— · no license
Ed's repo of Claude Code plugins, centered around a research-plan-implement workflow. Only a tiny bit cursed. If you're lucky.
v0.3.2 · MIT
Claude Code plugin that transforms vague requirements into detailed implementation plans via research, interviews, and multi-LLM review.
— · MIT
AI-powered development tools. 18 agents, 19 commands, 29 skills, 1 hook, 1 MCP server for code review, research, design, and workflow automation.
v3.13.1 · MIT
Claude-Code-style dynamic workflows for Pi — fan a task out across 100s of subagents with real model routing, token/cost accounting, resume, git-worktree isolation, an interactive /workflows TUI, and a real /deep-research.
v2.9.7 · MIT
A Claude Code plugin that gives Claude persistent memory across sessions — stores lessons and decisions as markdown in your Obsidian vault, searches them with SQLite FTS5, and mines past transcripts automatically.
v0.1.0 · MIT
Claude Code plugin that stops Claude writing like an AI. 29 researched patterns, loaded every session and checked on every file write.
v5.1.0 · MIT
Automates mountain route research for North American peaks. Aggregates data from 10+ mountaineering sources to generate detailed route beta reports with weather, avalanche conditions, and trip reports.
— · MIT
Claude Code plugin for building LLM-maintained Obsidian wikis from raw research — compile, query, lint, and evolve your personal knowledge base. Inspired by Karpathy's knowledge base workflow.
— · MIT
A theoretical reconstruction of the Claude Mythos architecture, built from first principles using the available research literature.
v1.2.0 · MIT
ERPAVal — autonomous software development. Six-phase Explore/Research/Plan/Act/Validate/Compound workflow with classifier-driven routing and a compounding lessons store.
— · MIT
Autonomous session memory for Claude Code. Never lose context, never repeat yourself. AI-powered summaries, searchable history, and automatic context injection. 📦 npm install -g memctx
— · Apache-2.0
Cross-platform toolkit to enhance Claude Code with multi-LLM consensus, 8 specialist agents, semantic knowledge search, and one-command install.