RequestHunt Example: Deep Investigation into Calendar/Scheduling Apps

This is a complete conversation example showing how the requesthunt skill helps users conduct user demand research by collecting and analyzing real user feedback from Reddit, X (Twitter), and GitHub.

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Conversation

User

I want to use requesthunt skill to have a deep investigation into Calendar app.

Assistant

I'll help you conduct a deep investigation into Calendar apps using RequestHunt. Let me first check the API setup and then gather user feedback data.

Checking API Usage:

python3 scripts/get_usage.py

# RequestHunt API Usage

## Cached Requests
- **Used**: 1 / 2000
- **Remaining**: 1999

## Realtime Requests
- **Used**: 64 / 500
- **Remaining**: 436

API is working. Before I start collecting data, let me clarify the research scope:

Questions to define the investigation:

1. Specific Calendar apps to focus on? (e.g., Google Calendar, Apple Calendar, Outlook, Calendly, Cal.com, Notion Calendar, Fantastical, etc.)
2. Research focus? (General calendar apps / Scheduling tools / Team calendars / Personal productivity)
3. What are you trying to learn? (Feature gaps / Competitive analysis / Market opportunity)
4. Platform preference? Reddit, X, GitHub - or all three?

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User

1. cal.com and similar apps 2. Scheduling/booking tools 3. user pain points 4. all

Assistant

Starting data collection across all platforms...

Step 1: Scrape Topic

python3 scripts/scrape_topic.py "scheduling-tools" --platforms reddit,x,github

# Scrape Job Started
- **Job ID**: kx71s2ccqederm61w3whaaqhvd7zd6cq
- **Topic**: scheduling-tools
- **Platforms**: reddit, x, github
- **Status**: pending

Step 2: Search for Cal.com feedback

python3 scripts/search_requests.py "cal.com" --expand --platforms reddit,x,github --limit 50

Results (50 requests):

Request	Platform	Votes
Embed Cal.com Integration inside website	GitHub	0
Integrate NextCloudTalk with Cal.com	GitHub	3
Create Task Trigger on New Bookings (Todoist)	GitHub	3
Insights API for Booking Data	GitHub	0
Native Zoho Meeting Integration	GitHub	4
Limit Time for Cancelling/Rescheduling	GitHub	4
Add auto-accept feature for appointments	X	0
Allow rotating client secret	GitHub	0
Batch bookings together	GitHub	0
Add MCP integration for AI workflows	GitHub	0

Step 3: Search for Calendly feedback

python3 scripts/search_requests.py "calendly" --expand --platforms reddit,x,github --limit 50

Results (18 requests):

Request	Platform	Votes
Add 'blocked schedule' feature	X	267
Add reminders for scheduled appointments	X	0
Add location-specific time slots	Reddit	1
Implement booking routing based on multiple rules	Reddit	3
Implement automated reminders for no-show	Reddit	4
Add ability to delete/cancel one-use links	Reddit	2

Step 4: Search for appointment scheduling pain points

python3 scripts/search_requests.py "appointment scheduling" --expand --platforms reddit,x --limit 30

Key findings:

• SMS notifications for healthcare scheduling (8 votes)
• Flexible appointment times for therapy apps
• CRM automated follow-ups and scheduling (5 votes, 17 comments)
• Voice AI appointment reminders (16 votes)

Step 5: Search for booking software feedback

python3 scripts/search_requests.py "booking software" --expand --platforms reddit,x --limit 30

Key findings:

• GP booking system usability overhaul (259 votes)
• Simple booking system for meeting rooms (20 votes, 41 comments)
• Price drop alerts for bookings (18 votes)

Step 6: Search for scheduling pain points

python3 scripts/search_requests.py "scheduling pain" --expand --platforms reddit,x --limit 30

Key findings:

• NomadTime: suggest optimal meeting times across timezones
• Streamline scheduling to reduce back-and-forth
• Gang scheduling support for Kubernetes (28 votes)

Step 7: Search for no-show management

python3 scripts/search_requests.py "no-show booking" --expand --platforms reddit,x --limit 20

Key findings:

• Automated reminder sequences (6 votes)
• No-show prediction models
• Over-booking systems to accommodate no-shows
• Improve refund process for no-show situations

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Generated Research Report

Executive Summary

Users of scheduling/booking tools like Cal.com and Calendly experience significant friction around time slot management, no-show prevention, integration limitations, and booking workflow inflexibility. The most critical pain points revolve around meetings being scattered throughout the day (destroying focus time), last-minute cancellations/rescheduling, and limited customization options.

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Top 10 Pain Points

1. Scattered Meetings Destroying Focus Time (HIGH PRIORITY)

Votes: 267 (X)

Users are frustrated that scheduling tools allow bookings scattered throughout the day, fragmenting their work time.

"I have a large window for meetings, and what often happens is someone will book at 13:00, another one at 15:00 and then at 16:00. Each meeting is 30 minutes and instead of having all of them one after the other I have to wait." — @ilan-grif (GitHub)

"User requests a feature in Calendly that allows booking only before or after existing meetings, creating blocks of time for focused work." — @JoshConstine (X, 267 likes)

Opportunity: Smart batching algorithm that groups meetings together automatically.

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2. Last-Minute Cancellations & Rescheduling (HIGH PRIORITY)

Votes: 4 (GitHub)

"There is a Minimum Limit (for event) that can be set up so people cannot book last minute meetings. Currently, there is no option for cancellation/rescheduling limits."

Opportunity: Cancellation/rescheduling policies with time limits and fees.

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3. No-Show Management (HIGH PRIORITY)

Votes: 6 (X)

"User wants to automate sending reminders to clients marked as no-show until they reschedule their appointment."

Opportunity: AI-powered no-show prediction + aggressive reminder sequences + overbooking options.

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4. Integration Gaps (MEDIUM-HIGH)

Missing Integration	Votes
Nextcloud Talk	3
Zoho Meeting	4
iDEAL payment (Stripe)	0
Todoist task creation	3
MCP for AI workflows	0

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5. Booking Slot Inflexibility (MEDIUM)

"When external calendar events create gaps in my availability, Cal.com offers booking slots that start at non-standard times based on when those gaps begin—rather than respecting my preferred scheduling intervals."

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6. Post-Booking Editing Issues (MEDIUM)

"Allow users to edit booking details, such as correcting email addresses, after a booking has been made instead of requiring cancellation and rebooking."

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7. Analytics & Insights (MEDIUM)

Votes: 257 (X)

"Introduce a built-in analytics dashboard that gives users clear insights into their scheduling activity."

"Meeting cost calculator based on attendee time" — 257 votes on X

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8. Notification & Reminder Gaps (MEDIUM)

Request	Votes
Voice AI reminders	16
SMS notifications	8
ntfy.sh support	0

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9. Team & Routing Complexity (MEDIUM)

"Currently, when an Event Type is set to 'Requires Confirmation,' the admin is blocked from approving a booking request if a conflicting event exists in that slot."

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10. Embed & Localization Issues (LOWER)

"Embedded calendars use browser language, not site language."

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Feature Priority Matrix

Priority	Feature	Impact
Must-Have	Meeting batching/adjacency booking	Preserve focus time
Must-Have	Cancellation/reschedule time limits	Reduce last-minute changes
Must-Have	No-show automation	Reminder sequences + prediction
Must-Have	Post-booking editing	Fix mistakes without rebooking
Should-Have	Native analytics dashboard	Booking insights
Should-Have	Broader integrations	Zoho, Nextcloud, iDEAL
Should-Have	Advanced routing rules	Multi-factor booking assignment
Nice-to-Have	AI scheduling assistant	MCP integration
Nice-to-Have	Meeting cost calculator	Time = money awareness

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Top Voted Requests (Appendix)

Request	Platform	Votes
Google Meet refund request for late meetings	X	1,829
Production-ready meeting bot API	X	332
Block scheduling (only book adjacent)	X	267
GP booking system usability overhaul	X	259
Meeting cost calculator	X	257
Big calendar component for MUI	GitHub	194

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Methodology

This report analyzed 150+ real user feedback items collected via RequestHunt from:

• Reddit: r/calendly, r/smallbusiness, r/productivity, r/CRM, r/remotework
• X (Twitter): Direct feature requests and complaints
• GitHub: Cal.com issues repository and related projects

API Usage:

• 7 search queries with realtime expansion
• 1 topic scrape job
• Total: ~75 realtime requests consumed

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Key Takeaways

1. scrape_topic.py triggers background scraping for a topic across platforms
2. search_requests.py --expand fetches fresh data in realtime (uses quota)
3. Multiple search terms help capture different aspects of the same problem
4. Quantitative data (votes, comments) helps prioritize findings
5. Final report synthesizes patterns into actionable insights