Skill UI

This comprehensive guide covers best practices for building modern Angular applications. It provides detailed instructions on component architecture, state management using Signals, advanced routing, dependency injection, handling forms (prioritizing Signal Forms), and implementing accessibility (ARIA). It also details setup procedures for new projects and modern rendering strategies like SSR.

A rigorous, data-driven methodology for improving system performance. Use this skill when aiming to significantly increase speed, reduce latency, or lower operational cost. It establishes a measurable baseline, generates testable variants based on hypotheses, runs controlled benchmarks, and validates the best performing solution through iterative testing and code promotion gates.

This tool drives and audits a website's authentication flow by executing a configurable set of adversarial probes. It checks for critical security vulnerabilities such as missing CSRF tokens, insecure session cookies, dangerous redirect leaks, and OAuth misconfigurations. It generates a structured findings report for pre-deployment security auditing.

This tool manages isolated profiles for Codex CLI and Codex Desktop, ensuring that different accounts, projects, and local states do not interfere with each other. It provides dedicated CODEX_HOME directories, allowing users to securely switch contexts (e.g., work, personal, client) on a single machine without manual environment variable management.

A comprehensive pattern for building robust and cost-efficient LLM application pipelines. This guide details combining model routing based on task complexity, immutable cost tracking, limited retry logic, and prompt caching to manage API expenditures while maintaining high quality. Essential for production systems handling variable-complexity, high-volume tasks.

This skill runs comprehensive benchmarks against structural and adversarial corpora. It measures the performance and cost efficiency of a booster model compared to leading LLM baselines (Gemini, Anthropic). Results are persisted in verifiable JSON reports, crucial for auditing claims and verifying booster win rates before publishing.

This tool validates the structural integrity of a Domain-Driven Design (DDD) codebase. It automatically detects cross-context import violations, checks for broken aggregate invariant enforcement, and verifies adherence to established patterns (like repository and event naming conventions). Essential for CI/CD gates and large-scale codebase auditing to prevent architectural leakage.

A comprehensive guide to building highly accessible user interfaces using React and Next.js. Covers best practices for semantic HTML, proper ARIA attribute usage, managing form labels and error states, and ensuring full keyboard navigation support. Essential when developing any interactive component or form.

A comprehensive multi-agent feedback loop inspired by Generative Adversarial Networks (GANs), designed to build complex, production-ready applications. It separates generation from evaluation, using a 'ruthlessly strict' evaluator (QA) to drive continuous iteration. This process ensures high design quality, robust functionality, and originality, overcoming the limitations of single-agent self-critique. Ideal for full-stack feature development and complex product specification implementation.

This advanced workflow is designed to generate comprehensive, fact-checked research reports on any complex topic. It systematically performs fan-out web searches across multiple defined angles, fetches multiple sources, and employs a rigorous adversarial verification system (3-vote) to validate claims. The final output is a highly cited, synthesized report, ideal for academic or critical business research.

This skill runs an automated evolution process designed to systematically optimize the seven core policy surfaces of an AI agent harness (e.g., planner, contextBuilder, reviewer). By mutating these policies and scoring the variants in a sandbox, it identifies crucial performance improvements without requiring expensive foundation model retraining. It is ideal for empirical configuration tuning and establishing optimized baselines.

A comprehensive framework for optimizing inventory levels and planning replenishment in multi-location retail environments. It covers advanced demand forecasting techniques (e.g., Holt-Winters, ML models), calculating safety stock based on variability, estimating promotional uplift, and generating actionable purchase orders while minimizing stockouts and excess inventory. Ideal for professionals managing complex SKU portfolios across various supply chain systems.