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lumaluma 搜索

Agent Skill

luma 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

总安装

62,151

周安装

2,564

GitHub Stars

1

下载量

20,307
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:luma(luma 搜索)
来源仓库:https://github.com/regalstreak/luma
安装命令:
openclaw skills install luma
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 luma

简介

从 Luma (lu.ma) 获取任何城市即将举行的活动。当用户询问科技活动、初创公司聚会、社交活动、会议或班加罗尔、孟买、德里、旧金山、纽约等城市发生的事情时使用。

SKILL.md

name
luma
description
Fetch upcoming events from Luma (lu.ma) for any city. Use when the user asks about tech events, startup meetups, networking events, conferences, or things happening in cities like Bangalore, Mumbai, Delhi, San Francisco, New York, etc.
version
1.0.0
author
Clawd

Luma Events Skill

Fetch structured event data from Luma (lu.ma) without authentication. Luma is a popular platform for tech meetups, startup events, conferences, and community gatherings.

How It Works

Luma is a Next.js SSR app. All event data is embedded in the HTML as JSON inside a <script id="__NEXT_DATA__"> tag. The Python script extracts this data - no API key needed.

Quick Start

python3 scripts/fetch_events.py bengaluru mumbai --days 14

Usage

python3 scripts/fetch_events.py <city> [cities...] [--days N] [--max N] [--json]

Parameters

  • city: City slug (bengaluru, mumbai, delhi, san-francisco, new-york, london, etc.)
  • --days N: Only show events within N days (default: 30)
  • --max N: Maximum events per city (default: 20)
  • --json: Output raw JSON instead of formatted text

Popular City Slugs

  • India: bengaluru, mumbai, delhi, hyderabad, pune
  • USA: san-francisco, new-york, austin, seattle, boston
  • Global: london, singapore, dubai, toronto, sydney

Output Format

Human-readable (default)

============================================================
📍 BENGALURU — 5 events
============================================================

🎯 AI Engineers Day with OpenAI
📍 Whitefield, Bengaluru
📅 Jan 31, 2026 10:30 AM IST
👥 OpenAI, Google AI
👤 1411 going
🎫 Available (150 spots)
🔗 https://lu.ma/57tarlkp

🎯 Startup Fundraising Masterclass
📍 Koramangala, Bengaluru
📅 Feb 02, 2026 06:00 PM IST
🟢 Free (50 spots)
🔗 https://lu.ma/startup-funding

JSON output (--json)

[
  {
    "city": "bengaluru",
    "count": 5,
    "events": [
      {
        "event": {
          "name": "AI Engineers Day",
          "start_at": "2026-01-31T05:00:00.000Z",
          "end_at": "2026-01-31T12:30:00.000Z",
          "url": "57tarlkp",
          "geo_address_info": {
            "city": "Bengaluru",
            "address": "Whitefield",
            "full_address": "..."
          }
        },
        "hosts": [{"name": "OpenAI", "linkedin_handle": "/company/openai"}],
        "guest_count": 1411,
        "ticket_info": {
          "is_free": false,
          "is_sold_out": false,
          "spots_remaining": 150
        }
      }
    ]
  }
]

Event Persistence

Always save fetched events to ~/clawd/memory/luma-events.json for future reference.

This allows you to:

  • Answer questions about events without repeated fetches
  • Track which events the user is interested in
  • Compare events across cities
  • Build context about upcoming plans

When to save:

  • After fetching events for any city
  • Merge with existing data (by event URL)
  • Keep events for next 60 days only
  • Add lastFetched timestamp

Format:

[
  {
    "city": "bengaluru",
    "name": "AI Engineers Day",
    "start": "2026-01-31T05:00:00.000Z",
    "end": "2026-01-31T12:30:00.000Z",
    "url": "https://lu.ma/57tarlkp",
    "venue": "Whitefield, Bengaluru",
    "hosts": ["OpenAI", "Google AI"],
    "guestCount": 1411,
    "ticketStatus": "available",
    "spotsRemaining": 150,
    "isFree": false,
    "lastFetched": "2026-01-29T12:54:00Z"
  }
]

Common Use Cases

Find tech events this week

python3 scripts/fetch_events.py bengaluru --days 7

Check multiple cities for AI events

python3 scripts/fetch_events.py bengaluru mumbai san-francisco --days 14 --json | jq '.[] | .events[] | select(.event.name | contains("AI"))'

Get next 5 events in a city

python3 scripts/fetch_events.py new-york --max 5

Example Queries

User: "What tech events are happening in Bangalore this weekend?" → Fetch Bengaluru events for next 7 days, save to memory

User: "Any AI meetups in Mumbai next month?" → Fetch Mumbai events for next 30 days, filter for AI-related, save to memory

User: "Compare startup events in SF vs NYC" → Fetch both cities, compare, save both to memory

Notes

  • No authentication: Luma event pages are public
  • City slugs: Use lowercase, hyphenated slugs (san-francisco, not San Francisco)
  • Rate limiting: Respectful fetching only (don't hammer the servers)
  • Data freshness: Events are live data from the HTML, always current
  • Timezone: Times are in the event's local timezone (extracted from start_at)

Troubleshooting

"Could not find __NEXT_DATA__" → Luma changed their HTML structure, script needs updating

"Unexpected data structure" → The JSON path changed, check the latest HTML

No events returned → City slug might be wrong, or no upcoming events for that city

Timeout errors → Network issue, retry or check internet connection

Dependencies

  • Python 3.6+ (stdlib only - no external packages needed)
  • urllib, json, re, argparse, datetime (all built-in)

Changelog

v1.0.0 (2026-01-29)

  • Initial release
  • Support for multiple cities
  • Human-readable and JSON output
  • Date filtering (--days)
  • Event limit per city (--max)
  • Event persistence to memory file

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

70.72%
按下载量换算14,361

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

未展示

权限和风险

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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