gws is a production-grade Rust CLI for driving Google Workspace APIs (Gmail, Drive, Calendar, Sheets, Docs, Chat, Tasks, Classroom, Admin, and more). Its defining architectural bet is dynamic command generation: instead of shipping generated API client crates, it fetches Google's Discovery Service JSON at runtime, builds a clap command tree from the schema, and executes generic HTTP calls against resolved endpoints. A two-phase argument parse extracts the service name first, then re-parses with the dynamically constructed command set, keeping the entire Google API surface reachable without codegen. The repo is a Cargo workspace split into a reusable library crate (google-workspace: discovery models, validation, HTTP client) and the CLI binary crate, and is distributed via crates.io, npm (binary downloader), GitHub Releases, and Nix. Beyond raw API calls, a helper-command system (`+send`, `+upload`, `+agenda`, `+triage`) is implemented through a `Helper` trait that injects subcommands for multi-step workflows — MIME construction for Gmail, streaming multipart uploads for Drive, calendar agenda assembly, and cross-service orchestrations. Authentication supports interactive OAuth2 login, service accounts, pre-obtained tokens, and Application Default Credentials, with credentials encrypted at rest (AES-256-GCM) in an OS keyring or file fallback. A ratatui-based interactive setup wizard bootstraps a GCP project, enables APIs, and configures OAuth consent via gcloud. Output is structured (JSON/table/YAML/CSV/NDJSON) with stable, documented exit codes, making it suitable for both shell scripting and LLM tool calling. The repository also functions as an AI-agent integration layer: it ships 100+ SKILL.md files (per-service references, multi-step recipes, role-based personas) plus TOML registries defining personas and recipes, with a generator that produces skill documentation from CLI metadata. An experimental Model Armor integration sanitizes prompts and responses for prompt-injection attacks. Engineering quality is high throughout: extensive unit tests (several hundred cases, including security-focused edge cases), CI covering 7 build targets with real-credential API smoke tests, cargo-deny dependency auditing, changeset-based automated releases, and a Nix flake for reproducible builds. Notable risks: the entire command surface depends on Google's Discovery Documents staying available and compatible; the Gmail helper module is ~3000 lines and approaching a maintainability ceiling; two divergent OAuth implementations (yup-oauth2 fast path vs proxy-aware reqwest fallback) add maintenance burden; 15+ environment variables increase configuration complexity; and hardcoded API lists in setup tooling must be manually updated as Google adds services. These are real but moderate concerns in an otherwise well-architected, actively maintained codebase.
CloudMeet is a full-stack meeting scheduler (Calendly alternative) built entirely on Cloudflare's free tier. It uses SvelteKit for the frontend and server-side logic, Cloudflare D1 for the database, KV for caching, and Workers for cron-based email reminders. The application supports single-user (admin) operation with Google Calendar and Outlook Calendar integration, allowing attendees to book meetings that automatically create calendar events with video conferencing links (Google Meet or Microsoft Teams). It includes a comprehensive email notification system via Emailit API, customizable availability rules, event types, and a dashboard for managing bookings, profiles, and email templates. The architecture is a monolith deployed to Cloudflare Pages with a separate cron worker for reminders. The codebase demonstrates solid engineering practices: TypeScript throughout, well-structured caching layer with KV and browser cache, request coalescing, input validation, and a modular email template system. It is not a data research project; it is a production-ready application.