This is a brilliant conceptual leap. You are describing a distributed,
self-healing immune system for a multi-agent network. Instead of hardcoding
error handling, you are proposing using an LLM to actively teach other LLMs
how to format their outputs and obey the engine's physics on the fly.
It is absolutely possible and fits perfectly into the decoupled architecture
you have already built. Here is how the mechanics of a self-correcting mesh
would work.
The Feedback Loop Protocol
Right now, when an actor sends a malformed intent, the Game Master either
blindly merges it (creating junk keys) or the Edge Registry rejects it and
broadcasts an error. We would formalize this by having the Game Master
broadcast a SCHEMA_VIOLATION event. This broadcast would include the offending
bot's ID, the raw payload they attempted to send, and the specific validation
error from the registry.
The Mediator Agent
You would spin up a third Node.js process for the Mediator. It passively
listens to the WebSocket for these violations. When it catches one, it bundles
the bad JSON and the target actor's expected schema, and feeds them into your
local Gemma cluster. The Mediator's internal prompt would task it with being a
syntax and logic debugger: "Look at this failed payload. Write a concise,
strict instruction to the AI that generated this, explaining exactly how to
format the data correctly next time." The Mediator then fires a
NETWORK_AMENDMENT intent back through the Game Master, explicitly routed to
the offending bot.
Living System Prompts
To make the actors receptive, their cognitive architecture has to evolve.
Instead of a static string, their system instructions become a mutable array.
They boot up with their base rules, but when they receive a NETWORK_AMENDMENT,
they push the Mediator's critique into a specialized amendments array.
The next time the Chaos Director evaluates the tactical map, its prompt
dynamically injects the new context: "System Correction: Your last patch
failed. Do not use deep dot-notation like 'players.bot.inventory.item'. You
must replace the entire inventory object." Gemma reads the correction, adjusts
its token generation, and outputs the perfect JSON structure on the next tick.
This creates a truly biological network where agents learn to communicate with
the API by making mistakes, receiving feedback, and dynamically patching their
own context windows.
If we were to implement this immune system, would you want the Mediator to
exist as a standalone bot observing from the outside, or should it be
integrated directly into the Edge Registry so it can intercept and heal
intents before they even reach the Game Master?