Skill UI

This skill utilizes the Kronos model to perform advanced financial time-series forecasting. It generates quantitative base predictions and then integrates news sentiment analysis to adjust and refine the forecast, making it an essential tool for finance professionals needing actionable market insights.

This skill provides robust mechanisms to interact with the Clari API, specifically designed to handle rate limiting (HTTP 429 errors) and manage asynchronous bulk export jobs. It implements exponential backoff and sequential scheduling, ensuring reliable data retrieval and forecasting exports without hitting API limits. Ideal for automated data pipelines and background job processing.

This comprehensive guide diagnoses and fixes common Clari API errors, including 401 Unauthorized, empty exports, job timeouts, and data mismatches. It provides step-by-step solutions for debugging data extraction and forecasting issues using API calls.

This skill provides blueprints for deploying Clari data export pipelines into robust, production-grade cloud environments. It guides users on setting up reliable, scheduled, and serverless data syncs using major platforms like Airflow DAGs, AWS Lambda, and Google Cloud Functions. Ideal for automating revenue forecasting and business intelligence data extraction.

A comprehensive workflow for setting up local development environments for Clari API integrations. It allows users to mock forecast data, test complex export pipelines, and iterate on data transformation logic (such as forecasting and aggregation) without requiring live API calls. Ideal for building robust dashboards and validating data workflows.

This checklist guides the secure and robust deployment of Clari API integrations into a production data pipeline. It covers crucial areas like secret management, rate limit handling, data deduplication, error resilience (circuit breakers, backoff), and comprehensive monitoring setup, ensuring reliable revenue forecasting and reporting.

This skill helps commercial leaders build accurate bookings, ARR, and pipeline forecasts by analyzing cohort retention, funnel confidence, and conversion assumptions. It generates three-tier numbers (commit, best-case, pipe-only) and identifies leaking cohorts or unreliable funnel stages, ensuring transparent reporting for boards and CFOs.

This skill generates a comprehensive capacity plan document for any service. It assists technical teams in proactively managing infrastructure by modeling traffic growth, forecasting resource utilization (CPU, memory, connections), projecting costs, and defining clear scaling strategies. Use this when assessing current resource headroom, planning for seasonal peaks, or defining a long-term infrastructure action roadmap.

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.

Expertise for demand forecasting, safety stock optimization, replenishment planning, and promotional lift estimation at multi-location retailers. Use when forecasting demand, setting safety stock, planning replenishment, managing promotions, or optimizing inventory levels.

This skill provides a structured framework for researching prediction markets when they are used as data sources, forecasting inputs, or oracle signals for business intelligence. It allows users to perform source-grounded analysis of market-implied probabilities, signal quality (e.g., liquidity, spread, age), and compare these signals against traditional internal KPIs or news sources. Crucially, it strictly separates implied signals from investment advice and trade recommendations.

A comprehensive tool for training and evaluating advanced neural network models (including LSTM, Transformer, and N-BEATS) on time-series market data. It facilitates the prediction of financial trends, generating results with confidence intervals, and comparing performance across multiple architectures. Ideal for quantitative trading research and financial forecasting.