Show HN: Id-agent – Token efficient UUID alternative for AI agents (github.com)

A new library called **id-agent** has been introduced as a token-efficient alternative to UUIDs for AI agents. While traditional UUIDs consume approximately 23 tokens and can lead to hallucinations in large language models (LLMs), id-agent generates human-readable word-based IDs at only around 14 tokens, with a comparable level of collision resistance. This innovative design emphasizes accessibility for both humans and LLMs by utilizing a curated list of 4096 English words, ensuring that each word represents a single BPE token, thus enhancing efficiency in data processing and memory retention. The significance of id-agent lies in its ability to reduce token usage substantially while maintaining safety in ID generation, making it particularly advantageous for developers of AI applications. The library offers configurable entropy ranging from 12 to 192 bits, accommodating various scales of applications—from quick prototypes to large-scale deployments—without compromising performance or safety. By enabling the generation of IDs that are both memorable and efficient, id-agent allows developers to optimize their workflows, reduces computational costs, and mitigates the likelihood of ID collisions, redefining how identifiers are managed in AI contexts.