luma-stats

name	luma-stats
description	Pull event statistics from the Postman Dev Events Luma calendar — registrations, waitlist, attendee count, and engagement score per event. Supports filtering by MMM-YY (e.g. Apr-26), YYYY (e.g. 2026), or blank for all time. Shows sum totals across all matching events.
argument-hint	[MMM-YY | YYYY] (optional, e.g. 'Apr-26' or '2026' — blank for all time)
allowed-tools	["Bash","Write"]

Luma Event Stats

Pull registration, waitlist, attendance, and engagement data for all events on the Postman Dev Events Luma calendar. Useful for measuring event program health, spotting trends, and reporting on community growth.

How the data is fetched

The Luma Public API v1 does not include guest counts directly on event objects. Stats are derived by paging through dedicated endpoints:

• Registered — guests with approval_status == "approved" (from event/get-guests)
• Waitlisted — guests with approval_status == "waitlisted" or "pending" (from event/get-guests)
• Attended — guests where checked_in_at is not null (from event/get-guests)
• Score — (attended ÷ registered) × 5.0, shown as x.x/5.0 Progress is printed to stderr as each event is processed.

---

Configuration

This skill requires a Luma API key with read access to the calendar.

Setup

1. Get your Luma API key:

   • Log in to lu.ma as a calendar admin
   • Go to Settings → Integrations → API
   • Create a new API key with read permissions

2. Set the environment variable in .claude/settings.json:

   {
     "env": {
       "LUMA_API_KEY": "your-luma-api-key"
     }
   }
   

---

Process

Step 1: Verify API key

Check that LUMA_API_KEY is set. If it is not present, stop and tell the user to set the environment variable as described above.

echo $LUMA_API_KEY

Step 2: Write and run the data-fetch script

Read references/luma-stats.py, write it to /tmp/luma-stats.py, then execute it.

python3 /tmp/luma-stats.py [filter-arg]  # e.g. "Apr-26", "2026", or omit for all time

Capture the JSON from stdout. Progress messages go to stderr and can be ignored.

---

Step 3: Render the report

From the JSON output, produce a clean markdown report and display it in the chat immediately.

## Luma Event Stats — Postman Developer Events
**Filter:** {filter}  |  **Events:** {N}

| Date | Event | Registered | Waitlisted | Attended | Score |
|------|-------|-----------|-----------|---------|-------|
| 15 Apr 2026 | NYC Meetup | 142 | 23 | 98 | 3.4/5.0 |
| 03 Apr 2026 | London Meetup | 87 | 0 | 71 | 4.1/5.0 |
| **TOTAL** | **{N} events** | **{sum}** | **{sum}** | **{sum}** | **{score}/5.0** |

**Score** = (checked-in ÷ registered) × 5.0. Future events show `—` until check-in data is recorded.

• Sort events newest-first
• Append % to score values
• Show — for score when registered = 0
• Bold the TOTAL row

Step 4: Save to file

Save the same report to luma-output/ — create the directory if it doesn't exist.

Filename pattern:

• All time → luma-output/luma-stats-all-time.md
• Year → luma-output/luma-stats-2026.md
• Month → luma-output/luma-stats-Apr-26.md

Append a Notes section at the bottom of the file:

---
*Generated: {today's date} | Calendar: https://luma.com/postman-dev-events*
*Score = checked-in ÷ registered × 100. Future events show 0 attended until check-in data is recorded.*
*Subscriber count not available via Luma Public API v1.*

---

Score Metric

Score = (checked-in ÷ registered) × 5.0, displayed as x.x/5.0.

Score	Interpretation
4.0–5.0	Excellent turnout
3.0–3.9	Good — typical for in-person tech meetups
2.0–2.9	Below average — consider venue, timing, or topic
< 2.0	Low — flag for review
—	No registrations, or future event with no check-in data yet

---

Error Handling

Error	Action
LUMA_API_KEY not set	Stop. Show setup instructions above.
HTTP 403 Cloudflare block	The User-Agent header is required — verify it is present in HEADERS.
HTTP 401 Unauthorized	API key is invalid or expired. Ask user to regenerate in Luma Settings → Integrations → API.
Zero events returned	Check that the filter format is correct (e.g. Apr-26 not April-26). Print the parsed filter value.
All counts are 0	Future events have no check-ins yet — this is expected. Past events with 0 attended may not have used Luma check-in.