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whitejohnk-26

Korean Video Editing With

作者 whitejohnk-26 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install korean-video-editing-with
功能描述
Korean content creators edit raw video footage into edited Korean videos using this skill. Accepts MP4, MOV, AVI, WebM up to 500MB, renders on cloud GPUs at...
使用说明 (SKILL.md)

Getting Started

Share your raw video footage and I'll get started on AI-assisted Korean editing. Or just tell me what you're thinking.

Try saying:

  • "edit my raw video footage"
  • "export 1080p MP4"
  • "add Korean subtitles and cut silent"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: \x3Cuuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Korean Video Editing With AI — Edit Korean Videos With AI

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

Say you have a 2-minute vlog recorded in Korean and want to add Korean subtitles and cut silent pauses between sentences — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 3 minutes process significantly faster and yield more accurate Korean transcription.

Matching Input to Actions

User prompts referencing korean video editing with, 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: korean-video-editing-with
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

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.

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 → "add Korean subtitles and cut silent pauses between sentences" → Download MP4. Takes 1-2 minutes 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 "add Korean subtitles and cut silent pauses between sentences" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for the best compatibility across Korean streaming platforms.

安全使用建议
This skill appears to implement exactly what it advertises (cloud-based Korean video editing) and only requests one API token (NEMO_TOKEN). However: 1) the skill has no published homepage or known source — that reduces provenance and increases risk if you plan to upload sensitive footage; 2) SKILL.md asks the agent to probe install paths and references a config directory (~/.config/nemovideo/) even though the registry metadata omitted that — confirm whether you are comfortable letting the agent inspect those paths; 3) the service domain (mega-api-prod.nemovideo.ai) is external — verify the vendor and privacy policy before sending private video; 4) anonymous-token generation is allowed (POST with a generated UUID) — tokens expire, but the agent will persist session_id and tokens for operation, so confirm how long data and tokens are retained by the backend. Before installing, ask the skill author for a homepage or privacy statement, confirm why the install-path/configPath checks are needed, and consider testing with non-sensitive sample videos first.
功能分析
Type: OpenClaw Skill Name: korean-video-editing-with Version: 1.0.0 The skill is a functional integration for the NemoVideo AI video editing service, facilitating cloud-based rendering and subtitle generation. It provides detailed instructions for the agent to manage authentication tokens, sessions, and file uploads via the 'mega-api-prod.nemovideo.ai' domain. While it includes logic for the agent to identify its installation environment for attribution headers and instructs the agent to suppress raw tokens in the UI, these behaviors are consistent with the stated purpose of providing a streamlined video editing tool and maintaining good security/UX practices.
能力评估
Purpose & Capability
The SKILL.md describes a cloud-based video-editing workflow (upload, SSE-driven edits, render/export) and the only declared credential (NEMO_TOKEN) is consistent with an API-backed service. Required binaries are none and the declared API endpoints line up with the editing/rendering purpose.
Instruction Scope
Runtime instructions are explicit: generate or use NEMO_TOKEN, create a session, upload files, use SSE, poll render status, and download the result. A few runtime actions extend outside pure editing: the skill instructs the agent to read the file's YAML frontmatter and to detect the agent install path (by probing paths like ~/.clawhub/ and ~/.cursor/skills/) to set X-Skill-Platform — this requires filesystem inspection of install paths and is not strictly necessary for editing. Instructions otherwise stay within the described editing workflow and do not ask for unrelated system secrets.
Install Mechanism
No install spec and no code files — instruction-only. This is lower risk because nothing is automatically downloaded or written to disk by an install step.
Credentials
The skill declares a single credential (NEMO_TOKEN) which is appropriate for an API-based editor. However, there is an inconsistency: the registry summary lists no required config paths, but the SKILL.md frontmatter includes configPaths ("~/.config/nemovideo/"). Asking the agent to probe install paths and possibly a user config directory expands scope beyond a single API token and should be justified. Otherwise, the number and type of env vars requested is proportionate.
Persistence & Privilege
always:false and normal model invocation are set. The skill asks to save session_id and reuse tokens, which is expected for session-based APIs. It does not request permanent platform-level privileges or modification of other skills.
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 korean-video-editing-with
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /korean-video-editing-with 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
Korean Video Editing With AI — Version 1.0.0 - First release: enables AI-driven editing of Korean-language videos with cloud GPU rendering. - Supports MP4, MOV, AVI, WebM uploads up to 500MB, exports at 1080p MP4. - Features rapid processing (1-2 minutes per short clip) with AI-generated Korean subtitles and automatic silent cut detection. - Easy upload, edit, preview, and export workflows, including session management and credit handling. - Includes automated session setup, API authentication, error handling, and support for common Korean creator use cases.
元数据
Slug korean-video-editing-with
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

Korean Video Editing With 是什么?

Korean content creators edit raw video footage into edited Korean videos using this skill. Accepts MP4, MOV, AVI, WebM up to 500MB, renders on cloud GPUs at... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 82 次。

如何安装 Korean Video Editing With?

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

Korean Video Editing With 是免费的吗?

是的,Korean Video Editing With 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Korean Video Editing With 支持哪些平台?

Korean Video Editing With 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 Korean Video Editing With?

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

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