Skills for “analytics”
51 skills match · 315 ms · understood as category: Data & Analytics
…the TPM_PROMOTION_MEASURE Data Transform, TPE Analytics app install, and optional KPI dashboard customization. Use when a customer or admin wants to set up TPE dashboards, enable Trade Promotion…
ISV App Analytics metadata types — AppAnalyticsQueryRequest and AppAnalyticsSettings. Use this skill when the user asks about retrieving managed package usage data, configuring App Analytics simulation mode, querying…
Use to build a Wave Recipe, deploy a CRM Analytics dataset or dashboard, or author the full CRMA asset stack — apps, Wave Recipes (.wdpr), datasets, and dashboards — against a connected Salesforce org via REST and…
…API route that retrieves Agentforce Vibes (AFV) metrics, analytics, data, and adoption/usage insights, including token/LOC, weekly active-user, and per-user activity. Supports local result filtering by period…
…Apps platform. Use when asked to create data apps, analytics tools, or custom interactive visualizations. A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use…
Analyze dashboards and notebooks using Davis analyzers — anomaly detection, novelty scoring, and correlation. Use when the user references a specific Dynatrace dashboard or notebook (by URL, UUID, or name) and asks what…
Predictive analytics for Dynatrace — time series forecasting with the timeseries-forecast tool, capacity saturation planning, trend and anomaly detection across hosts, services, and infrastructure.
…whether pages are indexed, what to improve, to check the analytics or funnel, after shipping a new page, or for a periodic read ("איך האתר בגוגל", "למה אין תנועה"). It runs a full on-page technical audit and reads…
…generation, with every Core endpoint's input schema, plus analytics event tracking. Use when a feature needs AI, email, files or analytics without a third-party…
Instrument an MCP server with Pendo MCP analytics in Python, TypeScript, Go, or Java. Detects which language/SDK the server is built with and wires up the matching Pendo integration — PendoMCPServer (Python), initMcp()…
Set up Pendo agent analytics in a codebase — detect the AI agent(s) and instrument them so prompts, responses, and reactions flow to Pendo. Reads the codebase to choose the best of four installation paths: the Python…
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…
…hypothesis, configuring rollout and bucketing, setting up analytics and running time, and reporting which choices are guesses. Delegates rollout decisions to configuring-experiment-rollout and metric setup to…
…pipeline health for a GitHub repo using the engineering analytics MCP tools — pull-requests (PR list with CI status), workflow-health (per-workflow CI trends), and pr-lifecycle (a single PR's timeline). Use when…
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.