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.
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Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration.
AI content workspace for Chinese creators: desktop writing, research, prompt library, knowledge base, and multi-model workflows.
An awesome list of Agent Harness engineering resources, including GitHub projects, tools, benchmarks, and practical guides.
Autonomous Agents (LLMs) research papers. Updated Daily.
Portable, vendor-agnostic agent harness for project-specific skills, workflows, and agent teams aligned with your codebase, conventions, and engineering standards.
Open-source AI agent harness in native Rust — GUI, CLI, headless, and webapp from one binary. Multi-provider, MCP, skills, plugins, agent teams.
The Agent Harness for AI-Human Collaboration, inspired by the AI-DLC (AI-Driven Development Lifecycle)
Open-source workspace where your agents and team share one memory. Any runtime, your infra — self-host in one command, no per-agent fees.
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Deterministic safety solutions for probabilistic AI agents
AI-native agent harness for coding workflows by python: multi-model LLM orchestration, stateful sessions, tool governance, traceable delivery, and provider routing for GPT, Claude, DeepSeek, Qwen, Kimi, GLM, and MiniMax.
Self-hosted Personal AI + agent runtime in .NET (NativeAOT-friendly)