— · MIT
Han: AI skills and agents for "Solo" product engineers and small teams
v3.7.0 · Apache-2.0
Senior-developer discipline for AI coding agents. A commit gate that counts unchecked as failing, quality controllers that refuse to call unfinished work done, and a lessons loop that closes each escaped bug's class. One Go binary, no runtime deps, works with 20+ agents.
v0.9.3 · Apache-2.0
A local detector for AI-writing patterns. Scores every prose file your agent saves. Python standard library only, no network, no model.
v0.67.1 · MIT
Workflow control for AI coding agents
— · Apache-2.0
AI-powered multi-agent code review. Simulates a customizable team of Engineers performing code review with built-in discourse.
— · Apache-2.0
Static analysis for AI agent configs, tool descriptions, and system prompts — catches vague tool descriptions, missing stop conditions, and schema gaps before they reach runtime. Zero-LLM, deterministic checks, built for CI.
— · MIT
The practices that made software work didn't stop working. They stopped keeping up. PAAD brings them back at AI speed.
— · MIT
Tailwind CSS v4 lint rules for oxlint that read your design system: unknown, conflicting and deprecated classes, theme colors and class order, with autofixes.
v9.7.0 · MIT
Your AI can write the UI. This makes sure it writes your UI. A deterministic scanner scores your design system 0-100 against 112 public repos, reads React and web components (Stencil, Lit), hands you a copy-paste fix prompt for each top finding, writes ru
v3.34.6 · MIT
Framework-aware code intelligence MCP server — 88 framework integrations, 81 languages, 72.7% fewer input tokens to review a pull request, comprehension at parity
v1.7.0 · MIT
AI code reviews grounded in 12 classic engineering books — decay risk diagnostics with book citations, severity labels, and 6 analysis modes including full-sweep auto-fix
v3.6.1 · MIT
Greptile code review from your terminal
v0.3.18 · Apache-2.0
:star: AI-assisted development workflow that produces understanding alongside code. Teach, capture decisions, document, assemble reviews.
v0.1.0 · MIT
Multi-agent codebase review for PRs, CI, and downstream fork syncs.
— · MIT
AI-powered development tools. 18 agents, 19 commands, 29 skills, 1 hook, 1 MCP server for code review, research, design, and workflow automation.
v0.1.0 · MIT
A prose linter that sniffs out AI writing tells. Zero dependencies, countable rules plus one judgment model.
v0.56.1 · MIT
Autonomous PR CI monitor and review-comment resolver for agentic coding tools
v0.3.0 · MIT
Show the instruction graph your coding agents actually receive.
v9.7.0 · MIT
Your AI can write the UI. This makes sure it writes your UI. A deterministic scanner scores your design system 0-100 against 112 public repos, reads React and web components (Stencil, Lit), hands you a copy-paste fix prompt for each top finding, writes ru
— · Apache-2.0
The ripgrep of AI context: a zero-dependency C++23 CLI + MCP server for coding agents. Find what you want without reading the repo, then check you built what you meant — blast radius, tests-to-run, quality deltas. Signatures at 74.7% fewer bytes than bodies; every guess labelled, every loss published. Paddle out with a map.
v1.16.0 · MIT
Quality gate for AI/Codex-generated pull requests: blocks TODO leftovers, leaked secrets, sloppy commits and red CI before they reach main.
v0.1.5462 · Apache-2.0
Soul-bound workflow roles for Pi
— · Apache-2.0
The fastest developer workflow for every AI coding agent. Live status, quick prompts, worktrees, and diff review from one tmux TUI.
v4.21.0 · MIT
Keep the state. Change the model. Shared context and a multi-model panel across Claude Code, Codex, Cursor, Antigravity, GitHub Copilot, and Muse.