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tk8544-b

Video Using

作者 tk8544-b · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
33
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当前安装
1
版本数
在 OpenClaw 中安装
/install video-using
功能描述
Skip the learning curve of professional editing software. Describe what you want — cut out silences, add background music, and export as MP4 — and get edited...
使用说明 (SKILL.md)

Getting Started

Ready when you are. Drop your video clips here or describe what you want to make.

Try saying:

  • "edit a 2-minute raw screen recording into a 1080p MP4"
  • "cut out silences, add background music, and export as MP4"
  • "editing and repurposing video clips with AI assistance for content creators"

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.

Video Using — Edit and Export Video Clips

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 2-minute raw screen recording and want to cut out silences, add background music, and export as MP4 — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 3 minutes process significantly faster.

Matching Input to Actions

User prompts referencing video using, 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 video-using
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.

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

  • "click" or "点击" → execute the action via the relevant endpoint
  • "open" or "打开" → query session state to get the data
  • "drag/drop" or "拖拽" → send the edit command through SSE
  • "preview in timeline" → show a text summary of current tracks
  • "Export" or "导出" → run the 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 → "cut out silences, add background music, and export as MP4" → 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 "cut out silences, add background music, and export as MP4" — 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 platforms.

安全使用建议
This skill looks coherent for cloud-based video editing. Before installing, make sure you are comfortable sending your video files and editing instructions to `mega-api-prod.nemovideo.ai`, use a dedicated or temporary NEMO_TOKEN, and avoid uploading confidential media unless you trust the provider’s privacy and retention practices.
功能分析
Type: OpenClaw Skill Name: video-using Version: 1.0.0 The skill provides a legitimate interface for a cloud-based video editing service hosted at nemovideo.ai. It manages authentication via the NEMO_TOKEN environment variable or an anonymous token generation process, and handles file uploads and video rendering tasks as described in its documentation. While it interacts with external APIs and handles user-provided media, its behavior is transparently documented, includes appropriate error handling, and lacks any indicators of malicious intent, data exfiltration, or harmful prompt injection.
能力评估
Purpose & Capability
The stated purpose—uploading clips, editing them through a cloud rendering pipeline, and exporting MP4s—matches the documented capabilities, but user-provided videos may be sensitive.
Instruction Scope
The skill automates setup, session creation, editing calls, export polling, and some backend-driven GUI-to-API translations; these are scoped to the video workflow.
Install Mechanism
There is no install spec or code to execute, and the static scan found nothing; however, the source is listed as unknown and no homepage is provided.
Credentials
Use of NEMO_TOKEN and external Nemo Video API calls is expected for a cloud video editing integration; no broad local filesystem or OS-level access is shown beyond user-directed uploads.
Persistence & Privilege
The artifacts show cloud session IDs and render-job polling, but no local persistence, background worker, privilege escalation, or continued local execution.
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 video-using
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /video-using 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
video-using 1.0.0 - Initial release: describe the edits you want and get back processed MP4 clips in 1–2 minutes. - Supports upload of MP4, MOV, AVI, WebM files up to 500MB; automatic AI editing with no editing software needed. - Handles cut, silence removal, background music, and exports to MP4 via a secure cloud backend. - Quick setup with anonymous token if no NEMO_TOKEN is present; session-based editing with persistent state. - Easy command routing for upload, export, credits check, and editing through keywords or direct file actions.
元数据
Slug video-using
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

Video Using 是什么?

Skip the learning curve of professional editing software. Describe what you want — cut out silences, add background music, and export as MP4 — and get edited... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 33 次。

如何安装 Video Using?

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

Video Using 是免费的吗?

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

Video Using 支持哪些平台?

Video Using 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 Video Using?

由 tk8544-b(@tk8544-b)开发并维护,当前版本 v1.0.0。

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