Skill UI

This skill analyzes raw WordPress Site Health reports (text, screenshots, or debug info). It converts diagnostic data into a prioritized, risk-tiered fix plan, identifying critical issues and recommended improvements. It provides exact, safe commands (WP-CLI/PHP snippets) necessary to address the site and strictly enforces safety protocols like backups, lint checks, and dry-runs.

WGM is a robust, agentic methodology designed to transform vague or rough requirements into working, validated software. It enforces a disciplined workflow across six stages: deep alignment (Grill), structured planning, deterministic iterative building (Loop), mandatory holdout-scenario judging, and final documentation audits. It ensures that the resulting code converges against rigorously tested acceptance criteria rather than relying on single-pass generation.

This tool reviews code changes (diffs) against existing, accepted Architecture Decision Records (ADRs). It detects potential compliance violations, architectural drift, and non-adherence to established team decisions. Use it before merging Pull Requests or during periodic audits to ensure the code respects agreed-upon architectural constraints and patterns.

Diagnoses full-stack failure modes in agent and LLM applications, including wrapper regressions, memory contamination, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings and code-first fixes for production agent systems.

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.

Automates comprehensive end-to-end Quality Assurance (QA) for deployed web applications. This skill performs multi-stage testing, including smoke tests, complex user interactions (forms, authentication), visual regression checks across breakpoints, performance monitoring (Core Web Vitals), and WCAG accessibility audits.

This technique audits user interaction flows (like button clicks) to detect subtle bugs that static analysis often misses. It specifically tracks the full sequence of state changes, identifying instances where later actions unintentionally cancel, contradict, or leave the UI in an inconsistent state due to state store side effects or race conditions. Ideal for debugging complex state management architectures (Redux, Zustand).

This utility provides garbage collection for Claude Code configurations. It periodically scans various directories—including skills, memory files, hooks, permissions, and caches—to identify orphaned, stale, or redundant configuration items. Crucially, the process is designed to be non-destructive, always requiring explicit human confirmation for every deletion to ensure a safe, audited cleanup process.

Use CronCreate to schedule background workers that must persist even after session restarts. This utility provides various recommended schedules for critical, recurring tasks like security audits, performance optimization, memory consolidation, and documentation generation. It is essential for CI/CD pipelines, continuous monitoring, and maintaining system health.

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 detailing security patterns and audit checklists for Automated Market Maker (AMM) smart contracts in DeFi. Covers critical vulnerabilities such as flash loans, slippage, reentrancy attacks, price manipulation, and integer overflow/underflow. Essential for reviewing major DeFi protocols like Uniswap.

A deterministic 'Stop hook' designed to enforce session hygiene for AI agents. It checks machine-verifiable facts such as file modification timestamps of learning logs, disk space, and predefined rationalization patterns. This gate ensures that complex tasks lead to captured knowledge, acting as a mechanical safeguard complementing AI self-auditing.