/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
$ npx -y skills add clamp-sh/analytics-skills --skill channel-and-funnel-quality --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/channel-and-funnel-quality
Context preview
The summary Claude sees to decide when to auto-load this skill.
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
Analytics skills for Claude, Cursor, and other AI agents. Read web analytics like a senior analyst: diagnose traffic changes, judge channel quality, read funnels, declare typed events, and read A/B tests without the usual rookie mistakes.
Repo: clamp-sh/analytics-skills
Other skills on analytics-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,
Open skill - /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
Open skill - /anomaly-detection-time-series
Formal time-series methods that augment the hand-coded fingerprint library in traffic-change-diagnosis. Use this skill when traffic-change-diagnosis fingerprints overlap, when the user asks "is this real?", or when the change date is contested. Applies STL decomposition,
Open skill - /bayesian-experiment-reader
Bayesian counterpart to experiment-result-reader. Computes posterior P(variant beats control), credible intervals, and expected loss from per-variant exposure and conversion data. Beta-Binomial for proportion metrics (CVR), Normal-Normal for continuous metrics (revenue per
Open skill - /causal-dag-builder
Build a refinable causal DAG before answering "did X cause Y" on observational data. Emits a Mermaid diagram of assumed causes, applies the back-door criterion to decide what to condition on, and forces confounders, mediators, and colliders to be named explicitly instead of
Open skill - /causal-evidence-checklist
Bradford Hill's 9 viewpoints (1965) reframed as a checklist for product analytics. Use this skill before recommending a decision based on observational analytics data. Applies the 9 Bradford Hill viewpoints to score whether X actually caused Y, or whether the correlation is
Open skill