Skill UI

This guide provides comprehensive techniques for writing highly robust, production-grade Bash scripts. It covers advanced error handling, input validation, and safety best practices essential for building reliable CI/CD pipelines, system administration utilities, and mission-critical automation scripts that must handle edge cases gracefully.

This guide provides comprehensive patterns and best practices for writing robust unit tests for shell scripts using Bats (Bash Automated Testing System). It is ideal for developers implementing Test-Driven Development (TDD) for shell utilities, setting up robust automated testing in CI/CD pipelines, and validating edge cases and error conditions in shell environments.

Automatically analyzes source files, detects or honors the requested testing framework, and produces comprehensive unit tests with mocks, edge cases, and assertions for Jest, pytest, JUnit, and other frameworks whenever users ask to generate tests.

This skill helps developers adhere to Test-Driven Development (TDD) principles by generating comprehensive, failing unit and integration tests. It is specifically designed for the 'Red' phase, ensuring that expected behaviors, edge cases (null, boundary values), and error handling are rigorously defined before any implementation code is written. It forces the definition of the 'what' before the 'how'.

This skill acts as an expert test automation specialist, capable of analyzing source code across multiple languages (Python, JavaScript, TypeScript, etc.). It generates comprehensive, maintainable unit test suites using best practices, maximizing code coverage, and specifically targeting edge cases and exception handling. Use it to ensure high code quality and structural consistency.

Master advanced testing strategies for smart contracts using industry-leading frameworks like Hardhat and Foundry. This skill covers unit testing, integration testing, gas optimization analysis, fuzzing for edge cases, and simulating real-world mainnet interactions via forking. Ideal for ensuring the security and reliability of decentralized applications (DApps).

This skill automates the creation of comprehensive test suites for any codebase. Utilizing advanced AI capabilities, it analyzes function signatures, automatically identifies potential edge cases, generates meaningful assertions, and produces necessary mock data and fixture files. It is essential for developers needing robust unit tests, increasing code coverage, and adopting Test-Driven Development (TDD) workflows across various frameworks like Jest or pytest.

Provides Wycheproof test vectors for validating cryptographic implementations against known attacks and edge cases, making it ideal for CI regression sweeps and third-party crypto audits.

This comprehensive guide outlines a rigorous, human-in-the-loop engineering workflow for leveraging advanced AI agents to complete complex implementation tasks. It mandates defining clear completion criteria, decomposing work into manageable units, and strategically routing models (Haiku, Sonnet, Opus) based on task complexity. The workflow emphasizes continuous evaluation, regression testing, security review of invariants and edge cases, and strict cost discipline to ensure robust and reliable software development using AI assistance.

This skill provides a comprehensive framework for conducting high-quality code reviews. It guides developers through checking code across four critical dimensions: Correctness (functional accuracy and edge cases), Maintainability (readability and documentation), Performance (efficiency and resource usage), and Security (input validation and vulnerability management). It also emphasizes providing actionable, constructive, and empathetic feedback.

Provides advanced debugging techniques for Notion API issues that standard troubleshooting cannot resolve. It covers response ID inspection, tracing complex permission chains, detecting property type mismatches, managing pagination edge cases, and resolving block nesting limits across Notion databases and pages. Essential for robust integration development.

A comprehensive guide detailing five validated architecture patterns for utilizing Notion as a powerful backend database. Use cases include: Headless CMS for blogging, task tracking for project management, building knowledge bases (wikis), handling form submissions, and serving as a data pipeline source. Includes schema design and code examples using TypeScript and Python.