Reverse-engineers live websites into production-ready Next.js codebases: an AI-driven /clone-website skill extracts design tokens, assets, and exact component specs, then dispatches parallel builder agents to reconstruct pages. Recommends Claude Code (Opus 4.7) but supports many agents.
Turns any codebase, docs, or wiki into an interactive knowledge graph for exploration, semantic search, and Q&A. Uses a Tree-sitter + multi-agent LLM pipeline to auto-generate node summaries, guided tours, and diff impact analysis; CLI and dashboard integrations.
Orchestrates parallel CLI-based AI agents in isolated git worktrees so you can run multiple coding agents side-by-side, review AI-generated diffs, and link PRs/CI to each worktree. Desktop client with a mobile companion and BYO model subscriptions.
Orchestrates LLM-powered coding agents in isolated sandboxes to automate code edits and review pipelines. Provider-agnostic (Docker, Podman, Vercel), supports branch strategies, session capture, reusable sandboxes and structured outputs.
Review-first terminal diff viewer that opens changesets in an interactive TUI with multi-file review stream, sidebar navigation, and inline AI/agent annotations. Supports split/stack responsive layouts, watch mode, and Git/Jujutsu pager integration.
Hands-on, phase-based curriculum for building end-to-end AI systems from first principles — implement algorithms, run tests, and ship reusable artifacts (prompts, skills, agents, MCP servers) across Python, TypeScript, Rust, and Julia under an MIT license.
Provides 1,000,000 model-generated chain-of-thought traces and instruction–response pairs for fine-tuning and distilled supervision. Focused splits (coding, PHD-Science, General-Math, MultilingualSTEM), ~5B tokens, Apache-2.0 license.
Orchestrates end-to-end video production with agentic pipelines that research, script, generate assets, edit, and render finished videos. Distinguishes itself by supporting true real-footage retrieval (Archive.org, NASA, Wikimedia), Remotion/HyperFrames composition, and usable zero-key workflows alongside cloud providers.
Provides a curated collection of DESIGN.md files extracted from real websites so AI coding and design agents can generate visually consistent UIs from a single markdown file. Includes previews, extracted tokens, and ready prompts for quick agent integration.
A dense 128B multimodal model with a 256k context window, configurable reasoning effort, and native function-calling for agentic workflows. Supports text+image input, multilingual output, and is released on Hugging Face under a Modified MIT license with revenue-based exceptions.
Turns a repo's code, docs, PDFs, images, and videos into a queryable multimodal knowledge graph for AI coding assistants. Uses deterministic AST extraction for code and LLM-based semantic extraction for other assets, exporting interactive HTML, JSON, and a human-readable audit report.
Generates and iterates on long‑horizon agentic plans and code — designed to stay productive across many rounds of tool calls and experiments. Emphasizes iterative reasoning, stronger repo/terminal automation and code generation than GLM‑5, and can be served locally for research and autonomous-agent workloads.