This repository is a comprehensive, tool-agnostic skills and steering pack that teaches AI coding agents to perform AWS Well-Architected Framework reviews. It contains a curated reference corpus of over 2,000 markdown files (6 pillars, 307 best practices, 27 industry lenses) derived from official AWS documentation, plus per-tool adapters for 15 AI coding assistants (Claude Code, Cursor, Codex, GitHub Copilot, etc.). The repo also ships production-grade supporting tooling: a CI gating tool (wa-ci) that diffs structured review JSON against a baseline and blocks PRs on regressed gaps; an evaluation harness with blind multi-reviewer adversarial adjudication; a crawler to regenerate the reference corpus from AWS docs; and one-command installers. The core skill dispatches six parallel subagents (one per pillar) to keep the 2.2 MB corpus out of any single context window. Despite the extensive content, the repository has notable maintenance challenges: the reference snapshot will drift as AWS documentation evolves (users are responsible for regeneration); lens files are duplicated across `powers/` and `skills/` directories creating a sync hazard; and the flagship skill is explicitly deprecated in favor of a successor in Agent Toolkit for AWS. The evaluation harnesses and CI tooling are well-crafted and reusable, but the sheer scale of markdown files and platform-specific adapters makes ongoing synchronization complex.
MCPM (Model Context Protocol Manager) is a production-grade CLI tool for managing Model Context Protocol (MCP) servers. It provides a centralized server registry, global configuration, virtual profile system (tags), multi-client integration (Claude Desktop, Cursor, Windsurf, VSCode, Cline, Goose, and 10+ more), direct server execution via stdio/HTTP/SSE, secure public sharing via tunnels, and usage monitoring/analytics. The tool is designed for both interactive use and AI-agent automation (non-interactive mode with environment variables). The repository also contains a curated registry of 400+ MCP server definitions (JSON manifests) with metadata and installation instructions. While primarily a Python CLI application, the registry component adds a hybrid data/configuration dimension. The architecture follows a monolith command pattern with modular command implementations, client adapters using base class inheritance, and optional FastMCP proxy for server aggregation.