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Awesome List
Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration.
GitHub stars and default-branch commits for ai-boost/awesome-harness-engineering.
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An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.
Secure, fast, efficient, battle-tested at Alibaba's scale. Hybrid architecture code review tool: deterministic pipelines + LLM Agent, precise line-level comments, built-in multi-language ruleset (NPE, thread-safety, XSS, SQL injection), OpenAI & Anthropic compatible.
A lightweight, powerful framework for multi-agent workflows
The batteries-included agent harness.
#1 Persistent memory for AI coding agents based on real-world benchmarks
How Python does AI. Agents, realtime voice, image generation, embeddings. Every model, every interface, typed end to end.
Multiplayer agent harness for work.
The best agent harness.
Multi-Agent Harness for Production AI
A meta-skill that designs domain-specific agent teams, defines specialized agents, and generates the skills they use.
Build an agent harness and control it end-to-end. Open-source SDK for production AI agents in Python & TypeScript - any model, any cloud.
Build distributed, production-grade, long-running agents.
Nexent is a zero-code platform for auto-generating production-grade AI agents using Harness Engineering principles — unified tools, skills, memory, and orchestration with built-in constraints, feedback loops, and control planes.
The open-source agent harness - the runtime layer that turns an LLM into a working agent.
Claw-Eval is an evaluation harness for evaluating LLM as agents. All tasks verified by humans.
Meta Harness Implementation
Continual harness optimization