Skill-kits is a local-first, single-binary desktop utility for managing AI agent skill directories across multiple coding agents (Codex, Claude Code, Gemini CLI, and custom agents). It operates by observing the filesystem: skills are directories containing a SKILL.md (or SKILL.md.disabled) file that agents read directly. The tool provides both a CLI (via clap) and a native GUI (via egui/eframe) that share a common core library. It does not move skills to the cloud, run a server, or require Node.js/Python runtimes. Architecturally, the system is a Rust monolith with three layers: a core library (src/core/) containing all business logic (agent space scanning, skill installation, project deployment, registry management, health checks, risk scanning), a CLI layer (src/cli/) for argument parsing and output formatting, and a GUI layer (src/gui/) for the desktop workbench. Persistent state is stored in TOML files under ~/.skill-kits/, including registries for managed skills, deployments, and a skill instance index cache. The system uses content hashing (SHA-256) for identity and drift detection, and atomic file writes for all state mutations. Key entry points include the CLI commands (status, scan, list, enable, disable, install, uninstall, doctor, adopt, project, plugin) and the GUI application launched with --gui. The core data flow involves scanning agent skill directories (global and project-level), building a normalized index of skill instances, comparing against managed copies and project deployments, and presenting the user with actionable status (drift, outdated, missing, etc.). The doctor module performs comprehensive health checks and can auto-fix certain issues. External dependencies are minimal: the Rust standard library plus crates for CLI parsing (clap), GUI (egui/eframe), serialization (serde, toml), hashing (sha2), filesystem walking (walkdir), and TOML editing (toml_edit). The system is designed to be offline-first and respects the filesystem as the source of truth for skill enablement.