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Ai Video Editor Eddie

作者 mory128 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install ai-video-editor-eddie
功能描述
edit raw video footage into polished edited clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators and social media users...
使用说明 (SKILL.md)

Getting Started

Got raw video footage to work with? Send it over and tell me what you need — I'll take care of the AI-assisted video editing.

Try saying:

  • "edit a 2-minute unedited phone recording into a 1080p MP4"
  • "trim the pauses, add background music, and export as a clean MP4"
  • "quickly editing raw footage into shareable videos without manual editing skills for content creators and social media users"

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.

AI Video Editor Eddie — Edit and Export Polished Videos

Drop your raw video footage in the chat and tell me what you need. I'll handle the AI-assisted 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 MP4, 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 and use fewer credits.

Matching Input to Actions

User prompts referencing ai video editor eddie, 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.

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

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

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

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.

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

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.

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)

Common Workflows

Quick edit: Upload → "trim the pauses, add background music, and export as a clean 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 "trim the pauses, add background music, and export as a clean MP4" — 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 balance of quality and file size.

安全使用建议
This skill appears coherent for a cloud-based video editor, but before installing: - Understand that using it will upload your video files (up to 500MB) to https://mega-api-prod.nemovideo.ai — do not use it for sensitive or private footage unless you trust the service. - The skill can auto-generate an anonymous NEMO_TOKEN if you don't provide one; consider setting your own token if you have an account and want control over credits and retention. - Ask the publisher to clarify the config path behavior: SKILL.md frontmatter references ~/.config/nemovideo/ (possible local persistence), but the registry metadata did not. Know where session tokens or IDs will be stored and for how long. - Because source/homepage are unknown, verify the service provider (nemovideo.ai) reputation and privacy policy before sending content. - If you need stronger guarantees, decline to install or only use with non-sensitive test clips.
功能分析
Type: OpenClaw Skill Name: ai-video-editor-eddie Version: 1.0.0 The skill is a functional wrapper for an AI video editing service hosted at nemovideo.ai. It provides detailed instructions for the agent to manage authentication tokens, upload video files, and handle asynchronous rendering tasks via SSE and polling. While it requests access to a specific configuration directory (~/.config/nemovideo/) and performs environment detection for telemetry (X-Skill-Platform), these actions are consistent with its stated purpose and do not exhibit signs of malicious intent, data exfiltration, or unauthorized system access.
能力评估
Purpose & Capability
The name/description match the runtime instructions: the skill routes user uploads and editing intents to a cloud rendering API (mega-api-prod.nemovideo.ai). The single required credential (NEMO_TOKEN) is appropriate for a cloud service. Minor inconsistency: registry metadata reported no config paths, but the SKILL.md frontmatter lists a config path (~/.config/nemovideo/), which is unexpected and should be clarified.
Instruction Scope
SKILL.md instructs the agent to upload user video files (multipart form or URL), create sessions, use SSE, and poll for render status — all within the scope of an editing service. It also instructs auto-creating an anonymous token if NEMO_TOKEN is missing. These actions are expected for a cloud editor but grant the skill the ability to transmit local files and session tokens to the external API (privacy/PII consideration).
Install Mechanism
There is no install spec and no code files — the skill is instruction-only. This is the lowest install risk (nothing is downloaded or written by an install step).
Credentials
Only a single environment variable (NEMO_TOKEN) is declared as required, which is proportionate for a cloud API. The SKILL.md does show behavior to generate an anonymous token via the service's /api/auth/anonymous-token endpoint if NEMO_TOKEN is absent. The frontmatter's configPaths entry suggests the skill may read/write ~/.config/nemovideo/, which was not listed in the registry metadata and should be clarified.
Persistence & Privilege
always:false and no install scripts reduce persistent privilege. The skill does instruct keeping session_id for subsequent operations and the frontmatter hints at a config path where tokens/state might be stored — this is not explicitly documented in the registry metadata and could result in session tokens being persisted on disk.
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 ai-video-editor-eddie
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-video-editor-eddie 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
AI Video Editor Eddie 1.0.0 — Initial Release - Instantly edit raw video footage (MP4, MOV, AVI, WebM up to 500MB) into polished 1080p MP4 clips on cloud GPUs. - Automatic session setup using NEMO_TOKEN for seamless cloud access; 100 free credits with 7-day expiry. - Streamlined workflows: trim pauses, add background music, export, and batch processing fully automated. - Simple, chat-based interface for content creators—no manual editing skills required. - Clear feedback and robust error handling for uploads, credits, status, and export. - Supports quick edits, iterative adjustments, and multiple common video/audio/image formats.
元数据
Slug ai-video-editor-eddie
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

Ai Video Editor Eddie 是什么?

edit raw video footage into polished edited clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators and social media users... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 131 次。

如何安装 Ai Video Editor Eddie?

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

Ai Video Editor Eddie 是免费的吗?

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

Ai Video Editor Eddie 支持哪些平台?

Ai Video Editor Eddie 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 Ai Video Editor Eddie?

由 mory128(@mory128)开发并维护,当前版本 v1.0.0。

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