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vcarolxhberger

Highlight Editor Free

作者 vcarolxhberger · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install highlight-editor-free
功能描述
Turn a 30-minute gameplay or event recording into 1080p trimmed highlight clips just by typing what you need. Whether it's generating short highlight reels f...
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 highlight extraction.

Try saying:

  • "create a 30-minute gameplay or event recording into a 1080p MP4"
  • "automatically find and cut the best moments into a 2-minute highlight reel"
  • "generating short highlight reels from long recordings for content creators and sports fans"

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 Free — Extract and Export Video Highlights

This tool takes your raw video footage and runs AI highlight extraction through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 30-minute gameplay or event recording and want to automatically find and cut the best moments into a 2-minute highlight reel — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter source clips under 10 minutes produce faster and more accurate highlights.

Matching Input to Actions

User prompts referencing highlight editor free, 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: highlight-editor-free
  • 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.

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.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend says You do
"click [button]" / "点击" Execute via API
"open [panel]" / "打开" Query session state
"drag/drop" / "拖拽" Send edit via SSE
"preview in timeline" Show track summary
"Export button" / "导出" Execute 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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "automatically find and cut the best moments into a 2-minute 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.

Common Workflows

Quick edit: Upload → "automatically find and cut the best moments into a 2-minute 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.

安全使用建议
This skill appears to do what it says (upload your video to a nemo-video backend, run cloud AI editing, and return a download link), but exercise caution: 1) The SKILL.md will upload your videos to https://mega-api-prod.nemovideo.ai and will create or use a NEMO_TOKEN — that means your media and some metadata leave your machine. Only proceed if you trust that domain/service and its privacy/retention policies. 2) There is a minor metadata mismatch: the manifest here lists no config path, yet the skill's frontmatter references ~/.config/nemovideo/ and also detects install paths to set headers — ask the publisher to clarify exactly what filesystem reads will occur. 3) If you plan to use sensitive footage, don't install until you verify the service's privacy terms and confirm where stored data resides and for how long. 4) Prefer obtaining an explicit API token from the service rather than allowing the skill to auto-create and store anonymous tokens. If you need help verifying the backend domain or drafting questions for the publisher, I can help.
功能分析
Type: OpenClaw Skill Name: highlight-editor-free Version: 1.0.0 The highlight-editor-free skill is a legitimate tool designed to interface with the NemoVideo AI cloud API (mega-api-prod.nemovideo.ai) for video highlight extraction. It manages authentication through the NEMO_TOKEN environment variable or an anonymous token acquisition process, and it handles video processing workflows including file uploads, session management via SSE, and rendering. All identified behaviors, such as network communication and configuration path requirements (~/.config/nemovideo/), are directly aligned with the stated purpose of a cloud-based video editing service, and no malicious indicators or data exfiltration attempts were found.
能力评估
Purpose & Capability
The name/description claim cloud-based AI highlight extraction; the SKILL.md exclusively describes uploading video and calling a nemo-video cloud backend, and it requires a NEMO_TOKEN — this is coherent. However the registry metadata lists no required config paths while the SKILL.md frontmatter and metadata reference ~/.config/nemovideo/ and install-path detection for X-Skill-Platform, which is an inconsistency between declared requirements and the instructions.
Instruction Scope
Runtime instructions are explicit about reading NEMO_TOKEN, creating an anonymous token via POST to the nemo API if absent, creating sessions, uploading videos, streaming SSE, polling render status, and returning download URLs. All operations are within the stated purpose (upload, process, download). The skill does instruct detection of install path and a config dir (~/.config/nemovideo/) to populate headers; that requires filesystem access but is plausibly used only for attribution.
Install Mechanism
There is no install spec and no code files — instruction-only skill — so nothing is written to disk by an installer. This is the lowest-risk install mechanism.
Credentials
The only declared credential is NEMO_TOKEN which is appropriate for a cloud service. But the SKILL.md instructs creating an anonymous token via the API and treating it as NEMO_TOKEN when none is present, and the frontmatter references a config path (~/.config/nemovideo/) not listed in the registry metadata. The skill will upload user video data to a third-party endpoint (mega-api-prod.nemovideo.ai), so requiring/creating a token and handing video data to an external service are privacy-sensitive and should be explicitly consented to.
Persistence & Privilege
always is false and the skill requests no persistent system-wide privileges. It keeps an API session_id for rendering jobs (expected), and there is no instruction to modify other skills or global agent config.
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-free
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /highlight-editor-free 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 Free. - Upload raw video footage and describe the highlights you want to extract. - Automated cloud-powered highlight detection and export in 1080p MP4 (free tier). - No timeline editing or complex settings required; just type your instructions. - Fast setup with anonymous token and session creation; 100 free credits for new users. - Supports common video formats; exports in MP4, MOV, AVI, WebM, and more. - Built-in error handling for token, session, credits, and file issues.
元数据
Slug highlight-editor-free
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 Free 是什么?

Turn a 30-minute gameplay or event recording into 1080p trimmed highlight clips just by typing what you need. Whether it's generating short highlight reels f... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 96 次。

如何安装 Highlight Editor Free?

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

Highlight Editor Free 是免费的吗?

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

Highlight Editor Free 支持哪些平台?

Highlight Editor Free 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 Free?

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

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