Skill UI

This skill provides comprehensive techniques for optimizing prompts used with any Large Language Model (LLM). It teaches proven methodologies—including Role definition (R), Context setting (S), Constraints (C), Instructions (I), and Templates (T)—to transform vague inputs into precision-engineered instructions. Users can reliably achieve structured JSON output, implement Chain-of-Thought reasoning, reduce hallucinations, and minimize token usage, ensuring consistent and high-quality results across different AI platforms.

This skill implements the BDI (Belief-Desire-Intention) architecture for advanced cognitive agent modeling. It allows agents to reason about context by transforming external knowledge (like RDF triples) into internal mental states (beliefs, desires, intentions) and vice versa. Key features include goal-directed planning, explainable reasoning chains, and T2B2T (Triples-to-Beliefs-to-Triples) flow, making it ideal for multi-agent systems and augmenting LLMs with formal cognitive structures.

This specialized skill acts as an expert AI auditor for Food Safety Modernization Act (FSMA) compliance. It is designed to review critical records, including HACCP plans, Preventive Controls, and Supply Chain documentation for food processing facilities. Use it to simulate FDA inspections, identify compliance gaps (such as missing CCPs or inadequate corrective actions), and receive actionable guidance to ensure the highest standards of food safety.

A comprehensive cheat sheet for the Either type in fp-ts, designed for robust error handling and flow control in TypeScript. It details how to use Either to manage synchronous operations that might fail, facilitating type-safe validation, fallible computations, and complex data chaining (e.g., replacing traditional try/catch blocks). Ideal for developers needing a quick, typed reference for functional programming patterns.

This guide provides a quick reference for 'pipe' and 'flow' utilities in fp-ts. The `pipe` function is used to chain multiple operations to transform a specific value, while `flow` allows you to create reusable, composed functions (pipelines). It is essential for implementing clean, declarative data manipulation and functional composition in TypeScript.

This guide offers a jargon-free, practical approach to functional programming using fp-ts in TypeScript. It focuses on the 80/20 principles, teaching core patterns like Pipe, Option, and Either. Learn how to handle missing values safely, manage errors explicitly, and chain operations cleanly, improving code readability without over-engineering.

TaskEither is a functional programming utility from fp-ts designed for handling asynchronous operations that might fail. It provides a robust, type-safe mechanism for managing complex async workflows, such as chained API calls or promise wrappers. Instead of relying on traditional try/catch blocks where errors can be lost, TaskEither forces the developer to explicitly handle both success and failure paths, making error management predictable and composable.

This utility is designed to build reusable, composable command-line scripts for interacting with the Hugging Face API and the `hf` command line tool. It enables complex data workflows by supporting chaining, piping, and intermediate processing across models, datasets, and repositories, streamlining the automation of Hub tasks.

A comprehensive, multi-phase security audit tool designed to evaluate AI agent skills before deployment. It detects critical vulnerabilities, including prompt injection, malicious code, excessive permissions, secret exposure, and supply chain risks, ensuring the integrity and safety of your agent environment.

A rigorous, multi-phase auditing skill designed for blockchain protocols. It verifies whether the implemented smart contract code strictly adheres to the detailed specifications provided in whitepapers, design documents, or technical specifications. It performs exhaustive, line-by-line semantic analysis to identify gaps, inconsistencies, and deviations across logic, invariants, and security guarantees, making it essential for formal compliance checking in decentralized systems.

This tool systematically audits a project's dependencies to identify potential supply chain security risks. It evaluates critical factors such as maintenance status, contributor count, popularity, and the presence of high-risk features. It is ideal for pre-security audits, assessing the overall attack surface, and mitigating risks before deployment.

This comprehensive skill allows users to manage crypto assets across seven major blockchains, including Ethereum, Solana, Bitcoin, and others. Functions include checking real-time balances, executing token swaps, analyzing detailed portfolios, and initiating secure, cross-chain transactions. It supports DeFi interaction and provides robust safety checks before execution.