Skill UI

This tool provides a statistically rigorous framework for analyzing a user's private LinkedIn post performance data. It moves beyond simple averages, utilizing median/MAD and permutation testing to determine if observed patterns are genuine or statistical noise. It guides users through three steps: descriptive analysis, pattern mining, and sizing future A/B experiments, ensuring hypotheses are testable and avoiding over-conclusion. Works only with your own exported data.

This skill guides the construction of robust, production-grade backtesting systems for financial trading strategies. It helps users systematically validate performance, avoid common biases (like look-ahead bias), and implement advanced techniques such as walk-forward analysis, ensuring reliable performance estimates before live deployment.

An evidence-first procedure for system performance debugging, root-cause analysis and incident reports. Applies Brendan Gregg's USE and TSA methods to sweep resources and thread states, then drills down with off-CPU analysis and flame graphs, ending in triage notes, RCA reports or blameless postmortems.

This skill combines automated static analysis and AI tools like GitHub Copilot and SonarQube to identify bugs, vulnerabilities, and performance issues in code. It supports multi-language reviews, integrates with CI/CD pipelines, and provides actionable recommendations for security, architecture, and maintainability across various development workflows.

This skill helps transform code reviews from simple gatekeeping into a powerful knowledge-sharing mechanism. It guides users through systematic analysis of code changes, focusing on correctness, security, performance, and maintainability. Use it when reviewing pull requests, establishing best practices, or mentoring developers to ensure high-quality, robust codebase development.

Orchestrate multi-dimensional code reviews covering quality, security, performance, and testing using specialized AI agents. Includes architecture analysis, vulnerability assessment, and test coverage evaluation with actionable remediation guidance.

This skill provides a highly rigorous framework for analyzing complex public issues, platform governance, and institutional compliance. It is designed to structure evidence boundaries, assess procedural justice, and track public commitments by synthesizing source ledgers and multiple data points. It is intended as a specialized sub-routine triggered by the main CrossFrame suite, not for standalone use. Key focus areas include source verification, identifying weak signals, and mitigating AI compliance performance risks.

This skill provides a structured methodology for tackling complex bugs, performance bottlenecks, and production incidents. It guides users through reproducing issues, forming hypotheses, performing controlled experiments, and narrowing down the scope using proven strategies and tools. Ideal for deep dive troubleshooting and root cause analysis in complex software systems.

Expert DevOps troubleshooter specializing in rapid incident response, advanced debugging, and modern observability. Provides guidance on log analysis, distributed tracing, performance debugging, and system reliability engineering for cloud-native environments.

This skill orchestrates multi-agent incident response workflows using modern SRE practices. It guides users through detection, triage, investigation, and resolution phases. It helps classify severity, analyze observability data, implement mitigations, and conduct root cause analysis. Suitable for handling outages, security breaches, and performance issues with structured checklists and best practices.

A comprehensive set of production-ready runbook templates for managing technical incidents. These guides cover the full incident lifecycle, including detection, triage, mitigation, root cause analysis, and resolution procedures, ensuring systematic and rapid response to system outages and performance degradation.

This skill provides a structured workflow to scan, audit, and fix web performance issues across Lighthouse and PageSpeed Insights pillars including Performance, Accessibility, Best Practices, and SEO. It helps improve Core Web Vitals like LCP, FCP, and CLS by identifying bottlenecks such as render-blocking resources and unused JavaScript. Users should provide reports or URLs for analysis.