A highly parallel Perl 5 interpreter written in Rust
Axum server plus TUI for orchestrating Claude Code and Codex agents across tmux panes
x402 API gateway: proxy with per-request payment rails + embedded facilitator
Built-in Guards, Hints, and Trackers for the TraitClaw AI agent framework
Core library for Arcane - agent-native 2D game engine (TypeScript runtime, renderer, platform layer)
Arcane game engine — agent-native 2D engine with embedded TypeScript runtime
Detect hallucinated, typosquatted, and non-canonical dependencies
CLI for Arcane - agent-native 2D game engine (dev server, testing, project scaffolding)
Debug smarter, not harder — CLI tool that analyzes errors and suggests fixes
Differential testing CLI — run two programs with the same inputs, compare outputs
Minimal APM for Rails
Minimal APM for Rails - CLI
A comprehensive AI toolkit for Rails with multi-provider support, context awareness, and performance optimizations
rails-ai-context turns your running Rails app into the source of truth for AI coding assistants. Instead of guessing from training data or stale file reads, agents query 38 live tools (via MCP server or CLI) to get your actual schema, associations, routes, inherited filters, conventions, and test patterns. Semantic validation catches cross-file errors (wrong columns, missing partials, broken routes) before code runs — so AI writes correct code on the first try. Auto-generates context files for Claude Code, Cursor, GitHub Copilot, OpenCode, and Codex CLI. Works standalone or in-Gemfile.
A modular and extendable Rails engine that provides an Agent model and LLM client integration for building AI-powered applications.
Rails AI Kit provides AI building blocks for Rails apps: embeddings (OpenAI, Cohere), vector-based classification, similarity search, and generators. Start with the Classifier feature; more capabilities as the gem grows.
An LLM-powered agent for your Rails console. Ask questions in natural language, get executable Ruby code.
Rails-AI-Bridge introspects your Rails application and exposes structure to AI assistants via static context files and a live Model Context Protocol (MCP) server. It classifies Active Record models semantically (Core, Join, Supporting), optionally surfaces non-ActiveRecord Ruby classes under app/models (tagged POJO/Service), and integrates with editors and assistants such as Claude, Gemini, Cursor, and Windsurf.
rails_ai_promptable makes it easy to integrate AI-driven features into your Rails application. It allows you to define promptable methods, chain context, and connect with AI APIs like OpenAI, Anthropic, or local LLMs with minimal setup.
A gem that extends Rails helpers with AI-powered image generation. Current functionality includes a custom image_tag helper that generates images based on a description.
Provider-agnostic guardrails (PII redaction, schema validation) and evaluation/regression harness for LLM prompts and models.
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