Gives the pi terminal AI agent an autonomous experiment loop: propose code changes, run benchmarks, record metrics, auto-commit improvements and revert regressions. Ships a live widget/dashboard, MAD-based confidence scoring, hooks and backpressure checks — made for iterating on speed, bundle size, training loss and build times inside a terminal workflow.
Framework for running agents inside real applications — it exposes shared actions, SQL-backed state, tools, skills, jobs and UI surfaces so agents can act on app state instead of just chatting. Backend-agnostic TypeScript stack with cloneable app templates and visual planning/recap features.
Turns any codebase, documentation, or knowledge base into an interactive knowledge graph you can explore, search, and ask questions about. Produces node-level summaries, guided tours, and diff impact analysis, and plugs into multiple LLM platforms (Claude Code, Codex, Copilot, Gemini CLI) for query-driven exploration.
Exposes a ChatGPT account as an OpenAI-compatible local API and SDK set, enabling chat, streaming, and image-generation calls via a dev proxy or "Sign in with ChatGPT". Includes a CLI and TypeScript/React adapters; unofficial and uses user ChatGPT credentials.
Turns a single research idea into runnable experiments and a conference-ready paper by orchestrating an LLM-driven end-to-end workflow (literature → design → code → sandboxed runs → analysis → writing). Provides human-in-the-loop checkpoints, domain-specialist executors, and multi-layer citation verification.
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.
A distilled 26M-parameter encoder–decoder LLM for on-device function-calling and tool use. Uses a pure-attention Simple Attention Network, provides open weights and local finetuning, and targets high-throughput inference on the Cactus runtime.
Provides modular “skills” that help designers and engineers audit, find, and improve UI animations and interaction decisions — optimized for use by AI agents or human-in-the-loop workflows. Distills domain-expert rules into actionable SKILL.md modules (review, improve, find opportunities, vocabulary).
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.