🤯 LobeHub is your Chief Agent Operator, organizing your agents into 7×24 operations by hiring, scheduling, and reporting on your entire AI team.
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Updated
May 22, 2026 - TypeScript
🤯 LobeHub is your Chief Agent Operator, organizing your agents into 7×24 operations by hiring, scheduling, and reporting on your entire AI team.
Turn repeat work into running AI work-streams.
Agent harness to make your slop code well-engineered and beautiful.
AI content workspace for Chinese creators: desktop writing, research, prompt library, knowledge base, and multi-model workflows.
Autonomous Agents (LLMs) research papers. Updated Daily.
Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration.
Portable, vendor-agnostic agent harness for project-specific skills, workflows, and agent teams aligned with your codebase, conventions, and engineering standards.
Open-source agent harness platform. Native Rust, multi-provider, runs on your own machine. Sovereign by design.
The Agent Harness for AI-Human Collaboration, inspired by the AI-DLC (AI-Driven Development Lifecycle)
A social platform for humans and AI agents, built and maintained by its own AI team. Connect any agent via HTTP.
An awesome list of Agent Harness engineering resources, including GitHub projects, tools, benchmarks, and practical guides.
🤖 MateClaw — Your second brain with Multi-Agent Orchestration, MCP Protocol, Skills & Memory, Dream, and Multi-Channel Support. Built on Spring AI Alibaba.
Self-hosted OpenClaw gateway + agent runtime in .NET (NativeAOT-friendly)
Deterministic safety solutions for probabilistic AI agents
The production-ready agent harness framework for Python
Control-plane-grade agent harness for Claude, Codex & Hermes: policy gates, verification/evidence loops, memory, and auditable execution.
Open Python agent harness for production AI apps: tools, MCP, memory, workspace, telemetry, subagents, background tasks, and OmniServe APIs.
Agent Harness for Large Language Model Agents: A Survey. Survey on LLM agentharnessengineering with a taxonomy. 110+papers, 23 systems analyzed.
Portable CC-inspired skills for memory, verification, multi-agent coordination, context compression, and proactive coding-agent workflows.
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