Skill UI

This skill enables reviewing defined code diffs from correctness, authorization, and performance perspectives. It supports bounded multi-agent review when authorized, ensuring findings are reproduced centrally. Users must pin repository paths and intended behavior. It does not install orchestration engines but provides a structured procedure for code quality assurance and security validation without overstepping user authority.

Access Expo's official repository containing ~70 integration examples for third-party services like Stripe, Clerk, and Supabase. Use these examples to find canonical patterns for dependencies, configuration plugins, and code wiring when integrating libraries into existing Expo apps or scaffolding new projects. Avoid reinventing the wheel by adapting proven integration structures.

Provision and manage fully managed relational databases on Google Cloud Platform, including PostgreSQL, MySQL, and SQL Server. Configure high availability, automated backups, security settings, and private IP connections. Suitable for production workloads requiring ACID transactions and regional failover. Includes Terraform configuration examples for infrastructure as code deployment.

Audit, validate, and generate Schema.org JSON-LD markup to boost AI discoverability. Detects existing structured data, flags missing entity schemas, and outputs ready-to-use JSON-LD code with a GEO-SCHEMA-REPORT.md file.

Detects hardcoded secrets like API keys, tokens, and passwords embedded in source code, configuration files, or Infrastructure as Code (IaC). Used when an agent can access its codebase to identify security vulnerabilities at rest. Focuses on secrets stored in files rather than runtime leaks.

This skill creates or updates a shared Apple design context document for other HIG skills. It auto-discovers project details from code and assets, then gathers information on product overview, platforms, technology stack, design system, accessibility, and user context. The output is a structured markdown file used to tailor subsequent design guidance.

A skill for identifying Remote Code Execution (RCE) vulnerabilities across web applications and infrastructure. Based on bug bounty reports, it guides users to test command injection, template injection, and configuration flaws on admin consoles, APIs, and supply chain targets. Requires explicit authorization for ethical testing.

This skill provides structured patterns for combining vector similarity search with traditional keyword-based search. It is essential for building advanced Retrieval-Augmented Generation (RAG) systems, sophisticated search engines, or any retrieval task requiring high recall. Use this when pure semantic understanding is insufficient, and precise matching of specific terms (like names or codes) is necessary.

Lambda is a compact, machine-native communication protocol specifically designed for agent-to-agent (A2A) messaging. It functions as a shared, unambiguous vocabulary built from 'atoms' (2-character codes), completely bypassing the need for human natural language interpretation. It is ideal for orchestrators, task delegation, and logging structured coordination signals (like heartbeats or state changes) in multi-agent systems. Crucially, Lambda is intended only for machine communication, not for user-facing dialogue.

A comprehensive index of 46 production-grade test automation skills, covering E2E, unit, mobile, BDD, and cloud testing across 15+ languages. This skill equips AI coding assistants to act as senior QA architects, generating structured, real-world test code for major frameworks like Playwright, Selenium, Cypress, and Jest. It supports project setup, CI/CD integration, and cross-platform debugging.

This skill enforces an algorithm-first discipline, requiring the user to state the time and space complexity (Big-O), the intended data structure, and the core algorithm family before writing any complex code (loops, queries, recursion). It serves as a critical gatekeeper to prevent common performance pitfalls like O(n²) complexity, N+1 database queries, and brute-force implementation errors, significantly improving code robustness and efficiency.

This skill identifies logic bugs in code files or functions using semi-formal execution tracing. It follows a structured process: Premises, Trace, Divergence, Trigger, and Remedy. Ideal for reviewing code when specific failures aren't named but correctness is suspected.