Skill UI

Provides comprehensive monitoring for the Clay data enrichment pipeline. It tracks critical operational metrics such as credit consumption velocity, enrichment success rates (hit rates), data quality scores, and lead distribution. Essential for cost control and ensuring pipeline health in data-intensive CRM workflows.

Query BindingDB for measured drug-target affinities (Ki, Kd, IC50, EC50) via REST endpoints or downloaded TSVs to support target-centric drug discovery, SAR analysis, lead profiling, and benchmarking datasets.

This skill provides comprehensive tracking and visualization for Security Operations Center (SOC) performance. It calculates critical metrics such as Mean Time to Detect (MTTD), Mean Time to Respond (MTTR), and alert quality ratios using SIEM data. Ideal for SOC leadership, compliance auditing, and continuous process improvement initiatives needing quantifiable security posture reporting.

This skill guides the systematic process of identifying and verifying candidate football entities (players or clubs). Use it when initial search results suggest a lead, or when the question provides enough detailed constraints (e.g., nationality, era, league) to hypothesize a candidate. The technique involves constructing targeted name-based searches and cross-checking every constraint (birth year, career timeline, etc.) against the found profile to ensure accuracy.

This advanced research technique is designed for deep dives into football topics. Instead of relying solely on the original query, it mandates tracking every discovered entity—such as player names, club names, or coaches—from search results. By treating these entities as new leads, the user must formulate follow-up searches using the discovered names and remaining constraints, ensuring nothing relevant is overlooked and building a comprehensive knowledge chain.

This advanced skill generates comprehensive, professional-grade market research reports (50+ pages) modeled after top consulting firm deliverables (McKinsey, BCG). It supports deep data analysis using research-lookup, multi-framework strategic assessment (PESTLE, SWOT, Porter's Five Forces), and extensive visual generation using scientific schematics and image generation tools. The output is in professional LaTeX format, compiled to PDF, suitable for strategic planning, investment decisions, and thought leadership.

Medchem is a powerful Python library designed for molecular filtering and prioritization in drug discovery. It allows users to apply rigorous, literature-derived drug-likeness rules (e.g., Lipinski, Veber, CNS), detect structural alerts (PAINS, NIBR), calculate complexity metrics, and combine multiple criteria using a custom query language. It is essential for compound library triage and hit-to-lead optimization.

Qiskit is a leading open-source framework for quantum computing. It enables users to build, optimize, and execute complex quantum circuits and algorithms. The platform supports running on various hardware backends, including IBM Quantum, IonQ, and local simulators. Ideal for advanced research in quantum chemistry simulations, variational quantum algorithms (VQE/QAOA), and quantum machine learning.

HasData is a comprehensive cloud platform designed for extracting structured public web data. It supports three core execution modes: Web Scraping API for arbitrary URLs (including JS rendering), pre-parsed Scraper APIs for known platforms (like Google or Amazon), and asynchronous Scraper Jobs for bulk or recursive crawling. Ideal for market research, e-commerce intelligence, job data collection, and local business lead generation.

A structured framework for performing in-depth cohort analysis. It helps measure user retention rates, estimate Lifetime Value (LTV), and segment users based on behavior over time. Use this when analyzing growth metrics, identifying churn risks, or presenting product health to leadership.