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Highlight Editor Ai

作者 peandrover adam · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install highlight-editor-ai
功能描述
Turn a 2-hour sports game recording into 1080p highlight reel clips just by typing what you need. Whether it's generating short highlight reels from long vid...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "create my raw video footage"
  • "export 1080p MP4"
  • "extract the best moments and compile"

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.

Highlight Editor AI — Extract and Export Video Highlights

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

Here's a typical use: you send a a 2-hour sports game recording, ask for extract the best moments and compile them into a 90-second highlight 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 — trimming your source video to the relevant section before uploading speeds up highlight detection.

Matching Input to Actions

User prompts referencing highlight editor ai, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint Method Purpose
/api/tasks/me/with-session/nemo_agent POST Start a new editing session. Body: {"task_name":"project","language":"\x3Clang>"}. Returns session_id.
/run_sse POST Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/\x3Csid> POST Upload a file (multipart) or URL.
/api/credits/balance/simple GET Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/\x3Csid>/latest GET Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda POST Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: 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 highlight-editor-ai
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.

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

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.

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)

Common Workflows

Quick edit: Upload → "extract the best moments and compile them into a 90-second highlight 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 "extract the best moments and compile them into a 90-second highlight 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 social platforms.

安全使用建议
This skill appears to do what it claims (upload videos, run cloud rendering, return downloads) but exercise caution: 1) The publisher and homepage are unknown — ask for a privacy policy, data retention rules, and where files are stored and for how long. 2) Understand that your uploaded video/audio will be sent to mega-api-prod.nemovideo.ai; avoid uploading sensitive or private footage until you verify the service. 3) Clarify the configPath inconsistency (~/.config/nemovideo/ appears in SKILL.md but not in registry metadata): confirm whether the skill will read any local config files. 4) If you already have a NEMO_TOKEN, ensure it came from a trusted source; otherwise the skill will create an anonymous token with limited credits. If these questions are answered satisfactorily, the skill is functionally coherent; if not, do not install or use with sensitive data.
功能分析
Type: OpenClaw Skill Name: highlight-editor-ai Version: 1.0.0 The highlight-editor-ai skill is a legitimate tool designed to interface with a cloud-based video processing service (nemovideo.ai). It contains standard instructions for the AI agent to manage authentication tokens, sessions, and file uploads to specific API endpoints. The behavior is transparently documented in SKILL.md, and the requested permissions (environment variables and config paths) are consistent with its stated purpose of video editing and export.
能力评估
Purpose & Capability
The skill's stated purpose (cloud video highlight extraction) matches the operations described (upload video, render on cloud GPU, return download URL) and the single required env var NEMO_TOKEN is appropriate. However the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata indicated no required config paths — that inconsistency is unexplained. Also the skill source/homepage is unknown which reduces confidence in provenance.
Instruction Scope
Runtime instructions stay within the editing/export domain: create session, upload files, stream SSE, trigger renders, poll state, and handle credits/errors. They also include an auto-acquire flow for an anonymous token (POST to /api/auth/anonymous-token) which is coherent for anonymous operation. Two things to note: (1) the skill requires adding attribution headers and auto-detecting an install path to set X-Skill-Platform (this may require reading agent environment/install path), and (2) the skill will upload user-supplied video/audio files to an external domain (mega-api-prod.nemovideo.ai) — expected for the feature but high-sensitivity activity for private content.
Install Mechanism
No install spec and no code files — instruction-only skill. This minimizes on-disk installation risk; nothing is downloaded or executed locally by an installer.
Credentials
Only one credential (NEMO_TOKEN) is declared and used, which is proportionate to a cloud API integration. The skill will auto-request an anonymous token if none is present. The unexplained presence of a configPath in the SKILL.md frontmatter (but not in registry metadata) is inconsistent and could imply the skill expects to read ~/.config/nemovideo/ — that should be clarified before trusting local config data.
Persistence & Privilege
The skill is not always-enabled and uses normal autonomous invocation settings. It stores session_id for the session lifecycle (expected) and does not request system-wide config changes or other skills' credentials.
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 highlight-editor-ai
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /highlight-editor-ai 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 Highlight Editor AI — Extract and Export Video Highlights. - Instantly extract highlight reels from long videos via natural language prompts; no manual editing required. - Automatic cloud setup with 100 free credits (NEMO_TOKEN handled seamlessly on first run). - Supports direct file uploads and multiple formats (mp4, mov, avi, webm, mkv, and more). - Fast cloud rendering: 1080p highlight exports typically ready in 1–2 minutes. - Simple workflows: upload, describe what you want, and get a download link—no complicated controls. - Built-in credit and session management; clear user feedback throughout the process.
元数据
Slug highlight-editor-ai
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

Highlight Editor Ai 是什么?

Turn a 2-hour sports game recording into 1080p highlight reel clips just by typing what you need. Whether it's generating short highlight reels from long vid... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 67 次。

如何安装 Highlight Editor Ai?

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

Highlight Editor Ai 是免费的吗?

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

Highlight Editor Ai 支持哪些平台?

Highlight Editor Ai 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 Highlight Editor Ai?

由 peandrover adam(@peand-rover)开发并维护,当前版本 v1.0.0。

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