Great point! Not just binary analysis, plus even self-analysis! (See skill-snitch analyze and snitch on itself below!)

MOOLLM's Anthropic skill scanning and monitoring "skill-snitch" skill has superhuman capabilities in reviewing and reverse engineering and monitoring the behavior of untrusted Anthropic and MOOLLM skills, and is also great for debugging and optimizing skills.

It composes with the "cursor-mirror" skill, which gives you full reflective access to all of Cursor's internal chat state, behavior, tool calls, parameters, prompts, thinking, file reads and writes, etc.

That's but one example of how skills can compose, call each other, delegate from one to another, even recurse, iterate, and apply many (HUNDREDS) of skills in one llm completion call.

https://news.ycombinator.com/item?id=46878126

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...

Skills also compose. MOOLLM's cursor-mirror skill introspects Cursor's internals via a sister Python script that reads cursor's chat history and sqlite databases — tool calls, context assembly, thinking blocks, chat history. Everything, for all time, even after Cursor's chat has summarized and forgotten: it's still all there and searchable!

cursor-mirror skill: https://github.com/SimHacker/moollm/tree/main/skills/cursor-...

MOOLLM's skill-snitch skill composes with cursor-mirror for security monitoring of untrusted skills, also performance testing and optimization of trusted ones. Like Little Snitch watches your network, skill-snitch watches skill behavior — comparing declared tools and documentation against observed runtime behavior.

skill-snitch skill: https://github.com/SimHacker/moollm/tree/main/skills/skill-s...

You can even use skill-snitch like a virus scanner to review and monitor untrusted skills. I have more than 100 skills and had skill-snitch review each one including itself -- you can find them in the skill-snitch-report.md file of each skill in MOOLLM. Here is skill-snitch analyzing and reporting on itself, for example:

skill-snitch's skill-snitch-report.md: https://github.com/SimHacker/moollm/blob/main/skills/skill-s...

MOOLLM's thoughtful-commitment skill also composes with cursor-mirror to trace the reasoning behind git commits.

thoughtful-commit skill: https://github.com/SimHacker/moollm/tree/main/skills/thought...

MCP is still valuable for connecting to external systems. But for reasoning, simulation, and skills calling skills? In-context beats tool-call round-trips by orders of magnitude.

More: Speed of Light -vs- Carrier Pigeon (an allegory for Skills -vs- MCP):

https://github.com/SimHacker/moollm/blob/main/designs/SPEED-...

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