This repository is an OpenCode plugin that provides interactive pseudo-terminal (PTY) management for AI coding agents. It allows agents to spawn, write to, read from, and kill multiple background terminal sessions, enabling long-running processes like dev servers, watch modes, and interactive programs. The plugin exposes five tools (pty_spawn, pty_write, pty_read, pty_list, pty_kill) and two slash commands for opening a web UI. The architecture is modular: a core PTYManager orchestrates session lifecycle, output buffering (via a RingBuffer), and exit notifications, while adapters decouple the plugin from OpenCode V1 and V2 APIs. A Bun-based web server serves a React frontend with real-time WebSocket streaming and a REST API for session management. The codebase demonstrates strong TypeScript patterns, clean abstractions, and comprehensive testing (unit, integration, and Playwright E2E).
NetworkManager is the standard Linux network management daemon, providing D-Bus and file-based APIs to control network interfaces, connections, VPNs, and system-wide DNS. The architecture is a modular system daemon (`NetworkManager`) with a rich GObject-based client library (`libnm`), a command-line tool (`nmcli`), a text UI (`nmtui`), and an initrd generator for early-boot networking. The daemon manages Ethernet, Wi-Fi (via wpa_supplicant or IWD), Bluetooth, WWAN (ModemManager), VLANs, bonds, bridges, VXLAN, WireGuard, and many other device types through a pluggable device model. Configuration is stored in keyfile format (or legacy ifcfg-rh). The codebase integrates heavily with systemd (sd-event, sd-device, DHCP6 stack) and bundles several high-quality low-level C libraries (c-list, c-rbtree, c-siphash, n-acd, n-dhcp4) for performance and correctness. While the project is mature and actively maintained, it carries technical debt from deprecated subsystems (WiMAX, ifcfg-rh) and a large vendored systemd core that requires periodic upstream synchronization. Overall, it is a masterclass in large-scale system C programming using GLib, D-Bus, and modern Linux APIs.
aspeak is a text-to-speech client for Azure TTS API, written in Rust. It provides a CLI, a Rust library, and Python bindings. The core functionality synthesizes speech from plain text or SSML using either the REST or WebSocket API. The architecture is modular: the library defines two synthesizer types (`RestSynthesizer` and `WebsocketSynthesizer`) with a unified trait, and a CLI wraps these for command-line use. The Python binding exposes a `SpeechService` class. The codebase demonstrates solid Rust engineering with builder patterns, comprehensive error handling, and support for proxies, custom audio formats, and rich SSML options. It is well-tested with unit and integration tests, has CI/CD pipelines, and is actively maintained.
search-engine-parser is a Python library and CLI tool designed to scrape search engines for structured results. It provides a base class for search engine implementations with specific parsers for engines like Google, Bing, Yahoo, DuckDuckGo, and others. The tool supports both synchronous and asynchronous HTTP requests, includes caching to avoid repeated requests, and uses user-agent rotation to prevent blocking. Key features include a command-line interface (pysearch) for terminal use and a programmatic API for integration into other projects, returning results as SearchItem objects with convenient access to titles, links, and descriptions.
Liza is a disciplined multi-agent orchestration system for AI-assisted software development. It manages a pipeline of roles (orchestrator, coder, reviewer, architect) that collaborate via a behavioral contract enforced by deterministic Go code. The system provides a CLI (Cobra) and a Bubbletea TUI, with a YAML-based state file (blackboard) for persistence, Git worktree isolation per task, and a state-machine task lifecycle (planning → implementation → review → merge). It integrates with multiple LLM providers (Claude, Codex, Gemini, etc.) via their CLIs or the Agent Context Protocol (ACP). The architecture follows a clean layered design: `cmd/liza/` contains CLI commands, `internal/commands/` are thin adapters, `internal/ops/` holds core business logic (claiming, submitting, reviewing, merging, recovering), `internal/models/` defines domain types, and `internal/db/` manages the blackboard. The system is heavily test-covered with unit, integration, and lifecycle replay tests. It also includes optional codebase indexing via SCIP, Stacklit, and Semble for improved context. Key features include generation-fenced agent authority, circuit breaker anomaly detection, sprint metrics, checkpoint summaries, automated dependency repair, and pre-commit hooks. The repository is well-documented with extensive ADRs, architecture diagrams, and skill definitions. While the codebase is large and has some platform-specific code (Windows support), it demonstrates high craftsmanship in its use of idempotent lifecycle receipts, file-locking primitives, and error classification.
Jikkou is a declarative infrastructure-as-code tool for managing Apache Kafka and related data infrastructure (Schema Registry, Kafka Connect, Apache Iceberg, Confluent Cloud, Aiven, AWS Glue). It provides both a CLI and a REST API server that reconcile desired resource state (defined as YAML/JSON files) against live cluster state using a Kubernetes-style resource model (apiVersion, kind, metadata, spec). The system computes diffs between declared and actual configurations, then applies only the necessary changes via pluggable controllers and change handlers. Architecturally, the project is a multi-module Maven project with a core library that defines extension points (collectors, controllers, validations, transformations, health indicators, change reporters) and provider modules that implement these interfaces for specific platforms. The CLI uses picocli for command parsing, and the REST API server is built on Micronaut with HATEOAS links. Both share the same core API and extension registry. A GraalVM native-image build is supported for the CLI. The codebase demonstrates strong software engineering with clean interfaces, builder patterns, annotation-driven extension metadata, and comprehensive unit and integration tests using Testcontainers. Some code duplication exists across provider modules, and the large number of generated model classes introduces maintenance overhead. Overall, it is a well-crafted, production-ready tool for Kafka ecosystem resource management.
django-click is a library that bridges the Click CLI framework with Django's management command system. It allows developers to write Django management commands using Click's decorator-based API instead of the traditional Django BaseCommand class. The library provides a drop-in replacement for Click's `command` and `group` decorators that automatically register the decorated function as a Django management command, handling all the integration details such as argument parsing, help output, verbosity, settings, and color support. The architecture consists of adapter classes (`DjangoCommandMixin`, `CommandAdapter`, `GroupAdapter`) that inherit from Click's `Command` and `Group` classes and override key methods (`run_from_argv`, `create_parser`, `execute`, `print_help`) to conform to Django's command execution protocol. A `BaseRegistrator` class handles the registration process: it extracts the command name from the module name, applies Click decorators with common Django options (verbosity, settings, pythonpath, traceback, color), and sets the module-level `Command` attribute to a lambda that returns the Click command instance. This enables seamless integration with both `manage.py` invocation and `call_command()` usage. The library also provides a `pass_verbosity` decorator for accessing the Django verbosity level within Click commands, and a `ModelInstance` custom parameter type that allows commands to accept Django model instances as arguments with support for custom lookups. The code is well-tested with comprehensive test coverage for CLI invocation, `call_command` integration, error handling, color support, and edge cases like abort handling and stdout/stderr capture.
wac is a CLI tool and library for composing WebAssembly components using the WAC language, a declarative superset of WIT. It parses .wac files, resolves package references from the filesystem or a Warg registry, builds a directed acyclic composition graph, and encodes the result into a valid WebAssembly component binary (.wasm). The system is modular, with four core crates: wac-parser (lexer, AST, name resolution), wac-resolver (package resolution with filesystem and registry backends), wac-graph (graph representation and binary encoding), and wac-types (type system, subtype checking, semver-aware type aggregation). The CLI exposes commands such as `plug`, `compose`, `targets`, `parse`, and `resolve`, each targeting a specific composition workflow. The architecture follows a pipeline: WAC source text → lexing/parsing → AST resolution (name binding, type checking) → composition graph construction → binary encoding. The resolver supports both local `.wat`/`.wasm` files and remote packages from a Warg registry (feature-gated). The type system includes full component model types (primitives, records, variants, resources, streams, futures, functions, interfaces, worlds) with async function support and semver-aware compatibility checks. The composition graph handles imports, instantiations, aliases, exports, and argument wiring, and can merge compatible imports from multiple packages. External dependencies include the Bytecode Alliance ecosystem: wit-parser, wasmparser, wit-component, wasm-encoder, wasmprinter, wat, and optionally warg-client and warg-protocol for registry support. The project is actively developed with extensive test coverage, including roundtrip parsing, resolution error cases, graph encoding, and registry integration tests. It is published on crates.io and provides prebuilt binaries for Linux, macOS, and Windows.
wacrawl is a local-first Go application for importing, merging, searching, and exporting WhatsApp Desktop archive data. It reads the WhatsApp Desktop SQLite database directly from local files, normalizes it into a private SQLite store, and exposes a CLI (import, status, chats, messages, search, sql, web, backup, contacts, metadata) plus a loopback-only read-only web viewer. The system is deliberately private: no network protocol, media confined to known roots, and the web UI requires a per-run bearer token.
ecschedule is a production-grade CLI tool for managing AWS EventBridge scheduled tasks that trigger ECS tasks. Written in Go, it uses declarative YAML/JSON/Jsonnet configuration files with template functions for environment variables, tfstate lookups, and SSM parameters. The tool supports full lifecycle management: dumping existing rules, diffing local vs remote state, applying changes (create/update/delete), and manually triggering rules. It provides parallel execution for performance, unified diff output with color control, and a plugin system for tfstate and ssm integrations. The codebase demonstrates strong engineering practices: clean separation of concerns, comprehensive unit tests, CI/CD pipelines, and dependency management with dependabot. The architecture is a single-binary CLI with subcommands, leveraging AWS SDK v2 and a custom template engine that defers variable resolution for idempotent diffing. Notable design patterns include a generic parallel job executor with panic recovery and context cancellation, a 'localYAMLForDiff' normalization technique to avoid flapping diffs, and a Resource Groups search-based orphan rule detection using custom tags.
songsee is a single-binary Go CLI tool that turns audio files into spectral visualization images. It decodes audio natively (WAV, MP3) or via ffmpeg, computes an FFT specrogram, and renders nine visualiation modes (spectrogram, mel, chroma, HPSS, self-similarity, loudness, tempogram, MFCC, spectral flux) as a grid of heatmaps in PNG or JPEG format. The architecture is a monlith: the `cmd/songsee/main.go` entry point parsers flags using Kong, delegates to `internal/audio` for decoding, `internal/dsp` for signal processing (STFT, mel filtering, chroma, median filters, etc.), and `internal/render` for image generation. It produces deterministic output – same input flags yield identical bytes. The codebase is well-structured with comprehensive tests, CI/CD, and a clean separation of concerns. It demonstrates high craftsmanship in DSP optimization (e.g., bit-exact HPSS with median networks, tiling) and safe WAV parsing.
graincrawl is a local-first CLI tool written in Go that archives Granola meeting notes, transcripts, panels, and metadata into a private SQLite database. It supports multiple read-only source adapters: Granola's private desktop API (via WorkOS token), the official public API (with a scoped API key), the local plaintext desktop cache, and legacy encrypted JSON files (via Electron safeStorage decryption). The tool provides commands for syncing, searching, exporting Markdown, creating portable snapshots, and browsing via a terminal UI. The architecture is cleanly modular with separate packages for each source adapter, a shared SQLite store with schema migrations, and a syncer that orchestrates fallback logic between sources. The codebase is well-tested, has comprehensive CI/CD, and follows Go best practices. It is not a data research project; it is a production-grade application for personal data archiving.
Slidev is a developer-oriented slide presentation tool that turns Markdown files into interactive, web-based slide decks. The system is built as a monorepo with several packages: a Node.js CLI and Vite-based dev server (`packages/slidev`), a Vue 3 client application (`packages/client`), a markdown parser (`packages/parser`), shared type definitions (`packages/types`), a VS Code extension (`packages/vscode`), and scaffolding tools (`create-app`, `create-theme`). The core workflow involves parsing Markdown slides with frontmatter, rendering them as Vue components with support for code highlighting (Shiki), diagrams (Mermaid, PlantUML, KaTeX), interactive editors (Monaco), animations (v-click, v-mark), and drawing tools. Export capabilities include PDF, PPTX (both raster and editable), PNG, and Markdown via Playwright. The system also includes a Model Context Protocol (MCP) server for AI agent integration, enabling programmatic slide editing. The architecture is modular: the parser handles slide splitting and feature detection, the client provides a rich presentation UI with presenter mode, and the CLI orchestrates build, serve, and export commands. The VS Code extension adds language support, a preview panel, and AI tools. Overall, Slidev is a mature, feature-rich application for creating technical presentations with minimal friction.
The Serverless Framework is a mature, open-source CLI tool for deploying and managing serverless applications on AWS. It compiles declarative YAML/JSON configuration (serverless.yml) into CloudFormation templates, orchestrates deployments via S3 artifact uploads and stack operations, and supports a wide range of AWS event sources (API Gateway, SQS, SNS, DynamoDB Streams, etc.). The repository is a monorepo with multiple packages: `sf-core` (new unified runner), `serverless` (legacy framework with AWS plugins), `engine` (AWS SDK client abstractions), `mcp` (Model Context Protocol server for AI agent integration), and `util` (shared logging, error handling, proxy support). Key entry points include `packages/sf-core/bin/sf-core.js` and `packages/serverless/lib/plugins/index.js`. The architecture is plugin-based, with lifecycle hooks for packaging, compiling events, and deploying. External dependencies include AWS SDK v2/v3, esbuild, and various npm packages. The codebase demonstrates high craftsmanship in areas like deterministic naming, proxy wrapping, and variable resolution, though some technical drift exists (dual SDK versions, deprecated providers).
asdf is a command-line application that manages multiple runtime versions (Node.js, Python, Ruby, etc.) per project using a plugin architecture. The Go binary dispatches commands like install, set, current, exec, and reshim; it reads `.tool-versions` files searched from the current directory upward, resolves versions via environment variables, plugin callbacks, and legacy version files, then invokes plugin-provided Bash scripts for listing, downloading, and installing tools. It generates shim executables that proxy to `asdf exec` at runtime, and supports shell completions, hooks, and extension commands. Architecturally, asdf is a modular single-binary Go application with internal packages for plugins, versions, shims, resolution, configuration, Git operations, execution, and plugin index lookups. Key external runtime dependencies are bash (plugin callbacks and hooks), git (plugin repository cloning/updating), and the asdf-plugins index. The codebase reflects a rewrite from Bash to Go (v0.16+), preserving the plugin extension model while introducing typed errors, interfaces, and more maintainable package boundaries. Some legacy BATS integration tests and in-progress cleanup comments remain, but the core implementation is clean and well-organized.
This repository is a curated collection of tips, scripts, and a Claude Code plugin (dx) that enhances developer workflows with Claude Code. It is primarily a knowledge base and tooling repository, not a standalone application. The core deliverable is the dx plugin, which bundles skills for GitHub Actions debugging, conversation half/quarter-cloning, context handoffs, Reddit/HN research, private GitHub search, and version checks. The repository also includes a custom status line script (context-bar.sh), a setup script for recommended configurations, and extensive markdown content documenting 49 tips for using Claude Code effectively. The architecture is a mix of bash scripts, skill definitions (markdown with YAML frontmatter), and a plugin manifest. The standout component is the half-clone-conversation.sh script, a 400+ line bash utility that clones Claude Code conversations with careful edge-case handling, cross-platform support (macOS, Linux, Windows Git Bash), and a comprehensive 19-test suite. The repository demonstrates high craftsmanship in its bash scripting, thorough testing, and detailed documentation of workarounds for platform limitations (e.g., Reddit's blocking, GitHub's private repo search).
XcodeGen is a command-line tool written in Swift that generates Xcode project files (.xcodeproj) from a declarative YAML or JSON specification (typically project.yml). It eliminates the need to manually manage Xcode project files by deriving the project structure from the filesystem and a concise spec, supporting all major Apple platforms (iOS, macOS, tvOS, watchOS, visionOS) and a wide range of product types including applications, frameworks, libraries, extensions, App Clips, and more. The tool integrates with Swift Package Manager, Carthage, and CocoaPods, and can generate schemes, breakpoints, Info.plist files, and build settings from layered presets. The architecture is modular: the ProjectSpec module defines the domain models and parsing logic for the spec format; XcodeGenKit contains the core generation logic (PBXProj generation, scheme generation, source file organization, settings resolution); XcodeGenCLI provides the command-line interface using SwiftCLI; and XcodeGenCore offers utility components like globbing, atomic properties, and path extensions. The tool is designed for automation and CI workflows, with caching support and pre/post generation commands. The codebase is well-structured with clear separation of concerns, extensive test coverage (unit tests, fixture-based golden tests, performance tests), and active maintenance. It demonstrates strong Swift engineering practices including protocol-oriented design, value types, and functional patterns. While the project is mature and widely adopted (over 8,800 stars), some areas like test fixtures are large and tightly coupled to specific Xcode versions, requiring periodic updates.
RoadRunner is a high-performance PHP application server and process manager written in Go. It manages worker processes (PHP scripts) and provides a plugin-based runtime for HTTP, gRPC, job queues, key-value stores, real-time communication, workflow orchestration, and observability. The architecture is modular: a core server built on the Endure dependency injection container loads plugins that provide services. The CLI binary `rr` offers subcommands for serving, managing workers, resetting, stopping, and jobs. Configuration is via YAML (`.rr.yaml`) with environment variable substitution and includes. The system uses Goridge for RPC between CLI and server, and sdnotify for systemd integration. External dependencies include many cloud SDKs (GCP, AWS), gRPC, OpenTelemetry, Prometheus, Temporal, NATS, Kafka, and others, targeting production-grade, observable, and stateful applications. The project is MIT-licensed and maintained by SpiralScout, with CI/CD for cross-platform builds (Linux, macOS, Windows, FreeBSD) and Docker images.
Arduino CLI is a command-line tool and gRPC daemon for Arduino embedded development. It manages board platforms (cores), libraries, sketches, compilation, upload, monitoring, and debugging. The architecture is dual: a CLI frontend using the Cobra framework and a gRPC server (daemon mode) that exposes the same operations via protobuf-defined services. The core domain logic is organized under `internal/arduino/` with subsystems for building (preprocessor, compiler, linker, diagnostics), package management (index loading, install/uninstall, dependency resolution), sketch handling (profiles, YAML config), and hardware discovery/monitoring. External dependencies include gRPC, protobuf, Cobra/Viper for CLI, and Arduino-specific libraries for path handling, properties, serial communication, and pluggable discovery protocols. The system supports cross-platform operation (Linux, macOS, Windows) and includes extensive integration tests that exercise real CLI commands against isolated environments.
Stoplight Prism is an open-source HTTP mock server and validation proxy driven by OpenAPI specifications (v2, v3, v3.1) and Postman Collections. It provides two primary CLI commands: `prism mock` to simulate an API from a schema definition, and `prism proxy` to validate requests and responses against a spec while forwarding traffic to a real upstream. The architecture is a monorepo with four packages (`core`, `http`, `http-server`, `cli`) that implement a functional pipeline: route matching, input validation (body, headers, query/path parameters, security), content negotiation, and response generation (static examples or dynamic faker-generated data). It also supports callback mocking, CORS handling, and RFC 7807 problem detail errors. The codebase is written in TypeScript with heavy use of fp-ts for composable error handling and dependency injection via reader monads. While the project is mature and well-tested (unit, integration, and a text-based harness test suite), its tight coupling to Stoplight internal packages and the steep learning curve of fp-ts reduce its overall reusability for external projects. It is not a data research repository.