Agent harnesses are the runtime scaffolding around AI agents. They usually combine context delivery, tool interfaces, planning state, memory, sandboxes, permissions, evaluation, and observability so agents can complete longer tasks reliably. Agent harnesses are especially common in coding agents, research agents, and multi-agent workflows where repeatability, safety, and traceability matter.
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Agent harness to make your slop code well-engineered and beautiful.
Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration.
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Autonomous Agents (LLMs) research papers. Updated Daily.
An awesome list of Agent Harness engineering resources, including GitHub projects, tools, benchmarks, and practical guides.
Open-source AI agent harness in native Rust — GUI, CLI, headless, and webapp from one binary. Multi-provider, MCP, skills, plugins, agent teams.
Portable, vendor-agnostic agent harness for project-specific skills, workflows, and agent teams aligned with your codebase, conventions, and engineering standards.
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.
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Deterministic safety solutions for probabilistic AI agents
Self-hosted OpenClaw gateway + agent runtime in .NET (NativeAOT-friendly)
Veldra — talk an agent into existence, then watch it grow. A self-hostable, local-first agent platform: describe what you need in plain language and it compiles a working agent tools, MCP, RAG, teams. The more you use it, the better it gets agents learn from your feedback and reshape as you talk.
Mantis Hack
The production-ready agent harness framework for Python