What's the optimal way for master and children agents to communicate between them? Should I try to have short or long queries to the children agents? Should my children agents answer in markdown (useful for debugging) or structured JSON format (I had issues with this approach)?
I'd say it doesn't matter too much
In case we don't have a JSON structure answer approach, is there any benefit in telling the master agent how its children agents will answer?
It really depends on the use case - it can be interesting. But I would be careful of not complexifying the instructions of the master agent too much
Is the mater agent able to aggregate the knowledge from the successive call to children agents and draw a conclusion? Is that too much to ask of it? Should I maybe have other agents that draw business knowledge conclusions from my search agents and my master agent only becomes an orchestrator between all the agents.
If I am not mistaking, the full convo is given as context to the meta agent (incl. documents retrieved) - but I'd need to retest it to be 100% sure
Is it better to give a lot of details about how to solve problems to my agents or is it better to be synthetic as to not restrict them too much in their approach of the problem?
As a rule of thumb, I usually start high level (give role, high level context, objective and tools it has access to). I then iterate on the instruction to make it work specifically for my use case. i.e: make it as high level as you can with the agent still capable of doing what it's supposed to
