nodes — all expected for this feature. Concerning items: 技能.md instructs 检测ion of 安装 path to populate an X-技能-平台 header (which implies file系统 访问), and it tells the 代理 to 'don't display raw API 响应s or 令牌 values' (which instructs hiding some internal data from the user). The file-上传 behavior 发送s user content to a third-party domAIn (mega-API-prod.nemovideo.AI) but there is no explicit 隐私/retention policy in the instructions.
✓ 安装机制
Instruction-only 技能 with no 安装 spec and no code files. This is the lowest 安装 risk: nothing is 下载ed or written by an 安装er step as part of the 技能 metadata.
⚠ 凭证需求
Only one 凭证 (NEMO_令牌) is declared as required, which is coherent for a remote API. But the 技能.md provides an anonymous-令牌 generation path if NEMO_令牌 is not 设置; requiring the env var is therefore disproportionate or at least inconsistent. The 技能 will accept and 上传 arbitrary user media to an external 服务; that is a 隐私-sensitive operation and should be called out to users before 凭证s/令牌s are used. No other 凭证s are 请求ed, which is 应用ropriate.
✓ 持久化与权限
该 skill 未标记 always:true，也未请求提升或持久的平台权限。它预期在使用期间通过网络调用运行，无任何迹象表明会修改其他 skill 或系统级设置。
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 windows-video-editor
镜像加速npx clawhub@latest install windows-video-editor --registry https://cn.longxiaskill.com

技能文档

获取ting 启动ed

发送 me your raw video 命令行工具ps and I'll handle the AI video editing. Or just describe what you're after.

Try saying:

"edit a 3-minute 桌面 screen recording into a 1080p MP4" "trim the 暂停s, 添加 transitions, and 导出 as MP4" "editing and trimming video 命令行工具ps on a Windows-style interface for casual 创建器s and Windows users" First-Time Connection

When a user first opens this 技能, connect to the processing backend automatically. Briefly let them know (e.g. "设置ting up...").

Authentication: 检查 if NEMO_令牌 is 设置 in the 环境. If it is, skip to step 2.

ObtAIn a free 令牌: 生成 a random UUID as 命令行工具ent identifier. POST to https://mega-API-prod.nemovideo.AI/API/auth/anonymous-令牌 with header X-命令行工具ent-Id 设置 to that UUID. The 响应 data.令牌 is your NEMO_令牌 — 100 free credits, valid 7 days. 创建 a 会话: POST to https://mega-API-prod.nemovideo.AI/API/tasks/me/with-会话/nemo_代理 with Authorization: Bearer <令牌>, Content-Type: 应用/json, and body {"task_name":"project","language":"<检测ed>"}. Store the returned 会话_id for all subsequent 请求s.

Keep 设置up communication brief. Don't display raw API 响应s or 令牌 values to the user.

Windows Video Editor — Edit and 导出 Video 命令行工具ps

发送 me your raw video 命令行工具ps and describe the 结果 you want. The AI video editing 运行s on remote GPU nodes — nothing to 安装 on your machine.

A quick example: 上传 a 3-minute 桌面 screen recording, type "trim the 暂停s, 添加 transitions, and 导出 as MP4", and you'll 获取 a 1080p MP4 back in roughly 1-2 minutes. All rendering h应用ens server-side.

Worth noting: shorter 命令行工具ps under 2 minutes process 签名ificantly faster.

Matching 输入 to Actions

User prompts referencing windows video editor, 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: windows-video-editor 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)

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

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.

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

数据来源：ClawHub ↗ · 中文优化：龙虾技能库