ISON
Data format that uses 30-70% fewer tokens than JSON for LLMs
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ISON (Interchange Simple Object Notation) - a data format optimized for LLMs and Agentic AI.The problem: JSON wastes tokens. Curly braces, quotes, colons, commas - all eat into your context window.ISON uses tabular patterns that LLMs already understand from training data:JSON (87 tokens): { "users": [ {"id": 1, "name": "Alice", "email": "[email protected]"}, {"id": 2, "name": "Bob", "email": "[email protected]"} ] }ISON (34 tokens): table.users id:int name:string email 1 Alice [email protected] 2 Bob [email protected]: - 30-70% token reduction - Type annotations - References between tables - Schema validation (ISONantic) - Streaming format (ISONL)Implementations: Python, JavaScript, TypeScript, Rust, C++ 9 packages, 171+ tests passingpip install ison-py # Parser pip install isonantic # Validation & schemasnpm install ison-parser # JavaScript npm install ison-ts # TypeScript with full types npm install isonantic-ts # Validation & schemas[dependencies] ison-rs = "1.0" isonantic-rs = "1.0" # Validation & schemasLooking for feedback on the format design.
HN · launched Dec 26, 2025 · 7 upvotes (top 64%) · 0 views
Niche: llm optimization tools · 127 launches, 9 in the last 7 days ▲ +50% · Explore this niche →
Category and tags
- Horizontal
- Data infrastructure
- Developer
- AI feature
- Hobby / open-source project
Visit website ↗ Source listing ↗
More like this: all 127 launches in llm optimization tools →
Could you build this?
Yes ISON is a text-based serialization format designed to encode JSON-like structures into a compact tabular text syntax, which can be implemented with a basic parser and serializer.
Discussion
14 comments analyzed.
Competitors mentioned: JSON, CSV, msgpack, JSON-COMPACT, TOON
Concerns raised: Loss of nesting and semantic structure compared to JSON, Alternative formats lack training data prevalence - LLMs must translate back to JSON, Token savings offset by translation overhead and confusion, Irrelevant optimization since tokens are getting cheaper, Unclear LLM accuracy benefits over established formats
Feature requests: Publish formal benchmark results comparing formats, Support for syntax highlighting in code fences (ison language tag)
Competitors
Other products that read as similar to this one : 98 launches clear the similarity bar, closest 8 shown.
Attention rank: #47 of 99 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 55 days after the earliest competitor.
- A text format for UI wireframes · hn · 2026-02-05 · 5 upvotes · similarity 0.48
- A new benchmark for testing LLMs for deterministic outputs · hn · 2026-04-29 · 60 upvotes · similarity 0.46
- Robust LLM extractor for websites in TypeScript · hn · 2026-03-26 · 72 upvotes · similarity 0.44
- ata-validator · ph · 2026-10-06 · 6 upvotes · similarity 0.42
- Private JSON Formatter · ph · 2026-10-29 · 1 upvotes · similarity 0.41
- json-toolkit · github · 2026-09-29 · 37 upvotes · similarity 0.39
- Seam · ph · 2026-09-06 · 2 upvotes · similarity 0.38
- json-kit.nvim · github · 2026-09-22 · 8 upvotes · similarity 0.38
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