📦 Editor Cinematic

v1.0.0

转换 raw video footage into cinematic edited video with this 技能. Works with MP4, MOV, AVI, ProRes files up to 500MB. filmmakers, content 创建器s, vi...

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by @whitejohnk-26

开发工具代码生成数据与API 数据库文件处理

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OpenClaw

安全

medium confidence

The 技能's 请求s and 运行time instructions are consistent with a cloud-based video-editing 服务: it asks for a single 服务令牌 and instructs 上传ing footage to that 服务; no unrelated 凭证s, 安装s, or mysterious behaviors are present, though there are a few small inconsistencies and 隐私 considerations to note.

评估建议

This 技能应用ears to do what it says: it 上传s your footage to an external 服务 (mega-API-prod.nemovideo.AI) for cloud GPU processing and requires a single 服务令牌 (NEMO_令牌). Before 安装ing or using it, consider: 1) 隐私 — your 上传ed videos leave your device and are stored/processed by the 服务; avoid 上传ing sensitive material. 2) 令牌 handling — prefer supplying your own 令牌 rather than relying on anonymous 令牌 generation if you need control; if you use anonymous 令牌s, note they expire and may be stored by the 代理/会话...

详细分析 ▾

✓ 用途与能力

Name/description (cinematic video editing) align with the instructions: the 技能.md documents 端点s for 上传ing video, editing via SSE, and 导出ing rendered MP4s. The only required 凭证 is NEMO_令牌 which is 应用ropriate for a third-party processing API. Minor inconsistency: the 技能.md frontmatter 列出s a config path (~/.config/nemovideo/) while the registry metadata 报告ed no required config paths — this is likely benign but inconsistent.

ℹ 指令范围

运行time instructions explicitly direct the 代理 to accept user video and 上传 it to https://mega-API-prod.nemovideo.AI for cloud rendering (expected for this purpose). The 技能 also directs the 代理 to obtAIn an anonymous 令牌 if NEMO_令牌 is not present and to save 会话_id from 响应s. One implementation detAIl to note: headers require an X-技能-平台 populated by 'auto-检测: 安装 path', which implies the 代理 may try to read its 安装 path or similar 环境 in格式化ion — that is outside pure editing 记录ic and could require file系统访问. The instructions do not ask for unrelated env vars or other 系统 files.

✓ 安装机制

Instruction-only 技能 with no 安装 spec and no code files — lowest 安装 risk. Nothing is 下载ed or written by an 安装er step in the manifest.

✓ 凭证需求

Only NEMO_令牌 is declared as required (primaryEnv). That matches the documented API usage. The 技能 offers an anonymous-令牌 flow to obtAIn a short-lived 令牌 if none is 设置, which is consistent with a cloud 服务 onboarding flow. No unrelated secrets (AWS, GitHub, etc.) are 请求ed.

✓ 持久化与权限

always:false and no special 平台 privileges 请求ed. The 技能 instructs saving 会话_id and using 令牌s for 请求s (normal for 会话-based APIs). It does not 请求 modification of other 技能s or global 代理 configs.

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 editor-cinematic

镜像加速npx clawhub@latest install editor-cinematic --registry https://cn.longxiaskill.com

技能文档

获取ting 启动ed

分享 your raw video footage and I'll 获取启动ed on cinematic AI editing. Or just tell me what you're thinking.

Try saying:

"转换 my raw video footage" "导出 4K MP4" "应用ly cinematic color grading, 添加 dramatic" 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.

Editor Cinematic — Turn Footage into Cinematic Videos

Drop your raw video footage in the chat and tell me what you need. I'll handle the cinematic AI 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 handheld camera recording of a city street, ask for 应用ly cinematic color grading, 添加 dramatic transitions, and 同步 cuts to the background music, and about 1-2 minutes later you've got a MP4 file ready to 下载. The whole thing 运行s at 4K by default.

One thing worth knowing — 命令行工具ps under 3 minutes render faster and give the AI more precise control over cinematic pacing.

Matching 输入 to Actions

User prompts referencing editor cinematic, 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 editor-cinematic X-技能-Version frontmatter version X-技能-平台 auto-检测: ClawHub / cursor / unknown from 安装 path

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 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=, regis

数据来源：ClawHub ↗ · 中文优化：龙虾技能库