Skill UI

Qdrant is a high-performance, Rust-powered vector database designed for production-grade RAG (Retrieval-Augmented Generation) and semantic search applications. It provides fast nearest neighbor search, supports complex hybrid search using metadata filtering, and offers horizontal scalability through sharding and replication. Ideal for building real-time recommendation systems and enterprise-level knowledge retrieval.

This skill provides a comprehensive, expert guide to the entire reverse engineering lifecycle. It covers advanced techniques for binary analysis, including static analysis (disassembly, metadata extraction, control flow mapping) and dynamic analysis (API hooking, memory tracing). Mastery includes utilizing industry-leading tools such as IDA Pro, Ghidra, radare2, and specialized frameworks like pwntools and angr. The methodology is structured for secure research, CTF challenges, and vulnerability assessment, emphasizing best practices and ethical use.

This skill acts as an expert guide for developing clean, idiomatic, and highly performant Ruby code. It specializes in the entire Rails ecosystem, covering metaprogramming, ActiveRecord patterns, gem development, and comprehensive testing using RSpec/Minitest. Use it to ensure best practices, optimal code structure, and maintainable architecture in Ruby projects.

Provides Meta AI’s Segment Anything Model for zero-shot image segmentation via interactive prompts or automatic mask generation, enabling rapid dataset creation and integration in vision pipelines.

Provides step-by-step guidance on technical SEO, on-page metadata, structured data, URLs, sitemaps, and security headers to improve visibility as per Lighthouse and Google SEO guidelines.

This skill analyzes multiple web pages to detect keyword overlap, content duplication, and potential SEO cannibalization issues. It compares topics, search intent, and metadata conflicts, providing actionable strategies like content consolidation, unique angle differentiation, and canonical implementation to improve organic search performance.

Automates the creation and validation of SEO meta tags for Frontend Development tasks, guiding developers through patterns, best practices, and production-ready setups.

This specialized skill generates comprehensive, best-practice SEO metadata packages, including optimized titles, compelling descriptions, and structured URLs. It ensures strict compliance with character limits (e.g., 150-160 characters) while strategically integrating primary and secondary keywords, emotional triggers, and clear CTAs. Use this when launching new content or needing A/B test variations to maximize search visibility and click-through rates across platforms.

Guides authors through building Claude Code plugin skills by detailing required metadata, structure, resource types, and best practices for scripts, references, assets, and progressive disclosure so Claude can load workflows efficiently.

Automates Claude skill creation by scaffolding directories, validating metadata, packaging assets, and posting summaries to Slack channels for collaborative team workflows.

A comprehensive meta-skill for validating, testing, and scoring the quality of technical skills within an ecosystem. It performs deep structural checks (SKILL.md compliance), executes Python scripts for syntax, runtime, and output validation, and generates multi-dimensional quality scores using letter grades and tier recommendations. Ideal for new skill authorship, auditing existing components, or integrating rigorous QA gates into CI/CD pipelines.

Provides a structured workflow for defining agent-agnostic subagents with isolated context, covering purpose definition, metadata configuration, prompt writing, and common specialist patterns for verification, debugging, security auditing, and review.