This article was originally published on BuildZn.
Spent weeks battling flaky AI agents that just couldn't stick to the script. Multi-step tool use was a nightmare, constantly hallucinating API calls or just flat-out ignoring the defined tools. Everyone talks about the raw power of new open LLMs, but nobody benchmarks them for reliable agentic workflows. Turns out, GLM-5.2 for open agent benchmark testing drastically changed the game.
The Agent Reliability Problem: Why Open LLMs Flop on Tool Use
Look, building multi-agent systems, especially with Node.js, means your LLM needs to be a damn good engineer. It needs to follow instructions, use specific tools at the right time, and pass valid parameters. Most open source LLMs? They're chat bots first, tool-users second.
I've pushed Mixtral 8x7B hard on FarahGPT and NexusOS. For simple, one-shot tool calls, it's decent. But throw a complex, chained task at it — "find product, check stock, then update CRM" — and it often fumbles. You'd see things like:
