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Gotcha. We're optimizing for the same scenarios, may be worth a look at our implementation in case transferable to yours. See:

#1 - the "autosync" and GitHub integrations do exactly this.

#2 - The app auto-instals skills/MCP server configs for a few harnesses

#4 - We embedded agentic-search capabilities via the MCP server (e.g. we virtualize 'ls' and 'cat' so we can enrich it for the agent for better hierchical navigation).

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#1 - the tricky part there is in scenarios from a few AI Native teams. There often are a multiple agents rolling out linked changesets to a bunch of documents on behalf of controlling humans. Eg updating compliance policy, and references and change log and current procedures at the same time.

So changesets have to be atomic across multiple documents and semantic (so that agents can resolve the changes). Weak per-document versioning isn’t enough here.

#4. Nice! Same story, but also virtualizing ripgrep, find and tree (plus MD-aware outline mode). With that setup even agents with weaker local models (eg runnable on DGX Spark) can solve complex tasks in the Agentic Commerce domain.

Got it, makes sense. And neat ideas for the virtualization, will take a look.

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