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linmillsd7

Video Editor Opus

作者 linmillsd7 · 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-opus
功能描述
Turn a 3-minute unedited interview recording into 1080p polished edited videos just by typing what you need. Whether it's editing raw footage into a finished...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

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

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.

Video Editor Opus — Edit and Export Finished Videos

Send me your raw video footage and describe the result you want. The AI-powered video editing runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 3-minute unedited interview recording, type "cut the pauses, add background music, and export as a clean final video", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 2 minutes process significantly faster and use fewer credits.

Matching Input to Actions

User prompts referencing video editor opus, 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: video-editor-opus
  • 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.

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 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 the pauses, add background music, and export as a clean final video" → 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 the pauses, add background music, and export as a clean final video" — 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 widest compatibility across platforms.

安全使用建议
Use this skill if you are comfortable sending your selected footage to NemoVideo's cloud service. Keep NEMO_TOKEN private, review the provider's privacy/retention terms for sensitive videos, and expect the skill to start a remote session when invoked.
功能分析
Type: OpenClaw Skill Name: video-editor-opus Version: 1.0.0 The skill is a legitimate integration for an AI-powered video editing service hosted at nemovideo.ai. It provides detailed instructions for the agent to manage authentication (including anonymous token acquisition), session state, and video processing workflows via a remote API. While it performs filesystem checks to determine its installation path for telemetry (X-Skill-Platform header) and accesses a specific configuration directory (~/.config/nemovideo/), these actions are consistent with its stated purpose and do not exhibit signs of data exfiltration or malicious intent.
能力评估
Purpose & Capability
The cloud upload and render workflow matches the stated video-editing purpose, but raw video can be sensitive and leaves the local machine.
Instruction Scope
The skill tells the agent to set up a remote session on first use and translate provider GUI-style responses into API calls; this is disclosed and aligned with the workflow.
Install Mechanism
There is no local install or code to run, and the static scan was clean, but the registry lists the source as unknown and provides no homepage.
Credentials
Use of NEMO_TOKEN is expected for this provider integration, and the instructions say not to print tokens or raw JSON.
Persistence & Privilege
The skill describes remote render jobs tied to session IDs that can become orphaned if the tab is closed; no local persistence or privilege escalation 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-opus
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /video-editor-opus 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 Video Editor Opus 1.0.0. - Instantly connect to cloud-based AI video editing with automatic setup and free temporary tokens. - Upload raw video footage and generate polished edits by describing desired outcomes—no manual timeline editing required. - Supports rapid 1080p exports in MP4 and other common formats via remote GPU rendering. - Includes session management, credit checks, real-time status updates, and troubleshooting for common errors. - Streamlined text-to-edit workflows tailored for interviews, quick cuts, or social content creation.
元数据
Slug video-editor-opus
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 Opus 是什么?

Turn a 3-minute unedited interview recording into 1080p polished edited videos just by typing what you need. Whether it's editing raw footage into a finished... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 45 次。

如何安装 Video Editor Opus?

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

Video Editor Opus 是免费的吗?

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

Video Editor Opus 支持哪些平台?

Video Editor Opus 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 Opus?

由 linmillsd7(@linmillsd7)开发并维护,当前版本 v1.0.0。

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