A reusable skill for trace clustering and root-cause analysis

you can see here in this case, we have 114 traces, and we're using those traces to then do the cluster analysis. How do we run the analysis? Well, this is actually a skill that we built. Basically, the skill it's going to instruct the coding agent properly to go in the go in the JSON file, look at all the traces, uh run some clustering, um then we do an adversarial review of that. So, basically, um once we have all the clusters, we do also a little bit of root cause analysis because, of course, our coding agent has access to the actual code of the AI agent, so it can do some root cause analysis. It can try to understand what happened, uh especially because it has also access to the details of every trace. So, it can go within the trace, understand why the agent answered that way, you know, trace it down to the root cause. Um and then what's going to do is going to um propose possible improvements. And what we get at the end of this process is a full markdown report, which is very helpful for us. Uh it's going to give us like the positive feedback, the negative feedback, the negative rate, you know, we are just trying to collect as many data as possible. And so, we get this very complete um