Skill UI

A comprehensive guide for intercepting and analyzing HTTP/HTTPS traffic from mobile applications using Burp Suite. This skill walks through configuring proxies on Android and iOS, handling CA certificate installation, and executing advanced penetration testing techniques. It is essential for assessing API security, identifying data leakage, and finding authentication vulnerabilities in mobile client-server communications.

This skill guides the systematic process of mitigating endpoint vulnerabilities. It involves calculating a comprehensive risk score by combining CVSS, EPSS, and CISA KEV data to prioritize findings. The workflow covers deployment of patches via platforms like WSUS/SCCM/Intune, applying necessary configuration changes, handling zero-day workarounds, and validating the fix to ensure endpoint compliance and system security.

A systematic checklist for launching Attio API integrations into a live production environment. It covers critical best practices for ensuring stability, including robust authentication, advanced error handling (exponential backoff, retries), rate limiting strategies, data integrity checks, health monitoring endpoints, and comprehensive rollback plans. Essential for reliable SaaS deployments.

Manages the complete data lifecycle within ClickHouse. Includes setting Time-To-Live (TTL) policies for automatic data expiration, implementing GDPR/CCPA compliant deletion, PII masking, partition management, and building comprehensive audit trails. Essential for robust data governance and compliance.

This comprehensive checklist guides developers through ensuring that Fathom API integrations are robust, secure, and fully compliant for production use. It covers critical areas including secrets management, rate limiting, webhook verification, advanced error handling (like circuit breakers), PII compliance, and comprehensive monitoring setup, ensuring reliable meeting data pipelines.

This guide provides comprehensive strategies for scaling datasets that exceed the capacity of a single node. It covers various architectural patterns, including multi-tenancy with payload partitioning and sliding time window management. We detail the full scaling progression, from optimizing a single node (Vertical Scaling) to distributing data across multiple nodes via sharding (Horizontal Scaling), ensuring reliable handling of massive, growing datasets.

A comprehensive guide for establishing research reproducibility in Electronic Design Automation (EDA). It details best practices for pinning benchmark suites, disclosing specific tool versions (open/commercial), documenting technology nodes (PDKs), and handling stochastic data flows (seeds, variance). Essential for ensuring that semiconductor design claims and ML-for-EDA results are credible and verifiable by the academic community.

A comprehensive methodology guide for designing and auditing empirical studies in software engineering, specifically focused on maintenance, evolution, and change impact. It outlines best practices for ensuring evidence is proportional to the claim, managing data provenance (SHAs, criteria), handling statistical confounds (survivorship, effect sizes), and integrating rigorous LLM evaluation protocols.

This guide details the process of preparing complex research artifacts (simulators, configurations, traces, and scripts) for post-acceptance evaluation, especially for microarchitecture papers. It outlines best practices for achieving ACM badges like 'Available' and 'Reproducible,' focusing on structuring the code base with tiered entry points (smoke, key, full) and handling dependencies, licensed data, and simulation time constraints.