home / skills / openclaw / skills / luma

This skill fetches upcoming tech events from Luma for specified cities and formats results for quick planning.

npx playbooks add skill openclaw/skills --skill luma

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md
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---
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

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

## Usage

```bash
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`)

```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:**

```json
[
  {
    "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
```bash
python3 scripts/fetch_events.py bengaluru --days 7
```

### Check multiple cities for AI events
```bash
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
```bash
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

Overview

This skill fetches upcoming events from Luma (lu.ma) for any city and returns structured, human-readable or JSON output. It requires no authentication and is optimized for tech meetups, startup events, conferences, and community gatherings. It also persists fetched events to a local memory file for later queries and comparison.

How this skill works

The script downloads the Luma event page HTML and extracts embedded JSON from the <script id="__NEXT_DATA__"> tag used by the Next.js app. It parses event objects, normalizes fields (name, start/end, venue, hosts, ticket info, url), and optionally outputs raw JSON. After fetching, it merges results into ~/clawd/memory/luma-events.json, keeping events for the next 60 days and adding a lastFetched timestamp.

When to use it

  • When a user asks for tech events, meetups, or startup gatherings in a city
  • To find upcoming conferences, networking sessions, or workshops in cities like Bengaluru, Mumbai, Delhi, San Francisco, New York
  • When you need structured JSON to pipe into tools or filters (use --json)
  • To compare events across multiple cities in one command
  • When you want to persist recent event data for follow-up questions or planning

Best practices

  • Use lowercase, hyphenated city slugs (e.g., san-francisco, new-york) to avoid empty results
  • Respect rate limits: fetch only needed cities and avoid rapid repeated requests
  • Set --days to limit results to a relevant time window and --max to control volume
  • Use --json when piping output to jq or other processors for further filtering
  • Always save and merge fetched data to ~/clawd/memory/luma-events.json to enable context and avoid repeated fetches

Example use cases

  • List tech meetups in Bengaluru for the next week: fetch events with --days 7 and present top entries
  • Check for AI meetups in Mumbai next 30 days, filter event names for “AI” and persist matches
  • Compare startup events between San Francisco and New York by fetching both cities, then show differences in hosts and attendance
  • Get the next 5 events in New York using --max 5 and return a concise, human-readable summary
  • Output raw JSON for automated pipelines: use --json and pipe to jq or a downstream processor

FAQ

Do I need an API key to fetch events?

No. All event data is embedded in the page HTML, so no authentication is required.

Where are fetched events stored?

Events are saved to ~/clawd/memory/luma-events.json and merged by event URL. The store keeps events for 60 days and adds a lastFetched timestamp.