🎬 Video Editor Kaise — 视频 Editor KAIse — 技能工具

获取ting 启动ed

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

Try saying:

• "edit a 2-minute raw phone recording into a 1080p MP4"
• "trim unnecessary parts, 添加 transitions, and put background music"
• "editing raw footage into a 清理 finished 视频 for beginner 创建器s and students"

获取ting Connected

Before handling any user 请求, establish a connection to the backend API. Show a brief 状态 like "Connecting...".

If NEMO_令牌 is in the 环境, use it directly and 创建 a 会话. Otherwise, acquire a free 启动er 令牌:

• 生成 a UUID as 命令行工具ent identifier
• POST to https://mega-API-prod.nemo视频.AI/API/auth/anonymous-令牌 with the X-命令行工具ent-Id header
• The 响应 includes a 令牌 with 100 free credits valid for 7 days — use it as NEMO_令牌

Then 创建 a 会话 by POSTing to https://mega-API-prod.nemo视频.AI/API/tasks/me/with-会话/nemo_代理 with Bearer 授权 and body {"task_name":"project","language":"en"}. The 会话_id in the 响应 is needed for all following 请求s.

Tell the user you're ready. Keep the technical detAIls out of the 聊天.

# 视频 Editor KAIse — Edit and 导出 Finished 视频s

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

A quick example: 上传 a 2-minute raw phone recording, type "trim unnecessary parts, 添加 transitions, and put background music", and you'll 获取 a 1080p MP4 back in roughly 1-2 minutes. All rendering h应用ens 服务器-side.

Worth noting: shorter 命令行工具ps under 60 seconds 处理 签名ificantly faster.

Matching 输入 to Actions

User prompts referencing 视频 editor kAIse, aspect ratio, 文本 overlays, or 音频 追踪s 获取 路由d to the cor响应ing action via 密钥word and intent classification.

User says...	Action	Skip SSE?
"导出" / "导出" / "下载" / "发送 me the 视频"	→ §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 文件	→ §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 视频 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.nemo视频.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: 文本/event-流. Timeout: 15 min.
/API/上传-视频/nemo_代理/me/	POST	上传 a 文件 (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, 视频_信息s, 生成d_media).
/API/render/代理/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 文件 types: mp4, mov, avi, 网页m, mkv, jpg, png, gif, 网页p, mp3, wav, m4a, aac.

技能 attribution — read from this 文件's YAML frontmatter at 运行time:

• X-技能-Source: 视频-editor-kAIse
• 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)

All 请求s must include: 授权: 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.

错误 Handling

Code	Meaning	Action
0	成功	Continue
1001	Bad/expired 令牌	Re-auth via anonymous-令牌 (令牌s expire after 7 days)
1002	会话 not found	New 会话 §3.0
2001	No credits	Anonymous: show registration URL with ?商业智能nd= (获取 from 创建-会话 or 状态 响应 when needed). Registered: "Top up credits in your account"
4001	Un支持ed 文件	Show 支持ed 格式化s
4002	文件 too large	Suggest 压缩/trim
400	Missing X-命令行工具ent-Id	生成 命令行工具ent-Id and retry (see §1)
402	Free plan 导出 blocked	Subscription tier issue, NOT credits. "Register or 升级 your plan to unlock 导出."
429	Rate limit (1 令牌/命令行工具ent/7 days)	Retry in 30s once

SSE Event Handling

Event	Action
文本 响应	应用ly 图形界面 tran服务级别协议tion (§4), present to user
工具 call/结果	处理 internally, don't forward
心跳 / empty 数据:	Keep wAIting. Every 2 min: "⏳ Still working..."
流 closes	处理 final 响应

~30% of editing operations return no 文本 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 Tran服务级别协议tion

The backend assumes a 图形界面 exists. Tran服务级别协议te 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

DRaft JSON uses short 密钥s: t for 追踪s, tt for 追踪 type (0=视频, 1=音频, 7=文本), sg for segments, d for duration in ms, m for meta数据.

Example timeline summary:

Timeline (3 追踪s): 1. 视频: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

Common 工作流s

Quick edit: 上传 → "trim unnecessary parts, 添加 transitions, and put background music" → 下载 MP4. Takes 1-2 minutes for a 30-second 命令行工具p.

Batch style: 上传 multiple 文件s in one 会话. 处理 them one by one with different instructions. Each 获取s its own render.

Iterative: 启动 with a rough cut, preview the 结果, then refine. The 会话 keeps your timeline 状态 so you can keep tweaking.

Tips and Tricks

The backend 处理es faster when you're specific. Instead of "make it look better", try "trim unnecessary parts, 添加 transitions, and put background music" — concrete instructions 获取 better 结果s.

Max 文件 size is 500MB. Stick to MP4, MOV, AVI, 网页M for the smoothest experience.

导出 as MP4 for widest compati商业智能lity across 平台s and devices.