Skill UI

Provides Playwright-driven browser automation for scraping structured data, driving multi-step workflows, managing sessions and anti-detection tactics, and capturing screenshots/PDFs in production pipelines.

This guide enforces the 'spec-first' principle in software development, treating the specification as a non-negotiable contract. It outlines a rigorous, multi-stage workflow detailing mandatory sections (Functional/Non-Functional Requirements, Acceptance Criteria, API Contracts, Data Models) and bounded autonomy rules. Users learn how to define the system 'must do' before writing a single line of code, thereby minimizing rework and eliminating scope creep.

This skill utilizes AI/LLM reasoning capabilities combined with industry-standard OSINT tools (Sherlock, theHarvester, SpiderFoot). It correlates fragmented data—including usernames, emails, domain records, and breach data—from multiple sources into unified, confidence-scored intelligence profiles. It is ideal for deep target profiling, identity resolution, and mapping complex threat landscapes.

A type-safe, generics-first library for implementing ReactiveX streams in Golang. It provides declarative, composable pipelines for handling infinite, asynchronous data sources (like WebSockets or timers) with automatic backpressure, robust error propagation, and full Go context integration. Ideal for building real-time, event-driven architectures.

Complex Skill CLI wraps multi-line metadata and coordinates lark-cli plus Node.js binaries to expose a predictable helper for complex automation or deployment tasks within CLI-driven workflows.

Generates a single formula-driven Excel dashboard from CSV/tabular data, complete with KPI cards, charts, sparklines, and conditional formatting so analysts can instantly review metrics and share an executive-ready .xlsx output.

This guide provides comprehensive best practices for writing robust and effective unit tests using JUnit 5 in Java. It covers standard test structures (Arrange-Act-Assert), advanced data-driven testing using parameterized methods, best assertion practices (including AssertJ), and dependency isolation using mocking frameworks like Mockito. Ideal for developers aiming to improve code coverage and test reliability.

This expert tool guides users through rigorous statistical analysis, specializing in A/B testing, hypothesis testing, and interpreting experimental results. It helps define sample sizes, executes appropriate tests (Z-test, T-test, Chi-square), and critically distinguishes between 'statistical significance' and 'practical significance' to ensure data-driven decision-making for product and business strategy.

This skill provides a comprehensive framework for optimizing, improving, and debugging Large Language Model (LLM) prompts. It leverages production trace data, system evaluations, and human annotations to extract prompts from spans. Users can run a data-driven optimization loop, ensuring the AI responses meet desired quality standards. Ideal for prompt tuning, system prompt refinement, and improving overall AI output quality.

Guides on structuring NUnit test projects, naming fixtures, arranging tests, and applying standard plus data-driven attributes along with assertions and mocking tactics to keep suites clear, independent, and repeatable.

A comprehensive guide covering best practices for writing effective unit tests using the TUnit framework for .NET. Topics include structuring tests using the Arrange-Act-Assert (AAA) pattern, implementing data-driven tests via attributes, utilizing fluent assertion syntax, managing complex test lifecycles (Class/Assembly level hooks), and migrating concepts from xUnit to TUnit. Learn how to write robust, isolated, and advanced tests.

Provides guidance on organizing and writing focused XUnit unit tests, covering project setup, fact/theory patterns, assertions, mocking, and data-driven testing for reliable .NET test suites.