Skill UI

This skill guides the design of robust, production-grade data extraction pipelines, moving beyond brittle one-off scripts. It supports three modes: API-driven web scraping (Firecrawl), traditional local Python extraction (PDF, CSV), and hybrid workflows. Key features include intelligent routing, mandatory data validation, secure key management, and adherence to scraping best practices.

A comprehensive guide for planning, promoting, and optimizing virtual events and webinars. This skill treats the event as a full conversion funnel, assisting users in maximizing lead generation and pipeline acceleration. It covers end-to-end planning, data-driven performance diagnosis (scoring funnel breaks), and setting up evergreen lead engines.

This module provides comprehensive abstractions, data types, and utilities for managing webhooks. It includes interfaces for defining payloads, tracking delivery status, dispatching events, and verifying incoming webhooks, enabling robust event-driven integration between services.

This skill generates a comprehensive, structured churn analysis, moving far beyond simple headline rates. It meticulously separates avoidable vs. unavoidable customer losses, identifies high-risk segments (by tier, cohort, etc.), calculates critical metrics like Net Revenue Retention (NRR), and pinpoints actionable early warning signals. The output culminates in prioritized, data-driven intervention recommendations to improve customer retention.

This skill generates a comprehensive, data-driven Customer Health Scorecard for any account. It assesses renewal risk, expansion potential, and overall account vitality by scoring five key dimensions: Product Adoption, Engagement, Outcomes, Support Health, and Commercial status. The output provides a weighted score (out of 100) and a RAG status (Red, Amber, Green), guiding Customer Success Managers and leadership on immediate risks and recommended actions.

This comprehensive skill applies industry-standard prioritization frameworks, including RICE, MoSCoW, Kano, and ICE, to rank product features and backlog items. It generates a scored, defensible list that includes a recommended build order, explicitly deprioritized items, and documented assumptions. Essential for Product Managers and teams needing to make data-driven, strategic decisions about the product roadmap and manage scope trade-offs.

This skill guides the decomposition of monolithic applications into independent microservices using Domain-Driven Design (DDD). It defines bounded contexts, service boundaries, communication patterns (sync/async), data ownership, and provides a structured migration roadmap (e.g., Strangler Fig Pattern). Essential for scaling and modernizing large enterprise systems.

This skill analyzes comprehensive sprint delivery data, including ticket completion rates, carry-over analysis, and unplanned work. It generates a structured, data-grounded retrospective brief, transforming raw metrics into concrete discussion prompts (Start/Stop/Continue) and actionable, testable experiments for the next iteration. It helps teams focus on measurable solutions rather than subjective debates.

This skill applies the RICE framework (Reach, Impact, Confidence, Effort) to objectively score and rank product initiatives. It helps teams prioritize backlogs, plan quarters, and compare multiple competing ideas by providing a structured, data-driven ranking. The output identifies quick wins, high-risk moonshots, and critical data gaps for validation.

A comprehensive framework for creating defensible, bottom-up sales forecasts. This model guides users through building detailed pipeline stage models, conducting scenario analysis (Upside, Base, Downside), and logging key assumptions. Ideal for sales and revenue leaders who need a systematic, data-driven approach to projecting future revenue, moving beyond simple guesswork.

A comprehensive guide for designing and implementing professional, data-driven dashboards across web, iOS, and Flutter. It details core principles like modular grid layouts, establishing data hierarchy (KPIs, charts), and maintaining minimalist aesthetics. Includes specific code examples using CSS Grid, SwiftUI, and Flutter widgets to ensure optimal user experience and data clarity.

Execute arbitrary PySpark or pure Python code directly on Fabric Spark compute using the Livy API. This method creates ephemeral sessions without generating persistent notebook artifacts. It provides full read/write access to lakehouse Delta tables, making it ideal for agent-driven ETL pipelines, quick data transformations, or analyses where session cleanup is critical. Users must manage the session lifecycle (create, run, and delete).