Automate long-running AI tasks with layered memory and external validation.
npx skills add https://github.com/thu-nmrc/OpenHarness --skill harness-24h
Please help me install this Agent Skill. Skill: harness-24h Source: https://github.com/thu-nmrc/OpenHarness/tree/main Command: npx skills add https://github.com/thu-nmrc/OpenHarness --skill harness-24h
OpenHarness provides a production-grade framework for long-running, autonomous AI agents that operate without constant human input by enforcing mechanical constraints, structured memory, and external validation.
Describe your task idea and the agent will automatically initialize the workspace, fill all templates, set up cron scheduling, and begin execution.
High-intent search queries and answers about installing and using this skill.
You can automate long-running AI tasks using a three-layer memory architecture with a compact L1 pointer index, on-demand L2 knowledge files, and an append-only L3 execution log to maintain persistent state across sessions and days.
The best way to verify autonomous task completion is using an external validation loop with a dedicated evaluation script, ensuring that task fulfillment is objectively and mechanically verified without requiring constant human oversight.
Yes, you can coordinate multiple autonomous agents for parallel execution using file-system IPC, allowing divisible workloads to be distributed and executed concurrently across multiple agents.
Memory consolidation works through entropy control scripts and a dream-mode mechanism that performs memory hygiene, cleaning up and consolidating persistent state logs to prevent unbounded growth during continuous 24/7 operation.
No, you do not need to manually configure cron scheduling; the framework automatically initializes the workspace, fills configuration templates, and sets up cron scheduling based on your task description.
The primary limitation of multi-agent autonomous tasks using file-system IPC is that workloads must be cleanly divisible to benefit from parallel execution, as coordination relies entirely on file-system state rather than real-time network communication.
xlelibertySchedule iterative code execution and evaluation tasks for recurring research experiments.
nshaikhsCoordinate user data across identity, content, knowledge, network, and operations modules.
delorenjEstablish a framework for autonomous AI agent teams with discovery, triage, execution, and feedback loops.
samvanmePersist agent memory across sessions with layered memory and temporal knowledge graphs.
