Discover the Best AI Resources
Curated essentials, no noise — just what matters
Provides ultra-fast, typo-tolerant file search and grep tuned for Neovim and AI agents, with built-in memory (frecency, git status, size, definition matches). It reduces agent token use and speeds developer file discovery in large repos.
Indexes any repo into a knowledge graph of dependencies, call chains, and execution flows, then feeds it to AI coding agents via MCP so they stop missing context. Ships as a CLI plus a zero-install browser graph explorer with chat.
A 20B-parameter MMDiT diffusion model that generates and edits images with accurate embedded text, including dense Chinese and English typography. Handles complex multi-line layouts and identity-preserving edits while keeping text legible.
An MCP (Model Context Protocol) server that lets AI assistants interact with Xiaohongshu (RedNote): check login, publish image/text or video posts, search and fetch feed/details, and manage comments — exposes HTTP+MCP endpoints and integrates with MCP clients via local Docker or browser automation.
Evaluates and optimizes AI agents and language models in containerized environments, supporting large-scale parallel benchmarks and RL rollouts. Integrates with third‑party providers for thousands of parallel environments and serves as the official harness for Terminal‑Bench.
Reviews each pull request for security issues: Claude reads the diff and flags vulnerabilities like injection, auth flaws, and hardcoded secrets as inline comments, with built-in false-positive filtering. Ships as a GitHub Action or slash command.
Helps developers connect IDEs and AI agents to the Figma MCP server to extract design context, generate code from frames, and write updates back to Figma. Includes client setup (VS Code, Cursor, Claude Code, Gemini CLI), tools and skills, best practices, and beta rate-limit notes.
Adds a lightweight, spec-driven workflow so AI coding assistants agree on requirements before code is produced — creates per-change artifacts (proposal, specs, design, tasks), exposes CLI slash-commands, and integrates with 20+ tools for repeatable AI-driven development.
Deploys autonomous AI agents that dynamically attack running apps and return validated proof-of-concept exploits instead of static-analysis noise. Specialized agents cover IDOR, injection, SSRF, XSS, and auth flaws, with HTTP proxy and CI/CD hooks.
Seven-week course that builds a production RAG system from scratch — an arXiv paper assistant that starts with BM25 keyword search, then layers hybrid vector retrieval, local-LLM generation, Langfuse monitoring, and an agentic LangGraph Telegram bot.
Wraps 20+ AI coding CLIs — Claude Code, Codex, Gemini CLI, Cursor Agent — in one cross-platform desktop app so agents run file, document, and data tasks without a terminal. Adds parallel multi-agent runs and cron-scheduled jobs for unattended work.
Deep research agent for complex, long-horizon research and prediction tasks. Pairs a 256K context window with up to 300 tool calls per query for web search, extraction, and code execution. Ships as open 30B and 235B models scoring 82.7% on GAIA.