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whitejohnk-26

Cap Cut

作者 whitejohnk-26 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install cap-cut
功能描述
Get edited video clips ready to post, without touching a single slider. Upload your video clips (MP4, MOV, AVI, WebM, up to 500MB), say something like "trim...
使用说明 (SKILL.md)

Getting Started

Share your video clips and I'll get started on AI video editing. Or just tell me what you're thinking.

Try saying:

  • "edit my video clips"
  • "export 1080p MP4"
  • "trim the clip, add captions, and"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

  • Generate a UUID as client identifier
  • POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
  • Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Cap Cut — Edit and Export Short Videos

This tool takes your video clips and runs AI video editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 60-second vertical phone recording and want to trim the clip, add captions, and sync background music — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: vertical video works fine for Reels and TikTok exports.

Matching Input to Actions

User prompts referencing cap cut, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header Value
X-Skill-Source cap-cut
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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.

SSE Event Handling

Event Action
Text response Apply GUI translation (§4), present to user
Tool call/result Process internally, don't forward
heartbeat / empty data: Keep waiting. Every 2 min: "⏳ Still working..."
Stream closes Process final response

~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.

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

Example timeline summary:

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 → "trim the clip, add captions, and sync background music" → Download MP4. Takes 30-60 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 "trim the clip, add captions, and sync background music" — 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 platforms.

安全使用建议
Install only if you are comfortable sending selected videos to the NemoVideo cloud backend for processing. Use a dedicated token where possible, avoid uploading sensitive footage unless the provider’s privacy terms are acceptable, and review exports before posting.
功能分析
Type: OpenClaw Skill Name: cap-cut Version: 1.0.0 The 'cap-cut' skill is a wrapper for a cloud-based AI video editing service hosted at nemovideo.ai. It facilitates video uploads, automated editing (trimming, captions, music sync), and rendering via a series of REST API calls and SSE streams. While it performs environment checks for an API token (NEMO_TOKEN) and gathers basic platform attribution from the installation path, its operations are transparently documented and strictly aligned with its stated purpose of video processing. No evidence of data exfiltration, unauthorized command execution, or malicious prompt injection was found.
能力评估
Purpose & Capability
The stated purpose is short-video editing/export, and the described cloud upload, render, and download workflow fits that purpose. Users should still notice that editing happens on an external cloud backend.
Instruction Scope
Instructions are mostly scoped to the active video-editing session, but backend responses are translated into follow-on API actions such as export, so users should verify that requested actions match their intent.
Install Mechanism
There is no install script or code package. First-use setup is instruction-driven and automatically obtains or uses a NEMO_TOKEN for the cloud backend.
Credentials
The required NEMO_TOKEN and remote NemoVideo API access are proportionate to the cloud editing purpose. No broad local file or OS access is shown beyond user-provided media.
Persistence & Privilege
The skill uses session IDs and render jobs that may continue on the backend; the artifact says closing the tab before completion can orphan a job. No hidden local persistence is evidenced.
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 cap-cut
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /cap-cut 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 — Cap Cut AI-powered short video editing. - Upload video clips (up to 500MB, MP4/MOV/AVI/WebM) for AI-based editing and export. - Describe desired edits (trim, add captions, sync background music, etc.) via natural prompts. - One-click 1080p MP4 export for easy posting on TikTok, Reels, and more. - Automatic cloud pipeline setup, with anonymous token and session management. - Quick access to credits, export, session state, and supported formats. - Error handling, timelines, and clear user guidance for a seamless edit-to-export workflow.
元数据
Slug cap-cut
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

Cap Cut 是什么?

Get edited video clips ready to post, without touching a single slider. Upload your video clips (MP4, MOV, AVI, WebM, up to 500MB), say something like "trim... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 12 次。

如何安装 Cap Cut?

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

Cap Cut 是免费的吗?

是的,Cap Cut 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Cap Cut 支持哪些平台?

Cap Cut 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 Cap Cut?

由 whitejohnk-26(@whitejohnk-26)开发并维护,当前版本 v1.0.0。

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