Self-hosted personal AI agent runtime that runs chats, tools, automations and long-term memory for persistent workflows. Small, readable core with a bundled WebUI, multi-chat integrations, an OpenAI-compatible API and a Python SDK for easy extension and deployment.
Provides a workflow layer for OpenAI Codex CLI to bootstrap stronger Codex sessions, add reusable agent roles/skills, and manage durable project state under .omx. Includes team runtime, canonical skills, and monitoring surfaces.
Automates decompiling APK/AAR/JAR and extracting HTTP APIs — Retrofit endpoints, OkHttp calls, hardcoded URLs, and auth patterns — so you can document and reproduce an app's network surface without source code. Integrates jadx/Vineflower/Fernflower and scripts for call-flow tracing.
Collection of small, composable agent skills that extend LLM-based agents for planning, development, and tooling — installable via npx and designed to turn higher-level tasks (PRDs, TDD, refactors, triage) into reproducible agent actions.
Runs untrusted code (LLM outputs, plugins, and third‑party tools) inside cross‑platform, policy‑driven sandboxes. Provides a unified JSON schema and a TypeScript SDK that sit on multiple containment backends (process sandboxes, LXC/Bubblewrap, microVMs). Early preview with known permissive profiles — not yet a security boundary.
Creates human-directed teams of AI agents (via GitHub Copilot) that live in your repo, persist knowledge, and coordinate development work. Key features: repo-first persistence, watch/triage automation, and an extensible CLI/SDK — alpha software, Copilot-dependent.
Rust library for fast PDF classification and position-aware text extraction that converts native-text PDFs to structured Markdown without OCR. Offers per-page OCR routing, multi-column and table detection, and Python/Node.js/WebAssembly bindings for low-latency local pipelines.
Runs automated, parallel SEO audits inside Claude Code and emits prioritized, testable action plans across technical SEO, content quality (E‑E‑A‑T), Schema.org markup, AI-search (GEO/AEO), local and e-commerce SEO. Operates with 25 sub-skills and 18 specialist agents; optional MCP extensions add live data.
A TypeScript framework for building programmable, headless autonomous agents with a harness-centric runtime. Includes an SDK and CLI, virtual sandboxes (just-bash) with optional full container sandboxes, provider-agnostic model settings, and connectors for CI/Daytona/MCP—suited for deployable agent runtimes.
Local integration layer that lets AI agents discover and securely call OpenAPI, MCP, GraphQL, or custom JavaScript functions. Centralizes a shared tool catalog, auth, and policy surface across multiple agents, with a local web UI and CLI for runtime control.
Provides a minimal web and desktop GUI for coding agents (Codex and Claude), letting you run LLM-driven code workflows through a lightweight interface. Emphasizes quick provider switching, desktop packaging, and an opinionated minimal UX; early-stage project, expect bugs.
Provides cross-platform semantic memory for AI coding agents by turning human-editable Markdown logs into a rebuildable Milvus “shadow” index and syncing memories across plugins (Claude Code, OpenClaw, OpenCode, Codex). Supports progressive retrieval, hybrid dense+BM25+RRF search, smart deduplication, live sync, and local ONNX embeddings.