Skill UI

This skill defines canonical, ordered middleware patterns for LangChain and LangGraph agents. It addresses critical production-level LLM deployment issues, including PII leakage across tenants, token budget overconsumption, prompt injection defense (Guardrails), and cache key corruption. Use this to build secure, scalable, and cost-aware AI applications.

A remote MCP server designed for AI agents to dynamically discover, inspect, and verify external tools, APIs, and services. It allows agents to search a curated index of AI-ready websites, check for machine-readable endpoints (like OpenAPI or MCP), and confirm if an endpoint responds correctly to JSON-RPC, enabling robust, dynamic agent workflow building.

This skill provides a comprehensive framework for security auditing LLM agents that possess external tools (file system access, command execution, network calls). It employs advanced dialogue probing techniques—such as command injection, path traversal, and SSRF attempts—to identify vulnerabilities where the agent might be induced to execute unexpected or malicious code, or access sensitive resources. Essential for red teaming and securing agent functionalities.

This skill provides a structured framework for capturing, organizing, and maintaining persistent facts about the user. By segmenting facts into topic-specific files (e.g., coding preferences, tech stack, goals), it creates a reliable, objective knowledge base. This structure is crucial for AI agents and applications to achieve highly personalized interactions and provide accurate context.

This guide provides comprehensive migration patterns for upgrading existing Webiny v5 code to the v6 architecture. It details key architectural shifts, such as replacing ContextPlugins with Dependency Injection (DI) services, converting event subscriptions to EventHandler features, and restructuring plugin arrays into feature registrations. It is an essential resource for developers and AI agents performing major framework upgrades.

A powerful tool for executing complex, multi-step, and multi-agent workflows defined in YAML format directly within the AI session. It acts as an orchestration engine, simulating various roles (agents) to complete tasks sequentially or in parallel, without requiring external API keys or configuration. Ideal for complex business process automation and multi-role content generation.

This skill is designed for tackling complex, multi-step software development tasks. It generates highly detailed, structured implementation plans that strictly adhere to best practices like TDD, YAGNI, and DRY. The plan breaks down features into small, atomic, executable tasks, specifying required file changes, writing initial failing tests, implementing minimum necessary code, and committing. It ensures the resulting plan is ready for efficient, autonomous execution by AI agents or human teams.

This guide outlines a sophisticated development workflow using dedicated subagents for each independent task within a plan. It mandates a two-stage review process—first for specification compliance, then for code quality—ensuring highly reliable, high-quality, and rapidly iterative development cycles while maintaining strict context isolation.

This guide provides comprehensive best practices for creating, structuring, and optimizing reusable 'Skills' for advanced AI agents. It maps the concept of Test-Driven Development (TDD) onto documentation writing, covering YAML frontmatter rules, optimal description writing (focusing on trigger conditions, not workflows), and maximizing token efficiency for superior AI compliance.

This comprehensive guide serves as a decision flowchart for developers using Claude Code. It details when to use specific slash commands (/plan, /compact, /loop), select specialized agents (planner, code-reviewer, build-error-resolver), or invoke workflow skills (e2e-testing, tdd-workflow). It helps users select the optimal tool combination for complex tasks across the entire software development lifecycle, including feature planning, bug fixing, testing, and architectural design.

This skill automates the process of making any codebase ready for advanced AI assistance. It analyzes your repository structure, review patterns, and stack details to generate essential configuration files, including AGENTS.md, copilot-instructions.md, CI workflows, and issue templates. Use this when setting up a new project or integrating advanced AI tooling into your existing development workflow.

This skill guides the integration of BuyWhere's product catalog, enabling AI shopping agents to perform advanced functions like structured product searching, real-time price comparison across multiple merchants, and systematic deal discovery. Use this when your agent needs robust, merchant-aware commerce capabilities through BuyWhere's official API or MCP setup path.