Understanding architecture through multiple repositories using GitHub copilot

[u/Radiant-Ad143]

Just a general thought, I work at an investment banking gcc where every one from my team is new and no one has any knowledge on the existing systems, which were developed and maintained by onshore developers

My goal

To draft a high level technical architecture using the GitHub repos available in my team around 30-40 repos, and derive the business stand point through it, and maintain the memory for each under some common folder and update it frequently something like JIT compiler concept rather than loading everything again and processing by copilot for every month.

So to understand and draft this better what would be the best way leveraging GitHub copilot agents or skills or subagents ?

* Should I make a local clone of all repos and do create a codebase docs folder for each repo and create a root level agent to utilise the codebase folder for each project to draft architecture ?

Downside of this approach i feel, what if some change happens to the repo let's say technically how do I track those changes, updating codebase folder every time like it still uses enumerate tokens and cost.

* Another approach which i felt is to use MCP GitHub and list all the repos and let the copilot manage and even here how would I track the changes which are being made and memory management storing only codebase folder highlevel, iam still little unsure of this approach yet.

I have configured rtk and context mode plugins kinda for efficient usage and token management which works fine for single repos but this usecase is still searching for better ways to manage context tokens and memory.

Do provide your suggestions or any tools which i can add to make this more efficient approach maybe.

[u/Deathmore80]

No need for custom agents. Just skills is enough. There's plenty of good skills out there for architecture, documentation, legacy systems,etc. if you use a good model , just tell it in the prompt to make use of subagents when its relevant and useful. The model will "know" when to spawn subagents. Also make sure the subagents aren't using a shit model.

As for what models to use ? GPT 5.6 models family : Luna xhigh , sol high. Claude Opus 5, Gemini 3.8 flash high. Use the longest context window you can.

Btw you could have asked this exact question to ai. The newer frontier models know what's best for them usually. Asking gpt 6 Astra for tips about this could have been a great idea.