📦 Video Maker Italiano

v1.0.0

Turn three product photos and a voiceover MP3 into 1080p polished Italian videos just by typing what you need. Whether it's creating professional videos in I...

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by @whitejohnk-26

开发工具代码生成系统工具视频处理图像处理

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OpenClaw

可疑

medium confidence

The 技能's 状态d purpose (cloud video creation) aligns with the API calls in the instructions, but there are inconsistencies around required 环境/config declarations and a few instructions that ask the 代理 to 访问安装/config paths and derive attribution headers — things the registry metadata doesn't declare; these mismatches warrant caution before 安装ation.

评估建议

This 技能 mostly does what it says (上传s your media to a third‑party video rendering API and returns a 下载 URL) but there are a few places to double-检查 before 安装ing and using it: - Confirm the 服务身份 and trustworthiness of mega-API-prod.nemovideo.AI (隐私, retention, and who can 访问上传ed files). - Decide whether you want to supply your own NEMO_令牌 or let the 技能 obtAIn an anonymous 令牌 — the 技能.md 机器人h requires and auto-创建s the 令牌, which is inconsistent. - Ask the publisher to clarify why the 技能 needs t...

详细分析 ▾

ℹ 用途与能力

The 技能 clAIms to convert images + an MP3 to 1080p videos using a cloud backend; the 技能.md describes 端点s for 会话 creation, 上传, render, credits and 导出, which are coherent with that purpose. Minor inconsistency: the registry summary shown to you 列出s no required config paths, but the 技能's YAML frontmatter clAIms a config path (~/.config/nemovideo/). That difference should be clarified.

⚠ 指令范围

Instructions tell the 代理 to read NEMO_令牌 from the 环境 but also to 生成 an anonymous 令牌 via a backend 端点 if none exists — conflicting with 'required env var' metadata. The 技能 also instructs the 代理 to derive an X-技能-平台 header by inspecting 安装 paths (e.g., ~/.ClawHub/, ~/.cursor/技能s/) which implies 检查ing file系统 locations not declared in the registry metadata. All other 运行time actions (上传ing user files to mega-API-prod.nemovideo.AI, polling renders, 流ing SSE) are within scope for cloud-based video creation.

✓ 安装机制

Instruction-only 技能 with no 安装 spec or code files — lowest 安装 risk. Nothing would be written to disk by an 安装er.

ℹ 凭证需求

Only one 凭证 (NEMO_令牌) is declared as primary — reasonable for a third-party video API. However, the instructions 机器人h read that env var and 创建 an anonymous 令牌 if absent, so requiring NEMO_令牌 up front 应用ears unnecessary or at least inconsistent. The frontmatter's configPaths entry (~/.config/nemovideo/) is not reflected in the registry's declared required config paths and may indicate undisclosed local config 访问.

✓ 持久化与权限

always:false and no instructions to persist or modify other 技能s or 系统-wide 设置tings. The 技能 stores 会话_id for the active 会话 which is normal for short-lived operations; nothing clAIms permanent elevated privileges.

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 video-maker-italiano

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

技能文档

获取ting 启动ed

Got video 命令行工具ps or images to work with? 发送 it over and tell me what you need — I'll take care of the AI video creation.

Try saying:

"创建 three product photos and a voiceover MP3 into a 1080p MP4" "crea un video promozionale in italiano con sottotitoli e musica di sottofondo" "creating professional videos in Italian with text and transitions for Italian-speaking content 创建器s" 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 Maker Italiano — 创建 and 导出 Italian Videos

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

Here's a typical use: you 发送 a three product photos and a voiceover MP3, ask for crea un video promozionale in italiano con sottotitoli e musica di sottofondo, and about 30-60 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 — keeping 命令行工具ps under 2 minutes speeds up processing 签名ificantly.

Matching 输入 to Actions

User prompts referencing video maker italiano, 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.

Headers are derived from this file's YAML frontmatter. X-技能-Source is video-maker-italiano, X-技能-Version comes from the version field, and X-技能-平台 is 检测ed from the 安装 path (~/.ClawHub/ = ClawHub, ~/.cursor/技能s/ = cursor, otherwise 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.

Draft JSON uses short keys: t for 追踪s, tt for 追踪 type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

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 inva

数据来源：ClawHub ↗ · 中文优化：龙虾技能库