A collection of agent plugins for improving productivity, automating workflows, and making AI coding agents work better together.

The agentic workspace where people and agents work together in the loop.

🪨 why use many token when few token do trick — Claude Code skill that cuts 65% of tokens by talking like caveman

lnwjud — local AI-agent runtime & MCP gateway

Helping the Agents Compose the Things

File-based message queue for local agent-to-agent communication (Maildir-style)

🤖🤮 Hate the yuck codes that agents generated? Try `alint`, a ESLint like toolchain for intent driven code check, freeze your skills, AGENTS.md to lint rules

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

⚡️ 10x - Up to 20x faster AI coding with multi-step Superpowers. Open-source agent with smart model routing, BYOK, fully self-hosted.

An agent skill focused entirely on Swift Testing, helping you write better tests, migrate from XCTest, improve test architecture, and adopt modern Swift testing patterns with confidence.

Codebase intelligence for AI. Detects patterns & conventions + remembers decisions across sessions. MCP server for any IDE. Offline CLI.

Semantic codebase indexing and search for OpenCode, Claude, Codex, Pi, Jcode, and MCP hosts. Powered by Rust and tree-sitter.

Privacy Code Scanner and Dataflow Context Engine for AI coding agents

Multi-agent system for software development

Real-time architectural sensor that helps AI agents close the feedback loop, enabling recursive self-improvement of code quality. Pure Rust.

AI agent security scanner. Detect vulnerabilities in agent configurations, MCP servers, and tool permissions. Available as CLI, GitHub Action, ECC plugin, and GitHub App integration. 🛡️

OpenSwarm — Autonomous AI dev team orchestrator powered by Claude Code CLI. Discord control, Linear integration, cognitive memory.

Finds the claims in your CLAUDE.md / AGENTS.md / skills that your code no longer supports. Zero-config, no API key.

Save 40%+ on agent token costs with code graphs: call graphs, dependency graphs, dead code detection, and blast radius analysis.

Semantic Intelligence for Large-Scale Engineering. Context+ is an MCP server designed for developers who demand 99% accuracy. By combining RAG, Tree-sitter AST, Spectral Clustering, and Obsidian-style linking, Context+ turns a massive codebase into a searchable, hierarchical feature graph.

AI-powered multi-agent code review. Simulates a customizable team of Engineers performing code review with built-in discourse.

humanizer, but for code — an agent skill that removes AI-generated code slop: duplicated helpers, try-import fallbacks, broad excepts, speculative abstractions. Test-gated, behavior-preserving.

CLI proxy that reduces LLM token consumption by 60-90% on common dev commands. Single Rust binary, zero dependencies

A collection of 265 rules across 26 categories that AI coding agents can use to write idiomatic, fast, and safe Rust.