Introduction

ilo is a token-optimised programming language for AI agents. Named from the Toki Pona word for “tool”, it’s designed to minimise the total token cost when AI agents write and run programs.

The problem

AI agents pay three costs per program:

1. Generation tokens - producing the code
2. Error feedback - reading error messages when something goes wrong
3. Retries - regenerating after failures

Traditional languages weren’t designed for this.

The solution

Here’s the same program in Python and ilo - a function that computes subtotal plus tax:

Python

def tot(p: float, q: float, r: float) -> float:
    s = p * q
    t = s * r
    return s + t

ilo

tot p:n q:n r:n>n;s=*p q;t=*s r;+s t

The ilo version is 0.33× the tokens and 0.22× the characters. Both are typed, both have named variables, both do the same thing.

The savings come from three things:

• Prefix notation eliminates parentheses: +*a b c instead of (a * b) + c
• Short names - single-char variables (x, n, s), short function names (dbl, fac), and builtins with compact aliases (len, hd, flt)
• Type verification catches errors before execution with compact codes (ILO-T004) - not a full stack trace
• Constrained vocabulary means fewer valid next-tokens, fewer wrong choices, fewer retries

Shell

# Run inline
ilo 'tot p:n q:n r:n>n;s=*p q;t=*s r;+s t' 10 20 30

# Run from file
ilo program.ilo tot 10 20 30