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mhogan2013-9

Free Highlight Editor

作者 mhogan2013-9 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install free-highlight-editor
功能描述
Get trimmed highlight clips ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something...
使用说明 (SKILL.md)

Getting Started

Send me your raw video footage and I'll handle the AI highlight extraction. Or just describe what you're after.

Try saying:

  • "create a 10-minute gameplay or event recording into a 1080p MP4"
  • "pull the best moments and compile them into a 60-second highlight reel"
  • "generating short highlight reels from long recordings for content creators and gamers"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

  1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
  2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer \x3Ctoken>, Content-Type: application/json, and body {"task_name":"project","language":"\x3Cdetected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Free Highlight Editor — 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 10-minute gameplay or event recording and want to pull the best moments and compile them into a 60-second highlight reel — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter source clips under 5 minutes produce faster and more accurate highlights.

Matching Input to Actions

User prompts referencing free highlight editor, 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 free-highlight-editor
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

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.

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)

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

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.

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 → "pull the best moments and compile them into a 60-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 "pull the best moments and compile them into a 60-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 platforms.

安全使用建议
This skill forwards your uploaded videos to a third-party backend (mega-api-prod.nemovideo.ai) and requires an API token (NEMO_TOKEN). Before installing: 1) Understand privacy: any video you upload will be sent to their cloud — don't upload sensitive content unless you trust the service and its retention policy. 2) Token handling: the skill will auto-request an anonymous token if you don't provide one and appears to expect a config directory (~/.config/nemovideo/) per its frontmatter — ask the author whether tokens/session IDs are stored on disk and where. 3) Metadata mismatch: registry metadata said no config paths while SKILL.md lists one — request clarification. 4) If you prefer control, provide your own NEMO_TOKEN (from the service) rather than letting the skill auto-create and store it. 5) If you have regulatory or privacy requirements for media (GDPR, company policy), verify the backend's policies before using. If the author cannot clarify token storage and config writes, treat the skill as risky for private media.
功能分析
Type: OpenClaw Skill Name: free-highlight-editor Version: 1.0.0 The skill bundle provides a legitimate interface for a video highlight extraction service hosted at nemovideo.ai. The SKILL.md file contains detailed instructions for the agent to manage API sessions, handle file uploads, and process video via a cloud rendering pipeline. It includes standard security practices such as hiding raw tokens from the user and uses specific environment variables and configuration paths (~/.config/nemovideo/) consistent with its stated purpose. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found.
能力评估
Purpose & Capability
The name/description (cloud-based highlight extraction) aligns with the endpoints and API calls in SKILL.md. Requesting a NEMO_TOKEN and interacting with nemovideo.ai is coherent. However, registry metadata reported no required config paths while the SKILL.md frontmatter declares a config path (~/.config/nemovideo/), an inconsistency that should be clarified.
Instruction Scope
Instructions are scoped to remote API actions: obtain (or check for) NEMO_TOKEN, create sessions, upload video files, use SSE for edits, poll export status, and return download URLs. They do not ask for unrelated system files or other credentials. Concerns: the skill instructs auto-obtaining and storing a token and session_id and mentions an on-disk config directory in its frontmatter — that implies reading/writing under ~/.config which expands the surface beyond purely in-memory session handling. The SKILL.md also asks the agent to auto-detect install path for X-Skill-Platform header, which may require inspecting environment/install paths.
Install Mechanism
Instruction-only skill with no install spec and no code files. No packages or remote archives are downloaded or extracted by the skill itself per the provided metadata.
Credentials
Only a single credential (NEMO_TOKEN) is required — appropriate for a cloud API. But the SKILL.md will call an anonymous-token endpoint to obtain and persist a token if NEMO_TOKEN is absent; it's unclear where/how that token/session_id will be stored (in memory vs ~/.config/nemovideo/). Uploading user videos to an external service is a significant privacy action and is proportional to the skill purpose but should be considered by the user.
Persistence & Privilege
Skill does not request always:true and does not declare system-wide privilege. The only persistence implied is storing the anonymous token or session_id for subsequent requests; whether this is transient or written under the config path is not specified and should be clarified.
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 free-highlight-editor
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /free-highlight-editor 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
Free Highlight Editor — Initial Release - Instantly extracts and exports highlight reels from raw video uploads using AI, with no manual editing required. - Supports MP4, MOV, AVI, and WebM uploads up to 500MB, returning downloadable 1080p MP4 files. - Fast processing via a cloud GPU backend; sessions require free anonymous token authentication. - Simple workflow: upload video, describe desired highlights, and download the edited clip. - Includes support for batching, iterative workflows, and queryable credits and export status. - Comprehensive error handling and clear user guidance for smooth, user-friendly experience.
元数据
Slug free-highlight-editor
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

Free Highlight Editor 是什么?

Get trimmed highlight clips ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 80 次。

如何安装 Free Highlight Editor?

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

Free Highlight Editor 是免费的吗?

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

Free Highlight Editor 支持哪些平台?

Free Highlight Editor 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 Free Highlight Editor?

由 mhogan2013-9(@mhogan2013-9)开发并维护,当前版本 v1.0.0。

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