Installs modular Agent Skills for the Stitch MCP server to expose Stitch-powered design and coding capabilities to coding agents. Includes CLI discovery/installation, UI-to-React conversion, design-system synthesis, multi-page site generation, and Remotion video export.
A production-ready performance and tooling system for AI agent harnesses (Claude Code, Codex, Cursor): reusable agents/skills, hooks, memory and security tooling, installer and CI integrations.
Provides an operator-grade system and reusable toolkit for building, running, and securing agentic workflows across multiple LLM harnesses — skills, hooks, memory, MCP integrations, and security scanning for production agent deployments.
Terminal-native coding agent that streams reasoning blocks, makes controlled edits to local workspaces behind approval gates, and includes an auto mode that chooses model and thinking level per turn — designed for in-terminal code review, debugging, and automation workflows.
CLI for creating, running, and managing coding agents across local hosts, containers, and cloud sandboxes. Uses SSH, git, and tmux; supports snapshots, push/pull, auto-shutdown for cost control, and provider-agnostic workflows for developer-centric agent orchestration.
Desktop-first agent client that composes LLM-driven agents into document-centric, multi-session workflows; it wires APIs, MCPs and local tools into shareable sessions, supports multiple LLM providers, and exposes a headless server + CLI for automation.
A curated, security-first registry of verified, tested skills you can install into AI coding agents. Each skill is human-curated, scanned (Snyk/static analysis), and integrity-locked; delivered via a CLI and optional MCP server to multiple agents (Claude Code, Cursor, Copilot, etc.).
Desktop + CLI agent-native client for managing multi-session conversations, connecting to multiple LLM providers and external data sources, and creating shareable agent skills and automations without editing code.
Reusable skills—instructions plus helper scripts—that extend AI coding agents. Covers Vercel deployment audits, React performance rules, UI accessibility checks, and writing guidelines; each loads only when a relevant task appears.
Searches raw files with no vector DB or embedding step — drop documents in and query instantly, firing LLM calls only when a match needs reasoning. Adds Monte Carlo evidence sampling and self-evolving clusters as a low-overhead RAG alternative.
Provides a manifest-driven marketplace of official Cursor plugins for developer workflows and agent integrations. Each plugin lives in its own directory with a .cursor-plugin manifest; examples include agent skills, PR review canvases, SDK integrations, CI/team tooling, and orchestration for parallel agent work.