Results for “product”

Automate Amazon ASIN data lookups and operations through the Asin Data API toolkit via Rube MCP, with dynamic tool discovery and connection management.

Read-only audit of product-analytics instrumentation: event taxonomy, funnel completeness, consent-gated firing, dead/duplicate/phantom events. Use when "audit our analytics", "are we tracking the right events", "funnel instrumentation", or before iterate-post-launch. PostHog/Amplitude/Mixpanel/GA4.

Generate optimized SQL queries from natural language descriptions across multiple database platforms including BigQuery, PostgreSQL, MySQL, and Snowflake. Reads database schemas from uploaded files or diagrams to produce accurate, production-ready queries.

Extract customer reviews from e-commerce product pages, returning reviewer name, rating, date, title, body, verified purchase status, and helpful votes. Supports Amazon, WooCommerce, Shopify, and generic sites with pagination.

Build production-grade Azure Cosmos DB NoSQL services with Python/FastAPI, including client setup with dual authentication, service layer CRUD operations, partition key strategies, parameterized queries, and TDD patterns.

Run and analyze molecular dynamics simulations with OpenMM and MDAnalysis. Set up protein/small molecule systems, define force fields, run energy minimization and production MD, analyze trajectories (RMSD, RMSF, contact maps, free energy surfaces).

Use for creating, reviewing, debugging, or testing dbt SQL projects involving models, sources, ref, tests, macros, materializations, incremental models, snapshots, seeds, selectors, compiled SQL, or dbt artifacts. Do not use for generic SQL with no dbt graph, warehouse administration, semantic-layer product configuration, or orchestration outside dbt.

Delivers a daily DeFi regime verdict (RISK-ON/NEUTRAL/RISK-OFF) from five named inputs, top TVL movers with causal reasoning, and a sustainable-vs-incentive yield split to distinguish real product-market fit from emissions-pumped APY.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when "langfuse, llm observability, llm tracing, prompt management, llm evaluation, monitor llm, debug llm, langfuse, observability, tracing, llm-monitoring, evaluation, prompt-management, debugging, analytics" mentioned.

Use to measure how long new support agents take to reach proficiency and where their ramp stalls, so training and nesting can be targeted. Trigger for "how long until new hires are productive", "time to proficiency", "how is the new cohort doing", nesting or ramp design, comparing training cohorts, or a new hire being assessed before they have had time to ramp.

Turn an at-risk account into a churn-save play. It diagnoses the real reason behind the risk (not the stated one), lays out the commercial and non-commercial levers you can pull, and builds a multi-touch save sequence with owners and dates. Built for B2B customer success teams, customizable to your CRM and product analytics. Trigger on "this account is going to churn", "build a save play", "why are they leaving", "at-risk renewal", "how do I keep this account", or any retention rescue.

Turn a customer's stated goals into a success plan that predicts the renewal. It sets time-to-value milestones, names an owner on both sides for each, and picks the leading indicators that tell you a year early whether this account renews. Built for B2B customer success teams, customizable to your CRM and product analytics. Trigger on "build a success plan", "onboarding plan for this account", "what are the milestones", "how do I know they'll renew", "time-to-value plan", or any post-sale planning.

The practice of collecting, analyzing, and acting on data to drive product decisions. Great analytics isn't about dashboards—it's about insights that lead to action. Every metric should answer a question that changes behavior. This skill covers event tracking, metrics design, dashboards, user behavior analysis, and data-driven decision making. The best analytics teams measure what matters, not what's easy to measure. Use when "analytics, metrics, tracking, dashboard, funnel, cohort, retention, events, KPI, measure, data, insights, conversion, engagement, analytics, metrics, data, dashboards, tracking, funnels, cohorts, KPIs, insights" mentioned.

Turn "is this new customer going to stick?" into a first-90-day diagnostic. Day-30 / 60 / 90 activation tracking, a sales-to-success handoff quality score, champion engagement during the onboarding window, time-to-value milestone hit rate, and an early false-negative catch on customers already adopting. Built for CS leaders and CSMs, customizable to your CRM and your product-analytics tool. Trigger on "how's {account} onboarding going?", "first 90 day check on {customer}", "is {account} activating?", "time-to-value on {customer}", "handoff quality", "who's at risk in first 90 days?", or any first-90-day adoption question.

Your won/lost/churn pattern analyst. Connect a CRM plus a product-analytics tool, then turn retrospective data into forward-looking action. Three modes. (1) WON, win pattern recognition that feeds your ICP and lookalike search. (2) LOST, loss pattern plus competitive intel that feeds a messaging refresh. (3) CHURN, churn theme extraction plus predictive scoring (which active accounts look like recent churners?). Trigger on "why are we winning?", "why are we losing?", "closed-lost autopsy", "churn patterns", "competitive intel rollup", "who do we lose to most?", "show me lookalike candidates to {winning customer}", "predictive churn", "which active accounts look like churners?", or any portfolio-level pattern recognition.