Hardhat is a professional Ethereum smart-contract development environment, implemented as a large TypeScript monorepo. In production it operates as a CLI and programmatic framework that compiles Solidity, runs tests against local or remote networks, deploys contracts, verifies source code on block explorers, and manages project secrets and hardware-wallet signing. The core `hardhat` package provides a task runner, plugin system (`definePlugin`), hook handlers, config loading, and a Hardhat Runtime Environment, while companion packages add viem/ethers client integration, chai matchers, the Ignition declarative deployment engine, verification against Etherscan/Blockscout/Sourcify, Mocha and node:test runners, Foundry remapping support, coverage, gas analytics, and alternative Slang/Solx compiler backends. The architecture is a modular, hook-driven monorepo of 30+ packages. The core exposes lifecycle hooks for config, network, HRE, Solidity, and testing; plugins register tasks, global options, and hook handlers that compose through `next()` chains. Ignition-core implements a journal-based deployment state machine with reconciliation, execution strategies, and nonce management, making deployments resumable and auditable. The network layer abstracts JSON-RPC providers over HTTP and EDR-backed simulated networks, with request handlers for gas estimation, account management, and chain validation. Entry points include `packages/hardhat/src/cli.ts`, `packages/hardhat/src/hre.ts`, `packages/hardhat/src/config.ts`, and `packages/ignition-core/src/deploy.ts`. The codebase is well-engineered and heavily tested, with fixture projects, CI workflows, changesets, e2e scenarios against real-world projects, and benchmark infrastructure. It is current with Node 24 and modern TypeScript/ESM patterns. Notable minor issues include duplicated helper code across packages, hand-maintained chain/explorer mappings and hardfork lists, and some fragile workarounds around third-party CJS/ESM interop. Overall, it is a strong, actively maintained developer-tooling codebase with several genuinely reusable internal components.
Skybridge is a production-grade, full-stack TypeScript framework for building interactive MCP (Model Context Protocol) Apps and ChatGPT Apps. It provides a unified runtime to develop server-side tools with rich React-based UI views that render inside AI chat hosts like ChatGPT, Claude, Cursor, and VSCode. The framework is structured as a monorepo with packages for the core server/client library (`skybridge`), a Vite plugin for build orchestration, a developer tools SPA for local debugging, a project scaffolding CLI (`create-skybridge`), and an eval/test harness. The architecture centers on a typed MCP server implementation that handles tool registration, per-tool OAuth 2.1 authentication, an onion-model middleware system, and view resource serving. On the client side, a bridge abstraction (HostAdaptor) normalizes communication across different host protocols (OpenAI Apps SDK vs. MCP App JSON-RPC), while React hooks provide type-safe access to tool calls, view state, user context, and display modes. The framework emphasizes a 'reason, then render' two-phase pattern: a tool call computes data, then a view displays it interactively. Extensive examples cover e-commerce, games, authentication, productivity dashboards, and generative UI, demonstrating the framework's flexibility. Skybridge is not a data research project; it is a developer toolchain for building agent-native applications.
e18e/cli is a command-line tool that analyzes JavaScript and TypeScript projects for packaging issues, dependency health, and opportunities to replace dependencies with lighter or native alternatives. It runs multiple checks: publint for publishing best practices, dependency replacement suggestions from curated manifests (native, preferred, micro-utilities), core-js polyfill analysis against declared engine ranges, duplicate dependency detection, and web feature codemod suggestions. The CLI also includes a `migrate` subcommand that can automatically apply codemods to rewrite imports for selected replacements. The architecture is plugin-based: each analysis is a self-contained `ReportPlugin` that receives an `AnalysisContext` and returns messages and stats, aggregated by a `runPlugins` orchestrator. The tool uses an abstract `FileSystem` interface with a `LocalFileSystem` implementation, making it extensible for custom environments. Output is either an interactive TUI via @clack/prompts or JSON. This is a pre-1.0 project, actively developed with good code quality and comprehensive tests.
The gvm-tools repository provides a Python library and command-line utilities for interacting with Greenbone Vulnerability Management (GVM) systems via the Greenbone Management Protocol (GMP). It consists of a core library (gvmtools) that handles GMP communication, authentication, and data formatting, along with three main CLI tools: gvm-cli for raw command execution, gvm-script for running Python scripts in a GMP context, and gvm-pyshell for an interactive shell. The repository includes approximately 80 example scripts in the scripts/ directory demonstrating common GVM operations such as target management, task control, report generation, and asset discovery. The architecture is library-first, with the CLI tools and scripts built on top of the gvmtools package, which abstracts the underlying GMP/XML complexity. External dependencies include the python-gvm library for protocol handling, with additional dependencies for specific scripts (e.g., terminaltables for output formatting, cpe for CPE processing).
This repository is a curated list (awesome list) of tools, frameworks, and resources for data engineering. It is not a software application or a data research project; rather, it serves as a community-maintained directory of databases, ingestion tools, stream processors, workflow orchestrators, data quality frameworks, and more. The list is organized into categories such as Databases, Data Ingestion, Stream Processing, Batch Processing, Workflow, Data Lake Management, Testing, and Community resources. Each entry includes a link and a brief description. The repository also includes contribution guidelines and CI workflows to maintain list quality. It is widely referenced (over 9,000 stars) and actively updated with new entries via pull requests. The primary value is as a reference for data engineers evaluating tools, not as executable code.
This repository defines a schema for describing custom elements manifest files. It provides a TypeScript definition file (schema.d.ts) that serves as the single source of truth for the schema, and a generated JSON Schema file (schema.json) for validation. The schema captures metadata about custom elements including their attributes, events, methods, and CSS properties. The repository includes build scripts to generate the JSON Schema from TypeScript definitions, tests to validate the schema against an example manifest, and CI/CD workflows. While the schema itself is well-designed and reusable, the project shows signs of technical drift due to outdated dependencies.
This repository is a curated collection of recipes and tools for Go development, organized into categories such as testing, dependencies, code visualization, code generation, refactoring, errors, build, assembly, deployment, execution, monitoring, benchmarking, documentation, security, static analysis, and guides. The actual codebase is minimal: a Go module with a three-line main.go that generates the README.md from a structured YAML file (page.yaml) using the mdpage library. The primary value is the content itself, which serves as a reference for Go developers to discover and utilize various tools and techniques. The project is actively maintained, with up-to-date dependencies and a simple CI workflow for markdown link validation.