aarrr-metrics
FreeMeasure and optimize growth using the AARRR (Pirate Metrics) framework with stage-specific KPIs and funnel analysis
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Monitor competitor websites for changes. Use when: tracking competitor pricing changes; monitoring new features; watching for content updates; alerting on website changes; competitive intelligence
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Run score Not tested
See how to installReview the instructions the agent will receive before you install.
Track competitor websites for changes and get alerts - stay informed about pricing, features, and content updates.
| Claude Does | You Decide |
|---|---|
| Structures analysis frameworks | Strategic priorities |
| Synthesizes market data | Competitive positioning |
| Identifies opportunities | Resource allocation |
| Creates strategic options | Final strategy selection |
| Suggests implementation approaches | Execution decisions |
pip install beautifulsoup4 requests click
# For diff comparison:
pip install diff-match-patch
python scripts/main.py watch https://competitor.com/pricing
python scripts/main.py watch https://competitor.com/pricing --selector ".price"
python scripts/main.py diff https://competitor.com/pricing --baseline cache.html
python scripts/main.py pricing https://competitor.com/pricing
python scripts/main.py batch competitors.txt --output changes/
# First, capture baseline
python scripts/main.py watch https://competitor.com/pricing --save baseline.html
# Later, check for changes
python scripts/main.py diff https://competitor.com/pricing --baseline baseline.html
# Output:
# Changes Detected!
# ─────────────────────
# - Starter: $29/mo → $39/mo (+34%)
# - Pro: $99/mo (unchanged)
# + New: Enterprise tier added
# Create competitor list
cat > competitors.txt << EOF
https://competitor1.com/pricing
https://competitor2.com/pricing
https://competitor3.com/features
EOF
# Run batch monitor
python scripts/main.py batch competitors.txt --output ./snapshots/
# Output: Creates timestamped snapshots for each URL
category: automation
subcategory: competitive-intelligence
dependencies: [beautifulsoup4, requests]
difficulty: intermediate
time_saved: 4+ hours/week
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Measure and optimize growth using the AARRR (Pirate Metrics) framework with stage-specific KPIs and funnel analysis
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Calculate A/B test statistical significance. Use when: determining if test results are significant; calculating required sample size; estimating test duration; analyzing conversion experiments; making data-driven decisions
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Assess customer account health using product usage, support sentiment, payment status, and relationship signals
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Analyze paid advertising performance across channels and recommend budget reallocation to maximize ROAS and minimize CAC. Use when: planning quarterly ad budget allocation, diagnosing underperforming ad channels, deciding whether to scale spend on a channel, calculating marginal ROI across Google Ads, Meta, LinkedIn, or TikTok, rebalancing media mix after performance shifts, or setting up a test-and-scale framework for new channels.
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Use when testing skills, commands, or agents for quality. Use after creating new skills, before deploying agents, or when debugging inconsistent agent behavior. Triggers on "evaluate", "test quality", "is this skill working", or QA of AI workflows.
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Use when analyzing server logs to understand how AI crawlers (GPTBot, ClaudeBot, PerplexityBot) interact with your site. Use when optimizing content placement for LLM retrieval, diagnosing why AI search isn't citing your content, or auditing crawl patterns to find optimization gaps.
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