📦 Video Factory — Video 工厂

v1.0.0

创建 raw video 命令行工具ps into finished MP4 videos with this 技能. Works with MP4, MOV, AVI, 网页M files up to 500MB. content 创建器s and marketers use it for...

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by @francemichaell-15

开发工具代码生成网络工具浏览器自动化文件处理

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可疑

medium confidence

The 技能's behavior (上传ing user videos to a third‑party API) matches its description, but there are multiple small inconsistencies and ambiguous instructions (required env vs anonymous 令牌 flow, unexplAIned config path / 安装-path 检测ion) that merit clarification before use.

评估建议

This 技能 will 上传 any videos you give it to a third‑party 服务 at mega-API-prod.nemovideo.AI and use a NEMO_令牌 to 认证. Before 安装ing: 1) Confirm the 服务/domAIn is legitimate and acceptable for your content (隐私/legal). 2) Ask the 技能 author to clarify: why is NEMO_令牌 labeled 'required' when an anonymous 令牌 flow exists, and why does the frontmatter reference ~/.config/nemovideo/ and 'auto-检测' of 安装 path? 3) If you don't want to tie this to an account, avoid 设置ting a persistent NEMO_令牌 and rely on the anon...

详细分析 ▾

ℹ 用途与能力

The 技能's 状态d purpose (batch video processing via a cloud API) aligns with the 端点s and flows in 技能.md. 请求ing a NEMO_令牌凭证 is reasonable for that purpose. However, the frontmatter references a local config path (~/.config/nemovideo/) that the registry metadata did not 列出, and the 技能.md 机器人h treats NEMO_令牌 as 'required' and documents an anonymous-令牌 flow — those are inconsistent and deserve explanation.

⚠ 指令范围

The instructions direct the 代理 to 上传 user-supplied video files to https://mega-API-prod.nemovideo.AI and to 创建/use 会话令牌s — that is expected for a cloud render 服务 but is a material 隐私 action (user files leave the machine). The 技能.md also requires 添加ing attribution headers where one header value is 'auto-检测: 安装 path' (X-技能-平台), which implies the 代理 may need to inspect its 安装ation path or 环境; this is not documented elsewhere and could cause unexpected file系统 or 环境 reads. The doc explicitly says not to print 令牌s/raw JSON, which is good, but the scope of file/env 访问 should be clarified.

✓ 安装机制

Instruction-only 技能 with no 安装 spec or code files — lowest 安装 risk. Nothing will be 下载ed or written to disk by an 安装 step.

⚠ 凭证需求

The registry 列出s NEMO_令牌 as a required 环境 variable / primary 凭证, which makes sense for a 服务令牌. But the 技能.md also documents an anonymous-令牌 flow (生成 UUID → POST anonymous-令牌) if NEMO_令牌 is not 设置. Declaring NEMO_令牌 as required while providing an anonymous fallback is inconsistent and should be corrected. No other secrets are 请求ed, which is proportionate to the task.

ℹ 持久化与权限

The 技能 does not 请求 'always' presence and does not include 安装-time persistence. The only potential privileged action is the implied need to read an 安装 path and a local config path (frontmatter), which could give it 访问 to files under ~/.config/nemovideo/ or to the 代理's 安装 location — the purpose of those reads is not explAIned.

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

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官方npx clawhub@latest install video-factory

镜像加速npx clawhub@latest install video-factory --registry https://cn.longxiaskill.com镜像同步中

需要定制？告诉我你的需求 →

技能文档

获取ting 启动ed

分享 your raw video 命令行工具ps and I'll 获取启动ed on batch video production. Or just tell me what you're thinking.

Try saying:

"创建 my raw video 命令行工具ps" "导出 1080p MP4" "combine all 命令行工具ps, 添加 intro and" 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.

Video 工厂 — Batch 创建 and 导出 Videos

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

Here's a typical use: you 发送 a five 30-second product 命令行工具ps, ask for combine all 命令行工具ps, 添加 intro and outro, and 导出 as one finished video, and about 1-2 minutes 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 — batching similar 命令行工具ps to获取her speeds up processing 签名ificantly.

Matching 输入 to Actions

User prompts referencing video 工厂, 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.

Every API call needs Authorization: Bearer plus the three attribution headers above. If any header is missing, 导出s return 402.

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

Header Value X-技能-Source video-工厂 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 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

数据来源：ClawHub ↗ · 中文优化：龙虾技能库