Skill UI

An advanced reliability wrapper for AI agents that monitors, manages, and recovers from tool call failures. It automatically handles common issues such as truncated JSON responses, API timeouts, rate limits, and mid-chain process breakdowns. By implementing sophisticated failure classification, checkpointing, and learning mechanisms, Guardian ensures complex, multi-step agent workflows remain stable and resilient.

This guide details how to implement coverage-guided fuzz testing using AFL++ within CI/CD pipelines. It covers building the fuzzing harness, utilizing advanced instrumentation (like AddressSanitizer), and configuring automated runs to discover memory corruption and input handling vulnerabilities in compiled applications. Ideal for strengthening DevSecOps practices and ensuring code reliability.

A comprehensive guide to writing robust and maintainable tests in Rust. It covers various advanced testing patterns, including Unit, Integration, Async, and Property-Based testing. Learn how to apply the TDD (Test-Driven Development) cycle (RED-GREEN-REFACTOR) to enhance code reliability and ensure high code coverage.

PydanticAI is a robust Python framework that integrates Pydantic's type-checking and validation capabilities into Large Language Models (LLMs). It allows developers to build production-ready AI agents that guarantee structured, validated outputs, moving beyond simple raw strings. Key features include supported tool calling, dependency injection for testability, and multi-model compatibility across major providers like OpenAI, Anthropic, and Gemini. Use this when reliability and correct data structure are paramount.

A comprehensive guide detailing best practices for executing commands on Windows using PowerShell and CMD. It addresses critical pitfalls such as handling spaces in file paths, ensuring correct character encoding (UTF-8), using native cmdlets, and managing long path limits. Essential for developers building robust, cross-platform Windows automation scripts.

This library provides comprehensive patterns for building robust Clinical Decision Support Systems (CDSS) integrated into Electronic Medical Records (EMR). It ensures patient safety by implementing critical checks such as drug interaction screening, weight/age/renal-adjusted dose validation, and standardized clinical scoring (e.g., NEWS2). The engine uses pure functions, guaranteeing high testability and reliability for critical medical insights.

This skill provides a comprehensive framework for validating backup reliability. It automates processes like cryptographic hash verification, running simulated restores to isolated environments, detecting silent data corruption (bit rot), and scanning for ransomware indicators. Use it before relying on backups during a major incident or ransomware attack to ensure data recoverability and compliance.

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.

Catalogs 42 cloud-agnostic design patterns that architects can apply when designing, reviewing, or operating distributed systems to boost reliability, performance, messaging, security, and deployment outcomes.

A comprehensive guide and utility for managing API interactions with BambooHR. It implements robust retry logic (with exponential backoff and jitter) to handle 503 and 429 rate limit errors. It also provides patterns for proactive optimization, such as queue-based throttling, batching data using custom reports, and utilizing incremental sync to maximize API throughput and reliability.

Automate the testing and validation of Clari export pipelines within a Continuous Integration/Continuous Deployment (CI/CD) environment. This tool helps developers ensure API connectivity, validate export schemas, and systematically test the reliability of Clari integrations, preventing deployment issues before they reach production.

A comprehensive workflow designed to build deep revenue analytics dashboards using exported Clari data. It calculates key metrics such as forecast accuracy, pipeline coverage ratios, and tracks representative performance changes. Ideal for financial analysts and sales managers needing to assess revenue health and forecast reliability.