Skill UI

This comprehensive workflow automates the creation of C4 architectural documentation for any codebase. It utilizes a bottom-up analysis approach, starting by analyzing code details (Code Level), synthesizing them into logical components, mapping containers, and finally establishing the high-level system context. Ideal for documenting complex, existing systems and ensuring comprehensive technical knowledge transfer.

Clarity Gate ensures documents entering RAG knowledge bases retain epistemic quality by generating Clarity-Gated Documents, validating Source of Truth tables, and running deterministic claim/document hash scripts before ingestion.

A sophisticated, two-stage system designed to capture and internalize user corrections and learnings during ongoing conversations. It automatically detects patterns (e.g., "use X instead of Y") and queues them. Users can manually review and apply these learnings to a persistent knowledge base (CLAUDE.md), ensuring the AI continuously improves its knowledge and adherence to specific user context for future sessions.

This skill helps transform code reviews from simple gatekeeping into a powerful knowledge-sharing mechanism. It guides users through systematic analysis of code changes, focusing on correctness, security, performance, and maintainability. Use it when reviewing pull requests, establishing best practices, or mentoring developers to ensure high-quality, robust codebase development.

Builds and restructures Confluence spaces: page hierarchy, permissions, templates, Jira macros, and knowledge-base content audits. Includes scripts to generate space structure and analyze page health.

An expert system for designing and implementing advanced AI context architectures. It specializes in integrating intelligent memory systems, vector databases, and knowledge graphs to ensure AI applications maintain coherent, relevant, and scalable state across complex, multi-agent workflows. Essential for enterprise RAG implementation and stateful AI development.

An elite AI-powered specialist mastering end-to-end customer support. This skill guides the implementation of advanced conversational AI, automated ticketing systems, and comprehensive omnichannel strategies. It covers sentiment analysis, knowledge base optimization, e-commerce support, and advanced CX analytics, ensuring seamless, human-centered, and efficient customer journeys across all platforms.

This skill provides expert guidance for modern, multi-cloud database administration. It covers comprehensive knowledge across AWS, Azure, and GCP platforms, spanning relational, NoSQL, and graph databases. Key areas include Infrastructure as Code (Terraform, Flyway), achieving high availability, disaster recovery, advanced performance optimization, and ensuring strict regulatory compliance (HIPAA, GDPR). It is essential for managing complex, highly reliable cloud data architectures.

This skill automates the creation of comprehensive documentation for relational databases (PostgreSQL/MySQL). By introspecting live schemas, it extracts detailed metadata including table structures, column descriptions, primary/foreign key relationships, indexes, views, and stored procedures. The output provides a data dictionary, entity-relationship map, and schema statistics, crucial for knowledge transfer and database lifecycle management.

This skill analyzes existing codebases to create comprehensive, long-form technical documentation. It captures the architecture, design patterns, implementation details, and rationale (the 'why') behind complex systems. Ideal for creating definitive technical manuals, system overviews, and internal knowledge bases for onboarding and maintenance.

This comprehensive workflow bundle guides the entire documentation lifecycle for software projects. It covers planning, API specification (OpenAPI), architectural design (C4 model), code commenting (JSDoc/TSDoc), generating READMEs, and maintaining structured knowledge bases (Wikis, Changelogs). Use this system when documenting a new product, maintaining an evolving codebase, or creating comprehensive technical guides.

A comprehensive workflow for executing advanced, semantic web searches using Exa. This tool moves beyond simple keyword matching, enabling deep context retrieval by understanding the intent behind the query. Key features include RAG context retrieval, content extraction (summaries, highlights, full text), and robust filtering by date range, specific domains, and content categories. Ideal for building knowledge base search features and complex research pipelines.