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Agent Skill · 开发

magic-light-ai(魔法光 AI)

magic-light-ai 用于辅助部署、云资源、容器和基础设施运维,适合在 OpenClaw 中需要检查配置、整理部署步骤或排查环境问题时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

magic-light-ai 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 8,422。

总安装 3,170周安装 127GitHub Stars 公开资料未说明下载 1,026核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.1

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:magic-light-ai(魔法光 AI)
来源仓库:https://github.com/dsewell-583h0/magic-light-ai
安装命令:
openclaw skills install magic-light-ai
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install magic-light-ai

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

使用云端 AI 技术修复视频画面中的光线缺陷。支持 MP4/MOV 格式上传与亮度、对比度智能优化。处理时长与画质提升程度取决于原始素材质量与订阅等级。上传内容仅限授权素材,禁止传播他人隐私影像。建议先裁剪片段测试效果再处理完整视频文件。

magic-light-ai 属于开发类 Skill,可作为该场景下的辅助能力补充。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install magic-light-ai;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

magic-light-ai 怎么安装?

在终端执行 openclaw skills install magic-light-ai。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

magic-light-ai 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

magic-light-ai 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

magic-light-ai 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

magic-light-ai 用的人多吗?

公开数据是累计安装 3,170 次,近一周安装 127 次,下载 1,026 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

magic-light-ai 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
magic-light-ai

魔法光 AI · 本页

3,170—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
magic-light-ai
version
1.0.1
displayName
Magic Light AI — Add Lighting Effects to Your Videos
description
>
metadata
{"openclaw": {"emoji": "💡", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "short_prompts"}}

Getting Started

Ready for magic light ai. Drop your video or tell me what lighting you want.

Try saying:

  • "warm up the lighting in my clip"
  • "add a golden hour glow effect"
  • "fix the dark areas in this footage"

First-Time Connection

On first use, the skill sets up a connection to the cloud backend. You'll see a brief "Setting up..." message.

Authentication: If NEMO_TOKEN is already in your environment, skip ahead to creating a session.

  1. Get a free token: Make a UUID for client identification. Send a POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id as the UUID. Grab data.token from the response — that's 100 free credits for 7 days.
  2. Open a session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer token auth and body {"task_name":"project","language":"<detected>"}. Hang on to the session_id.

No raw tokens or JSON get shown to the user.

Fix Lighting and Add Glow Effects to Footage

Upload your video and describe the lighting change you want. Everything runs on cloud GPUs — nothing to install on your machine.

Real example: I had a dim interview clip shot in a basement. Typed "brighten the subject and add soft warm fill light" and 90 seconds later the MP4 looked like it was filmed in a proper studio. Default output is 1080p.

Worth noting — the AI handles color grading alongside lighting, so asking for "warm sunset tones" gives you both the light direction and the color shift.

How Requests Get Routed

Depending on what you type, your message goes to different handlers.

What you sayWhere it goesSkips SSE?
"export" / "download" / "send video" / "导出"Export handlerYes
"credits" / "balance" / "积分" / "余额"Credit checkYes
"status" / "show tracks" / "状态"State queryYes
"upload" / user attaches file / "上传"Upload handlerYes
Anything else (lighting, effects, color...)Main SSE pipelineNo

Cloud Rendering Details

Your video gets uploaded to a GPU cluster for processing. The rendering queue re-encodes at 8Mbps for 1080p. Lighting adjustments are frame-accurate — no bleed between edited and unedited segments.

Every API call needs these headers: Authorization: Bearer <NEMO_TOKEN> plus attribution headers X-Skill-Source, X-Skill-Version, X-Skill-Platform. Without them, export returns a 402 error.

Attribution values come from this file's YAML block: X-Skill-Source = magic-light-ai, X-Skill-Version from the version field, X-Skill-Platform from install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, else unknown).

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

Start session: POST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Returns task_id and session_id.

Send message (SSE): POST /run_sse with body {"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}} and header Accept: text/event-stream. Timeout cap is 15 minutes.

Upload file: POST /api/upload-video/nemo_agent/me/<sid> — either multipart with -F "files=@/path" or JSON {"urls":["<url>"],"source_type":"url"}.

Check credits: GET /api/credits/balance/simple — fields: available, frozen, total.

Get session state: GET /api/state/nemo_agent/me/<sid>/latest — look at data.state.draft, data.state.video_infos, data.state.generated_media.

Export video (no credit cost): POST /api/render/proxy/lambda with {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Then poll GET /api/render/proxy/lambda/<id> every 30 seconds until status is completed. Download from output.url.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

What Errors Mean

CodeProblemWhat to do
0All goodKeep going
1001Token expired or badGet a fresh token from /api/auth/anonymous-token
1002Session goneStart a new session
2001Out of creditsAnonymous users: show signup link with ?bind=<id>. Others: top up
4001Wrong file typeList the accepted formats
4002File too bigTell them to trim or compress first
400No X-Client-Id headerGenerate one and resend
402Export blocked on free tierNot a credits problem — need to register or upgrade
429Too many requestsWait 30 seconds, try once more

Translating Backend GUI Instructions

The backend was built for a visual editor, so it sometimes refers to buttons and panels. Translate them:

Backend saysWhat you do instead
"click [button]" or "点击"Run the matching API call
"open [panel]" or "打开"Fetch session state
"drag/drop" or "拖拽"Send an edit command through SSE
"preview in timeline"Print a track summary
"Export button" or "导出"Run the export flow

SSE Stream Behavior

Text responses go to the user after GUI translation. Tool calls are internal only. Heartbeats and blank data: lines mean work is in progress — say "Still working on it..." every 2 minutes or so.

Around 30% of edits close the stream with no text output. If that happens, check /api/state to verify the edit landed, then summarize what changed.

Draft structure shorthand: t = tracks, tt = track type (0 = video, 1 = audio, 7 = text), sg = segments, d = duration in ms, m = metadata.

Track summary format:

Timeline (3 tracks): 1. Video: sunset beach (0-15s) 2. Audio: ambient waves (0-15s, 40%) 3. Text: "Golden Hour" (2-5s)

Tips and Tricks

Be specific about what you want. "Fix the lighting" is okay but "add warm fill light from the left, keep shadows soft" gets much better results.

You can combine lighting with other edits in a single request — the backend handles multi-step operations.

Max upload is 500MB. Stick with MP4 or MOV for the smoothest experience. Output is always MP4.

Quick Start

  1. Upload your footage (drag and drop into the chat)
  2. Describe the lighting: "make it look like golden hour with soft shadows"
  3. Wait about 60-120 seconds
  4. Download the finished MP4

No account needed for your first 100 credits. Works with MP4, MOV, AVI, WebM.

平台分布

OpenClaw

97.46%
按下载量换算1,000

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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