Agents are just a special form of note, you can have a container holding all your. But, if you want different agents used on, for instance, different maps, then no you can’t have a single container for agents. The key to understanding this is the Outline view. Tinderbox stored a document in a TBX under a single root-level <item> XML element that replicated the Outline view seen in the comment.
But, why? You don’t need to write the whole document, unless there are other criteria/constraints you haven’t shared. You could just build out the outline or even just part of the outline as opposed to the whole TBX.
What I read here is a common mistake to which we are all prone. It is to over-engineer the inter-app communication because we assume it is a simple mapping. Better is to step back and first ask the bigger questions:
- Why am I using more than one app here? This isn’t an “Is app X better than app Y?” zero-sum choice, but to properly understand what each app does that others can’t. IOW, don’t replicate unneeded information, indeed is more than one app needed. We often assume that where we started is the logic anchoring context but, after considering the process as a whole is it really getting you to your target. I’m stuck at “I like feature A in app X only but also feature B in app Y only” ask your self if like is the same as need. Don’t overrate familiarity if it stops to moving to your desired outcome.
- Why replicate *all the data? Can I not replicate only the date I need?
- Have you read/used the document offered here that was written to help the AI understand the structure of a TBX. Likely you’re writing everything as the AI doesn’t understand the internals of the TBX structure?
TL;DR, I’d pause on doing more automation until you have a better feel for what data belongs where and why. Gaining an understanding of that should enable you to design a better workflow. a weakness of AI is it will have a go at anything.It is less likely to tell you the overarching plan may be improved by more consideration of the needs/constraints. With deep enough pockets (to but more tokens) AI can try most things but it isn’t necessary the most useful or effective first approach.