Skills for “analytics”
34 skills match · 240 ms · understood as
Configures the analytics side of a PostHog experiment — exposure criteria (server-resolved default exposure event vs custom exposure events), primary and secondary metrics, the supported metric types (count, sum, ratio…
Inspects PostHog Web analytics Live tab data — current users online, last-30-minutes pageviews, top pages, referrers, devices, browsers, countries, bot traffic, and the per-minute bot/users charts. Use when the user…
Add PostHog AI Observability to trace AI model usage. Use after implementing LLM features or reviewing PRs to ensure all generations are captured with token counts, latency, and costs. Also handles initial PostHog SDK…
…data, defaulting to typed runners for supported product analytics. Read it before you write HogQL/SQL. Also read it before you call execute-sql against PostHog. Use it to find or aggregate PostHog entities. These…
Add PostHog product analytics events to track user behavior. Use after implementing new features or reviewing PRs to ensure meaningful user actions are captured. Also handles initial PostHog SDK setup if not yet…
Signals scout for PostHog Customer analytics (Accounts). Watches per-account engagement for churn-risk shapes — engagement cliffs, dormancy, champion departure — and the expansion inverse.
Signals scout for per-account product-mix shifts. Watches each staked account's usage and forecasted MRR per product for one product dropping or spiking against its own baseline while the account total holds.
Signals scout for PostHog web traffic. Watches per-channel session volume, attribution breakage, and landing-page health (bounce and 404 steps) against the site's own baseline. Per- page web vitals belong to…
Signals scout for PostHog revenue analytics. Watches for upstream failures (Stripe sync stalls, capture regressions), and config drift.
Signals scout for core product-analytics flows — funnels, retention, lifecycle, stickiness, and paths. Watches the team's saved flows for a derived-rate regression while entrants hold.
Converts engineering analytics (PR / CI) data into saved PostHog insights, dashboards, and subscriptions, and explains how to query the product data directly with SQL. Covers discovering per-team GitHub warehouse tables…
…Use this skill when the user says things like "deal flow analytics", "analyze our deal flow", "review deals added in the last 12 months", "who introduced most of our deals", "breakdown of deals by sector", "where is…
…local web console for firm-wide PORTFOLIO-COMPANY ANALYTICS over Carta Fund Admin + Data Collection data — a React app (read, plus inline KPI corrections published to Carta) spanning operating KPIs, valuation,…
Catalyst Zia Services and QuickML — OCR, Face Analytics, Text Analytics, Object Detection, Barcode Scanner, Content Moderation, and AutoML predictions. Trigger on 'Zia', 'QuickML', 'OCR', 'face detection', 'text…
End-to-end analytics instrumentation workflow for a PR, branch, file, directory, or feature. Reads the code, discovers what events should be tracked, and produces a concrete instrumentation plan — all in one shot. Use…
…events. Acts as a Software Architect: discovers existing analytics patterns in the codebase, reads the hinted files to determine what variables are in scope, designs minimal chart-useful properties, and identifies…
…and produces a structured YAML change brief for downstream analytics instrumentation skills. Use this as the first step whenever a user shares a PR link, branch comparison, or raw diff and wants to understand what…
Discovers how analytics tracking calls are actually written in this codebase — the concrete SDK calls, function signatures, and import patterns used to send events. Use this skill whenever you need to understand the…
…diff-intake), generates an exhaustive list of candidate analytics events to instrument. Takes the perspective of an engineer with a PM mindset — surfaces everything worth considering so a PM can decide what actually…
…sales — by querying the Amazon Selling Partner Connector analytics tools. Always discovers the real metric IDs first (never guesses metric names), then retrieves the data with the correct filters, grouping, and time…