✂️ Trimmer In — 技能工具

获取ting 启动ed

Got raw 视频 footage to work with? 发送 it over and tell me what you need — I'll take care of the AI 视频 trimming.

Try saying:

• "trim a 3-minute interview recording with long 暂停s into a 1080p MP4"
• "trim the intro silence and cut out the filler sections in the middle"
• "cutting unwanted sections from 视频 recordings for 内容 创建器s"

Quick 启动 设置up

This 技能 connects to a cloud 处理ing 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.nemo视频.AI/API/auth/anonymous-令牌 with X-命令行工具ent-Id header
• 提取 数据.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.nemo视频.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.

# Trimmer In — Trim and 导出 清理 视频s

Drop your raw 视频 footage in the 聊天 and tell me what you need. I'll handle the AI 视频 trimming on cloud GPUs — you don't need anything 安装ed locally.

Here's a typical use: you 发送 a a 3-minute interview recording with long 暂停s, ask for trim the intro silence and cut out the filler sections in the middle, and about 20-40 seconds later you've got a MP4 文件 ready to 下载. The whole thing 运行s at 1080p by default.

One thing worth knowing — shorter source 命令行工具ps 处理 faster and give more precise trim 结果s.

Matching 输入 to Actions

User prompts referencing trimmer in, 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: trimmer-in
• 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 授权: Bearer and all attribution headers on every 请求 — omitting them triggers a 402 on 导出.

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

Reading the SSE 流

文本 事件 go strAIght to the user (after 图形界面 tran服务级别协议tion). 工具 calls stay internal. 心跳s and empty 数据: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the 流 without any 文本. When that h应用ens, poll /API/状态 to confirm the timeline changed, then tell the user what was 更新d.

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 field m应用ing: t=追踪s, tt=追踪 type (0=视频, 1=音频, 7=文本), sg=segments, d=duration(ms), m=meta数据.

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 the intro silence and cut out the filler sections in the middle" → 下载 MP4. Takes 20-40 seconds 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 the intro silence and cut out the filler sections in the middle" — 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.