Browse plugins

Hookify creates custom hooks to prevent unwanted behaviors by analyzing conversation patterns or explicit instructions, using simple markdown configuration files with regex pattern matching. It supports four hook events (PreToolUse, PostToolUse, UserPromptSubmit, Stop) and provides commands to generate rules, list configurations, and interactively manage hook behavior without requiring restarts.

This plugin provides Git and GitHub workflow automation through 4 agents and 7 skills, handling commits, pull requests, code reviews, and comment resolution with built-in safety hooks. It integrates validation tools for commit types, visual proof requirements, and AI attribution checks directly into your development workflow.

Pro Workflow is a complete AI coding system with self-correcting memory, persistent SQLite-indexed research wikis, and an auto-research loop that learns from corrections across sessions. It provides 41 skills, 8 agents, 23 commands, and intelligent hooks that inject relevant knowledge and enforce quality gates without requiring API keys or external services.

Ars Contexta generates a personalized knowledge management system through conversational setup, creating markdown vaults with wiki links, processing pipelines, automation hooks, and domain-native documentation—all derived from how you describe your thinking and work. The plugin provides 10 skills for extracting insights, finding connections, and maintaining your vault, plus a 6-phase pipeline that mirrors Cornell note-taking with a meta-cognitive layer for continuous system evolution.

AutoHarness is a self-learning skill layer for Claude Code that automatically distills reusable skills from real work sessions, consolidates similar skills to avoid duplication, and prunes unused ones to keep the library clean. Skills are validated by actual adherence in use rather than offline benchmarks, and the system maintains a per-skill ledger of decisions and scenarios for transparency.

This plugin provides guardrails and debugging tools for research workflows, catching AI mistakes in paper reproduction and experiment tracking before they become costly. It includes citation validation, LaTeX checking, timezone handling, and evidence-first experiment comparison through shell-based guards and hooks.

Claude Octopus is a multi-LLM orchestration plugin that integrates up to ten external AI providers (Codex, Copilot, Qwen, Ollama, Perplexity, OpenRouter, OrcaRouter, OpenCode, Grok) alongside Claude for consensus-gated code review, research, and multi-model workflows. It provides 53 commands, 49 specialized agent personas, 62 reusable skills, and structured four-phase methodology (Discover→Define→Develop→Deliver) with quality gates, persistent memory integration, and autonomous pipeline execution.

Engram is a learning system that turns Claude into a Socratic tutor, verifying your understanding through free-recall challenges and scheduling review sessions using FSRS-4.5 spaced repetition. It keeps you accountable to what you actually learn—with receipts—across nine agentic platforms including Claude Code, OpenAI Codex, OpenCode, and multiple others.

dev-flow provides code review, automated fixes, commit management, and linting for development workflows through 2 agents and 6 skills integrated via hooks. It uses local tools (node, bash, python3) to run shell-based linting and code quality checks without external API dependencies.