The Problem: > Traditional formats like JSON and YAML carry a high "Syntax Tax". In a human-to-machine world, braces and quotes are fine. In a token-based economy, they are expensive overhead. Furthermore, implicit typing leads to "Type Hallucinations" (e.g., a model parsing "NO" as a boolean).

The Solution: > SONA uses "Symbol-Locked Safety." Every value’s type is declared by its first character (# for ints, $ for floats, ? for booleans). This makes parsing unambiguous for the LLM and the parser.

Key Technical Specs:

Token Efficiency: Up to 40% reduction compared to JSON (matches TOON in v1.1).

Performance: Designed for single-pass parsing (Rust implementation included).

Ecosystem: We already have Python/Rust/WASM implementations and a VS Code LSP.

I'm looking for feedback on the specification (SPEC.md) and the symbol-locking approach. Is the trade-off of learning a new syntax worth the token savings in production-scale AI agents?

Repo: https://github.com/fabiosleal/sona-structured-object-notatio...