Total Skills
5
Author Profile: clamp-sh
Skills published by clamp-sh with real stars/downloads and source-aware metadata.
Total Stars
5
Total Downloads
0
Skills Performance
Comparison chart based on real stars and downloads signals from source data.
analytics-diagnostic-method
1
Stars
1
Downloads
0
analytics-profile-setup
1
Stars
1
Downloads
0
channel-and-funnel-quality
1
Stars
1
Downloads
0
metric-context-and-benchmarks
1
Stars
1
Downloads
0
traffic-change-diagnosis
1
Stars
1
Downloads
0
Published Skills
analytics-diagnostic-method
The spine of analytics investigation. Use whenever interpreting analytics numbers, answering "why did X change", reading funnels, comparing cohorts, or presenting findings. Teaches a five-step method (load profile, frame the question, build a MECE hypothesis tree, triangulate, present with Pyramid Principle), how to separate signal from noise, and how to spot Simpson's paradox before it misleads you.
Repository SourceNeeds Review
analytics-profile-setup
One-time interview that captures the business context (industry, model, primary conversion, traffic range, ICP, data stack) into a local analytics-profile.md file. Every other analytics skill reads this file so its answers are calibrated to the right benchmarks and terminology instead of generic averages.
Repository SourceNeeds Review
channel-and-funnel-quality
Judge whether traffic is actually valuable and whether funnel drop-off is real or expected. Use when comparing marketing channels, reading a conversion funnel, or deciding where to invest. Covers volume × engagement × conversion as a matrix, vanity-traffic detection, expected step drop-off by funnel type, cohort decomposition, and mix-shift (Simpson's paradox) handling.
Repository SourceNeeds Review
metric-context-and-benchmarks
Interpret analytics metrics with correct context. Use when the user asks "is this good", "what's a normal X", or quotes a rate without denominator. Covers realistic ranges for bounce rate, engagement, session duration, pages per session, conversion rate by model type, SaaS unit economics (LTV:CAC, CAC payback, MRR churn, activation, retention), plus when each metric lies and minimum sample sizes.
Repository SourceNeeds Review
traffic-change-diagnosis
Diagnose why website traffic changed. Use when the user asks "why did traffic drop/spike", investigates an anomaly, or wants to separate tracking regressions from real behaviour changes. Walks a hypothesis tree (measurement → time-shape → channel → cohort → content), recognises common fingerprints (bot spike, tracking regression, deploy-correlated drop, SEO decay, campaign ramp), and applies sample-size discipline.
Repository SourceNeeds Review