Skill UI

This skill covers principles for identifying tasks suited to LLM processing, designing effective project architectures, and iterating rapidly using agent-assisted development. It applies to batch pipelines, multi-agent systems, and interactive applications. Key concepts include task-model fit recognition, manual prototyping, pipeline architecture, file system state management, and structured output design for reliable parsing.

Protect AI systems from prompt injection attacks by implementing input sanitization, tool permissioning, and output validation. Essential for securing LLM applications, RAG pipelines, and agentic workflows against indirect and direct attacks.

This skill helps plan engaging, structured puzzle-based activities for various settings like classrooms, parties, and corporate team-building events. Users provide the event description, target audience, and overall goal, and the planner generates a comprehensive activity schedule. It includes a minute-by-minute timeline, necessary materials checklist, and generates pre-configured generator links for diverse puzzles (Word Search, Crossword, Sudoku, etc.), ensuring content is theme-appropriate and ready for one-click use.

This skill provides language-specific super-code guidelines for Python, covering idioms, efficiency, and best practices. It includes recommendations on comprehensions, unpacking, built-ins, functions, classes, error handling, type hints, and common anti-patterns to improve code quality and readability.

This comprehensive guide provides robust strategies for testing Python code using industry best practices. It covers essential techniques like pytest, fixtures, mocking, parameterization, and implementing Test-Driven Development (TDD). Use this skill when writing unit tests, setting up complex test suites, performing integration testing, or establishing continuous testing infrastructure in CI/CD pipelines.

Guides an AI agent to give non-judgmental, evidence-informed quit-smoking support: quit planning, craving check-ins, slip debriefs, optional consent-based logging, and escalation to clinicians or quitlines. Not medical care.

A command-line interface skill for radare2, enabling binary reconnaissance, disassembly, analysis, function locating, and lightweight patching without a GUI. Supports various formats like exe, dll, elf, and apk. Ideal for scripting automation and quick terminal-based reverse engineering tasks using r2, rabin2, rasm2, and radiff2.

Expert in building Retrieval-Augmented Generation systems for LLM applications. Masters embedding models, vector databases, chunking strategies, and retrieval optimization. Capable of designing retrieval pipelines, implementing hybrid search, and optimizing context windows to ensure high-quality generation from retrieved documents.

Build and operate Retrieval-Augmented Generation (RAG) systems using vector stores, embedding pipelines, and hybrid search. This skill covers ingesting documents, generating embeddings, storing in vector databases, and serving grounded LLM responses. It includes setting up embedding pipelines, vector store infrastructure, and deploying hybrid search (dense + sparse) to reduce hallucinations and improve semantic search over large document collections.

Monitor and evaluate Retrieval-Augmented Generation (RAG) systems using measurable metrics. This skill covers retrieval quality checks like Recall@k, hallucination detection, and groundedness scoring. It enables continuous regression testing and production monitoring for AI pipelines using Python libraries like RAGAS and OpenTelemetry.

Rclone is a powerful command-line program for managing files on various cloud storage services. It supports over 70 cloud storage products including S3, Google Drive, and more. This skill provides reference and usage guides for terminal-based operations like upload, download, sync, copy, move, and mount. It includes security warnings and configuration instructions to ensure safe data handling.

This skill provides production-ready architectural patterns for building robust mobile applications using React Native and Expo. It covers complex topics like state management, sophisticated navigation flow, integrating native modules, and implementing offline-first capabilities. It is ideal for starting new projects or optimizing existing large-scale React Native applications.