Skill UI

This abstraction provides the `CliCommandFactory` pattern, enabling developers to implement custom command-line interfaces (CLIs) for the Webiny ecosystem. It standardizes the process of defining, structuring, and interacting with various shell commands, ensuring robust and maintainable tooling within your application.

This skill analyzes your entire codebase to ensure it is optimized for AI contributions and developer tooling. It automatically generates essential configuration files such as `AGENTS.md`, Copilot instructions, CI workflows, and customizable issue templates. It learns from your existing PR review patterns to tailor the setup precisely to your project's stack. Use it when you need to prepare a repository for advanced AI-assisted development.

This comprehensive tool provides annotations and tooling to automatically generate industry-standard OpenAPI/Swagger documentation for Go backend services. By treating documentation as a contract, developers can annotate handlers, define complex parameters, and specify security schemes (JWT, OAuth2). It integrates seamlessly with major Go frameworks like Gin, Echo, and Fiber, ensuring the Swagger UI is the accurate source of truth for API consumers and maintaining clean API contracts.

This skill generates comprehensive, tailored instruction files for AI coding assistants like GitHub Copilot and Claude. It supports multiple strategies (flat or nested) and is specifically designed for managing complex monorepos by creating area-scoped instructions using `applyTo` globs. Use it to standardize AI tooling usage across large codebases.

This tool searches a comprehensive database of over 2500 curated open-source repositories for tools related to Large Language Models (LLMs), ChatGPT, RAG, agents, and NLP. It interprets natural language queries, converts non-English inputs to core English keywords, and systematically filters results across multiple specialized categories (e.g., LangChain, Chatbots, CLIs). Use it whenever the user needs to find specific AI development libraries or open-source AI tooling.

Combines a curated Japanese NLP resource dataset with live web research to produce an up-to-date trend report on models, tooling, benchmarks, embeddings, speech, and related subfields.

Generates a complete, structured load and performance testing plan for any service. This skill guides the definition of test objectives, establishes measurable SLO thresholds (p99, error rate, throughput), and designs multi-scenario tests (Baseline, Stress, Spike, Soak). It is essential for teams needing to set clear pass/fail criteria, select appropriate tooling (k6, Locust), and integrate performance gates into CI/CD pipelines.

Provides a comprehensive workflow and tooling (GuardDog) to triage npm packages and dependency trees for signs of malicious activity. It focuses on static analysis of install scripts, detecting credential exfiltration, reverse shells, and worming behavior, thereby safeguarding against software supply-chain attacks.

NetExec is a powerful, protocol-oriented tool for penetration testing, designed for assessing and exploiting Windows and Active Directory environments. It facilitates lateral movement by authenticating over protocols like SMB, WinRM, LDAP, and MSSQL. Key functions include password spraying, comprehensive network enumeration, command execution, and dumping critical credentials (SAM, LSA, NTDS) during post-exploitation phases.