Skill UI

This guide clarifies the role of computation in theoretical computer science submissions, particularly for venues that prioritize theorems over empirical data. It distinguishes between legitimate forms of evidence—such as certified proof steps, constructive object discoveries, and illustrative examples—and inappropriate performance benchmarking. It helps researchers structure their work to align with theorem-based research, ensuring computational elements enhance the core theoretical contribution.

Provides a comprehensive setup for Playwright End-to-End (E2E) testing. This skill automatically analyzes your project structure (framework detection, TypeScript/JavaScript) and generates all necessary files: the core playwright.config.ts, standardized folder structure, initial test examples, and full CI/CD workflows (GitHub Actions/GitLab). It ensures your testing environment is production-ready, supporting modern frameworks like Next.js, React, Vue, and Angular.

Comprehensive reference for NetExec (nxc), a network exploitation and post-exploitation tool for Active Directory environments. Covers all protocols (SMB, LDAP, WinRM, etc.), authentication methods, password spraying, credential dumping, lateral movement, and module usage with practical command examples.

Guides creating or improving an Andru.ia skill: defines inputs/outputs, drafts SKILL.md with examples and limits, validates structure, and prepares a PR. For repetitive tasks turned into reusable instructions.

This skill focuses on designing tools for AI agents to interact with the real world effectively. It covers schema design, JSON Schema best practices, error handling, and validation. It also addresses description writing for LLMs and the emerging MCP standard. Proper tool design prevents hallucinations and ensures safety. Includes Python SDK examples for function calling.

Provides web and app implementation guidance for AI-native interfaces, covering conversational input, adaptive layouts, generative loading states, glowing borders, SwiftUI, Flutter, and CSS examples.

A comprehensive guide to product analytics, covering event tracking, funnels, cohort retention, north star metrics, OKRs, and dashboards. Examples include PostHog implementation and Python code for retention analysis. Ideal for product managers and data analysts seeking data-driven decisions.

End-to-end workflow for generating OpenAPI specs, developer guides, code examples, interactive API docs, and maintaining comprehensive API documentation.

Generate comprehensive, developer-friendly API documentation from your codebase, including endpoints, parameters, request/response examples, authentication, error handling, and OpenAPI/Swagger specs for REST, GraphQL, and WebSocket APIs.

This skill generates output schema files (dataset_schema.json, output_schema.json, key_value_store_schema.json) for Apify Actors by analyzing source code. It ensures consistency with repository conventions, derives types from TypeScript or Python definitions, and anonymizes examples. Use it when creating or updating Actor output schemas to define how results are displayed in the Apify Console.

Store, manage, and automatically rotate secrets such as database credentials, API keys, and tokens in AWS Secrets Manager using CLI and SDK examples.

Provides Java SDK guidance for Azure AI Foundry project management, including connections, datasets, indexes, deployments, and evaluations, with authentication and error handling examples.