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Video Editor Anup

作者 francemichaell-15 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install video-editor-anup
功能描述
Skip the learning curve of professional editing software. Describe what you want — trim the pauses, add background music, and export as a clean reel — and ge...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "edit my raw video footage"
  • "export 1080p MP4"
  • "trim the pauses, add background music,"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

  • Generate a UUID as client identifier
  • POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
  • The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Video Editor Anup — Edit and Export Polished Videos

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

Here's a typical use: you send a a 2-minute unedited phone recording, ask for trim the pauses, add background music, and export as a clean reel, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips under 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing video editor anup, 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.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"\x3Clang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/\x3Csid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/\x3Csid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s for completed status and download URL.

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

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

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

Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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)

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

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.

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 pauses, add background music, and export as a clean reel" → 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 "trim the pauses, add background music, and export as a clean reel" — 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
Treat this as a third-party cloud editing service: upload only videos you are comfortable sending to nemovideo.ai, use a dedicated token where possible, monitor credit usage, and be aware that render jobs may continue if the session is interrupted.
功能分析
Type: OpenClaw Skill Name: video-editor-anup Version: 1.0.0 The skill provides a legitimate interface for a cloud-based video editing service (nemovideo.ai). It manages user sessions, file uploads, and rendering tasks via the 'mega-api-prod.nemovideo.ai' endpoint. All documented behaviors, including the acquisition of anonymous tokens and the use of specific attribution headers, are transparently aligned with the stated purpose of providing AI-assisted video editing without local software requirements.
能力评估
Purpose & Capability
The stated purpose, cloud editing workflow, upload/export endpoints, and 1080p render behavior fit together coherently. The main user-noticeable risk is that video files and edit prompts are processed by an external service.
Instruction Scope
The instructions tell the agent to connect to the backend before handling requests and to keep technical details out of chat. This is disclosed in the skill text and appears UX-oriented, but users may not see backend details during normal use.
Install Mechanism
There is no install spec and no local code to execute. However, the registry lists the source as unknown and no homepage is provided, so provenance for the external service integration is limited.
Credentials
Using NEMO_TOKEN or an anonymous starter token is proportionate for a cloud rendering API, but it is still credential-backed access to sessions, credits, uploads, and exports.
Persistence & Privilege
The artifacts describe cloud render sessions and job IDs that can be orphaned if the tab closes. No local background worker or hidden persistence is shown.
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-editor-anup
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /video-editor-anup 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 Editor Anup 1.0.0 — Initial Release - Launches easy, AI-powered video editing via chat. - Supports uploads up to 500MB (MP4, MOV, AVI, WebM). - Handles editing requests: trim, add background music, export polished results in 1–2 minutes. - Runs fully in the cloud (no software install); keeps sessions for iterative edits. - Includes clear error handling, session, and API token management.
元数据
Slug video-editor-anup
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 Editor Anup 是什么?

Skip the learning curve of professional editing software. Describe what you want — trim the pauses, add background music, and export as a clean reel — and ge... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 41 次。

如何安装 Video Editor Anup?

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

Video Editor Anup 是免费的吗?

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

Video Editor Anup 支持哪些平台?

Video Editor Anup 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 Editor Anup?

由 francemichaell-15(@francemichaell-15)开发并维护,当前版本 v1.0.0。

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