Agent Skill for Swift architecture design and implementation patterns.

From text & real sources to maintainable .drawio architecture models: Diagram IR with source-kind profiles, incremental sync preserving manual layout, multi-view projection, architecture-as-test with a CI action, query/review, what-if, accessible Story Mode, and a built-in MCP server

CTO-level architectural skill for Claude Code

Real-time architectural sensor that helps AI agents close the feedback loop, enabling recursive self-improvement of code quality. Pure Rust.

Make AI coding agents architecture-aware: baseline-first, evidence-verified, drift-checked, and safe across long tasks.

Standalone engineering skills for Claude Code and Codex: review, audit, optimization, testing, product discovery, architecture, and safe publishing.

Production-ready PySpark ETL template for Databricks — medallion architecture, DABs, tests, DQX, CI/CD, and agentic development with Claude Code.

A disciplined methodology for AI-assisted software development. Covers architectural constraints, validation hooks, session governance, and PAG (Pattern Abstract Grammar) for structured AI collaboration. Copy claude-setup/ into your project to start.

AI agent skill for Jetpack Compose & Compose Multiplatform (KMP/CMP). MVI architecture, Navigation 3, Koin/Hilt, Ktor, Room, DataStore, Paging 3, Coil, coroutines/Flow, animations, performance, accessibility, testing, and cross-platform patterns. Works with Codex, Cursor, Claude Code.

An agent skill focused entirely on Swift Testing, helping you write better tests, migrate from XCTest, improve test architecture, and adopt modern Swift testing patterns with confidence.

Spec-driven development workflow for AI coding agents: architecture-first planning, task decomposition, GitHub Issue/PR tracking, Deep Discuss, and adaptive control for Claude Code, Codex, Cursor, and other Markdown-capable agents.

Code intelligence CLI — function-level dependency graph across 34 languages, 34-tool MCP server for AI agents, complexity metrics, architecture boundary enforcement, CI quality gates, git diff impact with co-change analysis, hybrid semantic search. Fully local, zero API keys required.

Professional slash commands for Claude Code that provide structured workflows for software development tasks including code review, feature creation, security auditing, and architectural analysis.

Codebase intelligence for AI and humans: code health scores, auto-generated docs, git analytics, dead code detection, and architectural decisions via MCP.

🔥 An autonomous AI agent that runs your deep learning experiments 24/7 while you sleep. Zero-cost monitoring, Leader-Worker architecture, constant-size memory.

Playwright AI Agent POM MCP ServerPlaywright AI Agent using Page Object Model (POM) architecture with MCP Server integration for automated web and mobile testing

OpenBrowser is a framework for intelligent browser automation. It combines direct CDP communication with a CodeAgent architecture, where the LLM writes Python code executed in a persistent namespace, to navigate, interact with, and extract information from web pages autonomously.

AGENTS.md rules / skills for AI coding agents: Codex, Cursor & Claude Code. Inspired by Clean Code, Refactoring, DDD, Clean Architecture and DDIA programming books.

Agent Skills marketplace: framework-aware skills for code review, documentation, test-plan generation, AI-writing detection, architectural analysis, and git workflows — for Python, Go, Rust, Elixir, React, Remix, and iOS/Swift. Works with Claude Code, Codex, and any agent that supports Agent Skills.

Agent skills for fallow, codebase intelligence for TypeScript and JavaScript. Teaches AI agents how to find unused code, duplication, circular deps, complexity hotspots, architecture drift, design-system drift, and (with Fallow Runtime) hot-path and cold-path evidence. Works with Claude Code, Cursor, Codex, Gemini CLI, and 30+ agents.

ATLAS: a senior-engineer layer for Claude Code. Explore with wireframes & prototypes, clarify the essentials, capture it in HTML spec doc then let Claude Code's native plan/goal/workflow loop build. Fewer tokens, less ceremony, faster to what people pictured. KISS/YAGNI/DRY, context decides. No overengineering. Clean architecture that works.

AI code reviews grounded in 12 classic engineering books — decay risk diagnostics with book citations, severity labels, and 6 analysis modes including full-sweep auto-fix

🐙 ADLC Team Skills — Agentic SDLC for Engineering Teams

Goal-based planning and proof gate for AI coding agents