Provides hierarchical, versioned semantic memory for AI agents with Git-like branching, commits, and rollbacks—using semantic paths and cryptographic provenance instead of opaque vector stores. Designed for branch-aware, auditable memory in multi-agent and production workflows.
Extensible AI coding-agent toolkit offering a terminal-first coding agent CLI, a unified multi-provider LLM API, TUI and web UI libraries, Slack integration, and vLLM pod support—built to prototype and run agent-driven developer workflows.
A TypeScript agent harness split into composable npm packages: a unified LLM API across OpenAI, Anthropic and Google, an agent runtime with tool calling and state, a self-extensible coding-agent CLI, and a differential-rendering terminal UI library.
Framework for building multi-modal AI agents that watch, listen, and reason over live video, pairing vision models (YOLO, Roboflow, Moondream) with LLMs like Gemini and OpenAI. Agents join calls in ~500ms and keep audio/video latency under 30ms.
Write repository automation as natural-language markdown that compiles into deterministic GitHub Actions workflows running AI agents. Agents run read-only by default and write only via sanitized safe-outputs. Works with Copilot, Claude, Codex, or Gemini.
Bridges MCP-capable AI agents (Claude, Copilot, Cursor) to 150+ offensive-security tools, letting them autonomously run pentests, vulnerability scans, and bug-bounty workflows. A decision engine picks the right tools and adapts as findings emerge.
Wraps the OpenCode CLI with a plan-first workflow: agents propose a plan you approve before any code is written, and a ContextScout step loads your repo's existing patterns so output matches house style, not generic boilerplate.
Defines a predictable repository-level instruction file for coding agents, giving teams one place to document workflow rules instead of each tool inventing its own context format.
Makes the spec an executable artifact: you write intent in structured markdown and AI agents generate the plan, task breakdown, and code from it. A specify CLI and slash commands drive a constitution-plan-tasks-implement workflow across 30+ coding agents.
Wraps Claude Code in a loop that re-runs it until a task is done, gating every exit behind two conditions — semantic completion plus an explicit EXIT_SIGNAL — so it never stops early. Adds rate limiting and a circuit breaker for unattended, headless runs.
Composes AI agent teams from a Ghost+Shell+Model formula: each Bot pairs a prompt/MCP/Skills Ghost with a Chat, ClaudeCode, or Dify shell and a model like Claude or DeepSeek. Bots form Teams that run as traceable Tasks, wired to GitHub and DingTalk.
Converts your goals and context into verifiable agent workflows that hill-climb your Current State → Ideal State across life and work. Bundles an ISA-based criteria system, persistent memory and a Pulse dashboard into a single AI-native skill designed to run inside an AI coding harness.