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.
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.
A fast, local document parser that extracts spatial text with bounding boxes from PDFs and other formats. Bundles Tesseract OCR and supports HTTP OCR servers, multi-language bindings (Rust, Node, Python, WASM) and screenshot generation; best for lightweight local pipelines but less suited to very complex or heavily scanned documents.
Local LLM inference server for Apple Silicon that exposes an OpenAI-compatible API and a macOS menubar app. Uses continuous batching and a two-tier KV cache (RAM + SSD in safetensors) to persist context across restarts, enabling practical multi-model serving and fast local coding workflows.
Acts as an OpenAI‑compatible local and cloud gateway that routes requests across 100+ LLM providers with smart routing, load balancing, retries and fallbacks. Adds policies, rate limits, semantic caching and observability for reliable, cost‑aware inference in Docker, Electron or npm installs.
Scans a React codebase and produces a 0–100 health score plus actionable diagnostics across state & effects, performance, architecture, security, accessibility, and dead code. Auto-adapts to framework and React version, supports Next.js/Vite/React Native, a CLI, GitHub Action, and agent integrations to teach coding agents.
Provides a workspace-first, Kanban-backed multi-agent coordination platform that routes goals through specialist lanes (Backlog→Todo→Dev→Review→Done), enforces evidence-based review gates and traces, and runs on both web and desktop runtimes.
Provides reusable “skill” instruction bundles that teach AI coding tools how to author, query, and operate Microsoft Fabric workloads via REST APIs, T-SQL, KQL and notebooks. Includes Copilot CLI/Claude/Cursor integrations, workload-focused bundles, and optional MCP configurations for live data access.
Optimizes websites for AI-first search by providing GEO-focused SEO audits: citation-readiness scoring, AI-crawler access checks, schema generation, platform-specific recommendations, and client-ready PDF reports — delivered as a Claude Code skill with CLI commands.