— · MIT
ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.
v0.26.0 · MIT
A toolkit for frontier forecasting.
— · no license
Enables discovery, retrieval, summarization, comparison, methodology and limitation analysis, research gap identification, and local management of academic papers via arXiv and Gemini AI.
v1.0.2 · MIT
Research-first design skill for AI agents. 150K+ real app screens and flows via Refero MCP.
v0.3.5 · Apache-2.0
88 installable open-source Agent Skills for research, social intelligence, marketing, and business workflows—compatible with Codex, Claude Code, Cursor, Gemini CLI, and DeepSeek Harness.
— · Apache-2.0
88 installable open-source Agent Skills for research, social intelligence, marketing, and business workflows—compatible with Codex, Claude Code, Cursor, Gemini CLI, and DeepSeek Harness.
v2026.04.26.2 · MIT
Open-source deep research for AI agents: 40 channels, 10+ Chinese sources.
— · MIT
Local NotebookLM for Claude Code via Google Antigravity (agy / Gemini 3.x): /agy:notebook turns a folder of documents into per-doc summaries + a relevance index + a cited synthesis + Q&A. Plus audio/video transcription, deep web research with citations & branded HTML reports. 13 commands, no Node runtime.
v1.7.1 · MIT
Research that compiles.
— · no license
368 AI skills, 76 expert agents, and 859 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, and research. Installs on Claude Code, Cursor, Codex, Gemini, Copilot, and 6 other AI assistants.
— · MIT
Open-source marketing skills for founders. Keyword research, growth strategy, social search audit, competitor analysis. Install with npx skills.
v0.25.1 · MIT
Claude Code plugin: run the Antigravity CLI (Gemini) as a collaborating sub-agent with intelligent model routing across the SDLC. Community project; not affiliated with Google/Anthropic.
v0.5.0 · MIT
Pre-build reality check for AI coding agents. Scans GitHub, HN, npm, PyPI, Product Hunt. MCP server. 290+ stars.
— · no license
Feed your agent papers and half-formed ideas — it links them into a system design you can defend. Markdown keeps the record; a visual canvas makes it readable. An Agent Skill for Claude Code & any SKILL.md-compatible agent.
v2.9.2 · Apache-2.0
Search ClinicalTrials.gov trials, retrieve study details and results, and match patients to eligible trials via MCP. STDIO or Streamable HTTP.
v0.4.0 · MIT
Open-source quantum Agent workspace with a desktop client, Web UI, messaging, Qiskit/MCP tools, and scientific validation
v0.4.3 · MIT
Hire Google's Antigravity CLI (agy) as a fast Gemini staffer for Claude Code and OpenAI Codex.
v2.2.0 · no license
台灣法律 MCP 伺服器 + CLI(免費、免註冊、免 API key):2,250 萬筆裁判書、行政函釋、憲法法庭裁判,附引用查核。Free Taiwan legal MCP server for Claude/ChatGPT/Codex — bring your own LLM, retrieval-only.
— · MIT
A market-driven Product Manager copilot (Agent Skills + Claude Code plugin) based on the Pragmatic Framework — guides PMs from idea to launch and produces a client-ready artifact (Markdown or .docx) at every stage.
v1.0.0 · MIT
Autonomous knowledge base plugin for Claude Code - captures reserch, ideas, and decisions into an interlinked wiki with reserch-on-miss, semantic search, and a Wikipedia-style web UI. Knowledge compounds as you work.
— · MIT
Connect Cursor, Copilot & Claude AI directly to Cheat Engine via MCP. Automate reverse engineering, pointer scanning, and memory analysis using natural language.
— · MIT
A collection of servers which are deliberately vulnerable to learn Pentesting MCP Servers.
v9.66.1 · MIT
Run multiple AI models against the same research, design, or coding task. Surface disagreements before you ship.
— · MIT
Claude Code plugin for Elixir/Phoenix/LiveView — 26 specialist agents, Iron Laws enforcement, and Tidewave MCP integration. Plan features with parallel research agents, execute with automatic verification, review with 4-agent parallel audits, and capture learnings as reusable knowledge.