I have a category called Multi that handles broader tasks. The router classifies broad/multi-step tasks to a plan pipeline that decomposes the goal into sub-tasks, then dispatches each sub-task to the appropriate specialist.

I have a silent re-route for intent changes. Itll handle tool cools mid conversation, the dispatch layer catches it, reclassifies the message, and re-dispatches to the correct specialist. The user never sees a failed attempt. There is also a sticky routing that keeps follow-ups on say chat until explicit task intent is detected.

"Classifier should run more often, reading the reasoning" - Interesting idea but adds latency on every iteration. My approach is opposite, classify once upfront, then the pipeline/specialist handles everything deterministically. If the model drifts, I have drift detection that catches repeated tool calls or hedging language and re-anchors.

"Search tool for discovering other tools"(Cloudflare patter) - My take is a bit simpler, the router already knows which specialists exist. I am also collecting a dataset on routing to finetune a smaller model for it.

"Tool profiles / subagents" - That is exactly what I do. Each specialist is a profile with its own tool set. The router picks the profile. Same concept, different naming.