Smart idea but the concern can be that in the future, tokenization techniques and libraries may change. And also this looks like a very edge optimization to me. But overall, it deserve to exist. Good job.

i would be afraid of accidental prompt injection

any plans for a python port?

Is this just a reinvented humanhash?

Benchmark comparing conventional UUID and AID across models, hallucination rate, token usage, would be cool!

Nice package, not only is using words more token-efficient [saving time and money], but weaker models are also less likely to make mistakes when providing the key, at least in my tests.

That said, for `createAliasMap`, don't you think you could create a deterministic mapping from and to UUIDs <-> word chains? That way, no additional state would be needed. [Might require fairly long word chains...]

An even better solution is to present the AI with local IDs and map those to UUIDs outside of its context. So when giving a list of items for the LLM to choose from, just list them with incremental numbers (1, 2, 3...) and ask for these numbers in tool schemas.

Hello HN,

I have built id-agent to solve the 3 major pain points with using UUIDs with LLMs:

1. Increased token usage 2. Incorrect ids in the output tokens because of hallucination 3. Poor readability when debugging prompts and traces

While building agent-qa, I encountered challenges with ids, since each test, suite, and run artifact has a UUID associated with it. The AI agents often made mistakes and referenced incorrect entities. With id-agent, I was able to achieve a token-efficient way of defining unique ids which can be easily differentiated. The prefixed id path drastically reduces the hallucination rate.

Do check out agent-qa: Open-source Agentic QA Harness with Memory https://vostride.com/

Why do people choose the hyphen ("-") as the separator in an identifier? When double-clicking, the ID does not select completely, unlike when an underscore ("_") is used.

I don't like that they're not apples to apples; less bits so of course it'll take less tokens.

> Where UUIDs cost ~23 tokens and get hallucinated by LLMs

How does this solve the hallucination problem?

Just removing the - from the example UUID takes it from 26 tokens to 18