What parts of Ghidra (like cross referencing, translating, interpreting text and code) can be "uplifted" and inlined into skills that run inside the LLM completion call on a large context window without doing token IO and glacially slow and frequently repeated remote procedure calls to external MCP servers?
>There's a fundamental architectural difference being missed here: MCP operates BETWEEN LLM complete calls, while skills operate DURING them. Every MCP tool call requires a full round-trip — generation stops, wait for external tool, start a new complete call with the result. N tool calls = N round-trips. Skills work differently. Once loaded into context, the LLM can iterate, recurse, compose, and run multiple agents all within a single generation. No stopping. No serialization.
>Skills can be MASSIVELY more efficient and powerful than MCP, if designed and used right. [...]
Leela MOOLLM Demo Transcript: https://github.com/SimHacker/moollm/blob/main/designs/LEELA-...
>I call this "speed of light" as opposed to "carrier pigeon". In my experiments I ran 33 game turns with 10 characters playing Fluxx — dialogue, game mechanics, emotional reactions — in a single context window and completion call. Try that with MCP and you're making hundreds of round-trips, each suffering from token quantization, noise, and cost. Skills can compose and iterate at the speed of light without any detokenization/tokenization cost and distortion, while MCP forces serialization and waiting for carrier pigeons.
speed-of-light skill: https://github.com/SimHacker/moollm/tree/main/skills/speed-o...
More: Speed of Light -vs- Carrier Pigeon (an allegory for Skills -vs- MCP):
https://github.com/SimHacker/moollm/blob/main/designs/SPEED-...