subscription-slayer

Tracks subscriptions, calculates monthly and annual costs, detects likely-unused services based on last-used patterns, and generates ready-to-send cancellation email templates. Helps users stop wasting money on forgotten subscriptions.

Find and slay the subscriptions draining your wallet every month.

When to use

• The user wants to audit their recurring subscriptions.
• The user wants to know how much they spend monthly/yearly on subscriptions.
• The user suspects they're paying for services they don't use.
• The user wants to cancel a subscription and needs a cancellation email.

How it works

1. Receive a list of subscriptions as JSON (see format below).
2. Run scripts/subscription_tracker.py analyze subs.json to get:
   • Monthly and annual cost totals
   • Each subscription ranked by waste probability (how likely it's unused)
   • Ready-to-send cancellation email templates for high-waste subscriptions
3. The agent presents the analysis and offers to generate/send cancellation emails.

Subscription JSON Format

json

[
  {
    "name": "Netflix",
    "cost": 15.49,
    "billing_cycle": "monthly",
    "category": "entertainment",
    "last_used": "2024-01-15",
    "start_date": "2022-03-01",
    "auto_renew": true,
    "cancel_url": "https://www.netflix.com/cancel"
  },
  {
    "name": "Adobe Creative Cloud",
    "cost": 54.99,
    "billing_cycle": "monthly",
    "category": "software",
    "last_used": "2023-06-01",
    "start_date": "2021-01-15",
    "auto_renew": true,
    "cancel_url": "https://account.adobe.com"
  }
]

Fields

Field	Required	Description
name	✅	Subscription name
cost	✅	Cost per billing cycle
billing_cycle	✅	"monthly", "yearly", "weekly", "quarterly"
category	❌	Entertainment, software, news, fitness, etc.
last_used	❌	ISO date of last use (for waste detection)
start_date	❌	When the subscription started
auto_renew	❌	Whether it auto-renews (default true)
cancel_url	❌	URL to manage/cancel the subscription
notes	❌	Free text notes

Usage

bash

# Analyze subscriptions
python3 scripts/subscription_tracker.py analyze subs.json

# JSON output
python3 scripts/subscription_tracker.py analyze subs.json --json

# Generate cancellation emails for high-waste subscriptions
python3 scripts/subscription_tracker.py cancel subs.json --name "Netflix"

# Generate cancellation emails for all high-waste subscriptions
python3 scripts/subscription_tracker.py cancel subs.json --threshold 70

# Show only subscriptions above a waste threshold
python3 scripts/subscription_tracker.py analyze subs.json --threshold 50

# Run demo with sample data
python3 scripts/subscription_tracker.py demo

Waste Detection

The waste probability score (0–100) is calculated from:

Factor	Weight	Logic
Days since last use	40%	>90 days unused = high waste signal
Cost vs. usage frequency	25%	Expensive + rarely used = waste
Subscription age	15%	Very old subs you forgot about
Auto-renew status	10%	Auto-renewing = easy to forget
Category tendencies	10%	Some categories are more forgettable

Score interpretation:

• 80–100: Almost certainly wasting money. Cancel now.
• 60–79: Likely unused. Strong cancellation candidate.
• 40–59: Possibly underutilised. Review.
• 0–39: Probably in use. Keep.

Cancellation Emails

The script generates ready-to-send email templates with:

• Subject line
• Formal cancellation request
• Account identification placeholders
• Request for confirmation
• Legal phrasing (effective date, pro-rated refunds)

Files

• scripts/subscription_tracker.py — main analysis and email generation script
• references/waste_detection.md — detailed scoring methodology
• references/cancellation_template.md — email template reference