Mole is a macOS system maintenance CLI tool that provides a unified interface for cleaning caches, uninstalling applications, analyzing disk usage, monitoring system health, and optimizing performance. It combines two Go binaries (cmd/analyze for disk exploration with a Bubble Tea TUI, cmd/status for real-time system metrics) with an extensive shell script library for orchestration and system-level operations. The `mo` command dispatches to subcommands like `clean`, `uninstall`, `analyze`, `status`, `optimize`, `purge`, and `installer`. The architecture is hybrid: Go handles performance-critical tasks (concurrent directory scanning with semaphore-based concurrency, hardlink deduplication, gob-based caching, and interactive TUI rendering) while Bash scripts manage cleanup logic, safety guards (path identity snapshots, whitelists, process guards), Homebrew integration, and sudo session management. Key data flows include disk scanning with progress events and cache invalidation, system metrics collection via gopsutil and macOS commands (system_profiler, ioreg, pmset), and cleanup operations with dry-run previews and bounded timeouts. External dependencies include Homebrew (for cask detection and uninstall), macOS system commands (tmutil, plutil, diskutil, osascript), and Go modules (charmbracelet/bubbletea, lipgloss, gopsutil). The codebase emphasizes safety with fail-closed policies, identity re-verification before deletion, and extensive timeout handling. It supports both interactive TUI and non-interactive JSON output for scripting.
OpenEvolve is an open-source evolutionary coding agent that uses large language models (LLMs) to iteratively improve programs. It implements a MAP-Elites quality-diversity algorithm with island-based evolution, supporting multiple LLM backends (OpenAI, Claude Code, etc.) and a cascade evaluation pattern. The system accepts a user-provided initial program and an evaluator script, then repeatedly mutates the program via LLM-generated SEARCH/REPLACE diffs or full rewrites, evaluates the fitness, and maintains a diverse population across feature dimensions. The core architecture is a library with a CLI entry point (`openevolve-run`), a high-level API (`run_evolution`, `evolve_function`, `evolve_code`), and a controller that orchestrates the evolution loop, prompt sampling, LLM inference, parallel evaluation, and database storage. The repository includes 20+ diverse examples ranging from algorithm optimization (AlgoTune, TSP, circle packing) to mathematical discovery (Heilbronn, kissing number) and hardware-specific kernel tuning (MLX Metal, MLIR). The codebase is well-structured with extensive unit and integration tests, typed configuration, and a modular design that separates concerns (evaluator, LLM, database, prompt templates). It is actively maintained with frequent commits and responsive issue triage.
Win11Debloat is a PowerShell-based Windows 10/11 debloating and configuration utility. It provides both a WPF graphical interface and a command-line interface, allowing users to remove pre-installed bloatware, disable telemetry and AI features, customize the taskbar, Start menu, File Explorer, and apply numerous registry tweaks. The tool is data-driven: feature definitions, app catalogs, and localization strings are stored in JSON files, while registry modifications are applied via `.reg` files. It supports undo operations, registry backup/restore, system restore points, and multi-user or Sysprep deployment scenarios. The architecture is modular, with dot-sourced PowerShell scripts organized into functional directories (Features, Helpers, GUI, AppRemoval, FileIO, Threading) and a comprehensive Pester test suite. External dependencies include PowerShell 5.1, winget, and standard Windows command-line tools. The codebase demonstrates high craftsmanship with reusable patterns for registry file parsing, non-blocking execution, user profile resolution, and localization.