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.
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.
Researches the last 30 days of public discussion across Reddit, X, Bluesky, YouTube, TikTok, Instagram, HN and Polymarket, then synthesizes a citation-rich briefing and copy-paste prompts. Multi-source scoring, comparative mode, and optional watchlist; requires API/auth for some sources.
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.
Runs background coding agents in isolated sandboxes to autonomously handle development tasks, create pull requests, and integrate with Slack, GitHub, Linear and webhooks. Supports multiplayer sessions, multiple LLM providers, fast startup via snapshots and prebuilt images; designed for single-tenant deployments.
Models an AI agent's context as a file system, unifying memory, resources, and skills instead of flat vector RAG. Uses L0/L1/L2 tiered loading to cut tokens, directory-recursive plus semantic retrieval, and visualized retrieval traces for debugging.