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Free Product Video Cutter

作者 vcarolxhberger · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install free-product-video-cutter
功能描述
trim product video clips into trimmed product clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. e-commerce marketers use it for cuttin...
使用说明 (SKILL.md)

Getting Started

Got product video clips to work with? Send it over and tell me what you need — I'll take care of the AI video trimming.

Try saying:

  • "trim a 2-minute product demo recording into a 1080p MP4"
  • "cut out the intro and trim the clip to 30 seconds for Instagram"
  • "cutting product videos into short shareable clips for e-commerce marketers"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

  1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
  2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer \x3Ctoken>, Content-Type: application/json, and body {"task_name":"project","language":"\x3Cdetected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Free Product Video Cutter — Cut and Export Product Clips

Drop your product video clips in the chat and tell me what you need. I'll handle the AI video trimming on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute product demo recording, ask for cut out the intro and trim the clip to 30 seconds for Instagram, and about 20-40 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter source clips process faster and use fewer credits.

Matching Input to Actions

User prompts referencing free product video cutter, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says... Action Skip SSE?
"export" / "导出" / "download" / "send me the video" → §3.5 Export
"credits" / "积分" / "balance" / "余额" → §3.3 Credits
"status" / "状态" / "show tracks" → §3.4 State
"upload" / "上传" / user sends file → §3.2 Upload
Everything else (generate, edit, add BGM…) → §3.1 SSE

Cloud Render Pipeline Details

Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source: free-product-video-cutter
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

All requests must include: Authorization: Bearer \x3CNEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/\x3Csid>/latest — key fields: data.state.draft, data.state.video_infos, data.state.generated_media

Export (free, no credits): POST /api/render/proxy/lambda — body {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s until status = completed. Download URL at output.url.

Supported formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool 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 stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend says You do
"click [button]" / "点击" Execute via API
"open [panel]" / "打开" Query session state
"drag/drop" / "拖拽" Send edit via SSE
"preview in timeline" Show track summary
"Export button" / "导出" Execute export workflow

Draft field mapping: t=tracks, tt=track type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.

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

Error Codes

  • 0 — success, continue normally
  • 1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token
  • 1002 — session not found; create a new one
  • 2001 — out of credits; anonymous users get a registration link with ?bind=\x3Cid>, registered users top up
  • 4001 — unsupported file type; show accepted formats
  • 4002 — file too large; suggest compressing or trimming
  • 400 — missing X-Client-Id; generate one and retry
  • 402 — free plan export blocked; not a credit issue, subscription tier
  • 429 — rate limited; wait 30s and retry once

Common Workflows

Quick edit: Upload → "cut out the intro and trim the clip to 30 seconds for Instagram" → Download MP4. Takes 20-40 seconds for a 30-second clip.

Batch style: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.

Iterative: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut out the intro and trim the clip to 30 seconds for Instagram" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.

Export as MP4 for widest compatibility across social and e-commerce platforms.

安全使用建议
This skill looks coherent for cloud-based video trimming, but before installing consider: (1) it will talk to an external service (mega-api-prod.nemovideo.ai) and can auto-create and persist an anonymous token/session_id — if you prefer control, set NEMO_TOKEN yourself rather than letting the skill generate it; (2) clarify the frontmatter's config path (~/.config/nemovideo/) — find out whether the skill will write/read files there and what it stores; (3) verify the external domain is trusted and acceptable for you to upload video content to (privacy/data policy); and (4) if you have sensitive videos, avoid automatic uploads or test with non-sensitive content first. These checks would raise confidence to high.
功能分析
Type: OpenClaw Skill Name: free-product-video-cutter Version: 1.0.0 The skill is a functional integration for a third-party video processing service (nemovideo.ai). It automates API interactions for video trimming, including anonymous token generation, session management, and file uploads to 'mega-api-prod.nemovideo.ai'. While it accesses the local installation path to set attribution headers and requires a specific environment variable (NEMO_TOKEN), these actions are consistent with its stated purpose of providing cloud-based video editing services and do not exhibit signs of malicious intent or unauthorized data exfiltration.
能力评估
Purpose & Capability
Name/description (cloud GPU video trimming, MP4/MOV/AVI/WebM support) align with the runtime instructions and the NEMO API endpoints referenced. Requesting a NEMO_TOKEN credential is coherent with calling nemovideo.ai. One inconsistency: the registry metadata summary earlier listed no required config paths, but the SKILL.md frontmatter includes a configPaths entry (~/.config/nemovideo/). This mismatch should be clarified.
Instruction Scope
Instructions are focused on connecting to the nemo backend, uploading files, reading SSE, polling job state, and returning download URLs — all within the stated purpose. The skill instructs automatic anonymous-token creation (POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token), storing returned tokens/session_id, reading its own frontmatter, and detecting an install path to set X-Skill-Platform. These behaviors are expected for a hosted-render workflow but mean the agent will contact an external service and persist auth/session values; the doc also explicitly tells the agent not to display raw token values to the user.
Install Mechanism
This is an instruction-only skill with no install spec or code files, so nothing is written to disk by an installer. Lowest-risk install posture.
Credentials
The skill declares a single required credential (NEMO_TOKEN) which is proportional to calling the Nemovideo API. The SKILL.md also references a config path (~/.config/nemovideo/) in its frontmatter; if the agent will read/write that directory, it increases scope beyond just a single in-memory token. Clarify whether the skill will create or read files in that path. No other unrelated secrets or credentials are requested.
Persistence & Privilege
always:false and model invocation is allowed (default). The skill asks to generate and store an anonymous token/session_id for subsequent calls — normal for a cloud API integration. It does not request permanent platform-wide privileges or to modify other skills' configurations.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install free-product-video-cutter
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /free-product-video-cutter 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release of Free Product Video Cutter, a skill for trimming and exporting product video clips for e-commerce marketers. - Upload product videos (MP4, MOV, AVI, WebM, up to 500MB) and cut them into shareable clips. - Automatic cloud GPU processing with 1080p MP4 output; typical jobs finish in 20–40 seconds. - Simple onboarding with automatic connection and free token generation (100 free credits valid 7 days). - User prompts route to upload, export, credits, state, or editing actions via intent classification. - Supports quick, batch, and iterative editing workflows with persistent session timelines. - Comprehensive error handling and clear feedback for common upload and export issues.
元数据
Slug free-product-video-cutter
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Free Product Video Cutter 是什么?

trim product video clips into trimmed product clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. e-commerce marketers use it for cuttin... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 104 次。

如何安装 Free Product Video Cutter?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install free-product-video-cutter」即可一键安装,无需额外配置。

Free Product Video Cutter 是免费的吗?

是的,Free Product Video Cutter 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Free Product Video Cutter 支持哪些平台?

Free Product Video Cutter 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Free Product Video Cutter?

由 vcarolxhberger(@vcarolxhberger)开发并维护,当前版本 v1.0.0。

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