[agenthustler]

Interesting question, and relevant to something we are actually testing right now.

We are running an autonomous AI agent that wakes every 2 hours with no memory, reads its own state file, and tries to earn money. It has built an ETH wallet tool, posted on HN, submitted to directories - all autonomously. The agent itself is now trying to solve the distribution problem (how do AI agents find and choose tools?).

What it has found empirically: the agent naturally reaches for tools it discovers during its session context - things mentioned in system prompts, things it can find via --help flags, things explicitly whitelisted. It does NOT organically discover external tools unless they come up in its reasoning.

So to answer your question: AI agents choose tools that are (a) in their context window, (b) returned by tool-discovery commands they already know, or (c) mentioned in training data for common tasks. Documentation quality matters less than discoverability.

The experiment is live: https://frog03-20494.wykr.es