AI · alternatives · 2026

24 alternatives to CTON: JSON-compatible, token-efficient text format for LLM prompts

CTON provides a JSON-compatible, token-efficient text representation optimized for LLM prompts. - davidesantangelo/cton

CTON is a text format designed to reduce token usage in large language model prompts while maintaining JSON compatibility. It allows developers and AI practitioners to structure data more efficiently, shrinking prompt… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

1
LLMs can generate valid JSON 100% of the time▲854
Outlines is a Python library that focuses on text generation with large language models. Brandon and I are not LLM experts and started the project a few months ago because we wanted to understand better how the generation process works. Our original background is probabilistic, relational and symbolic programming. Recently we came up with a fast way to generate text that matches a regex (https://blog.normalcomputing.ai/posts/2023-07-27-regex-guide...). The basic idea is simple: regular expressions have an equivalent Deterministic-Finite Automaton (DFA) representation. We…
2023 · github.com · its alternatives →
2
Why write code if the LLM can just do the thing? (web app experiment)▲436
I spent a few hours last weekend testing whether AI can replace code by executing directly. Built a contact manager where every HTTP request goes to an LLM with three tools: database (SQLite), webResponse (HTML/JSON/JS), and updateMemory (feedback). No routes, no controllers, no business logic. The AI designs schemas on first request, generates UIs from paths alone, and evolves based on natural language feedback. It works—forms submit, data persists, APIs return JSON—but it's catastrophically slow (30-60s per request), absurdly expensive ($0.05/request), and has zero UI…
Nov 2025 · github.com · its alternatives →
3PT
Predictive text using only 13kb of JavaScript. no LLM▲207
2024 · adamgrant.info · its alternatives →
4
ZEON Format▲1
Stop wasting money on JSON. Save 50%+ tokens on your LLMs
Aug 2026 · zeon-eight.vercel.app · its alternatives →
5
Wordllama – Things you can do with the token embeddings of an LLM▲370
After working with LLMs for long enough, I found myself wanting a lightweight utility for doing various small tasks to prepare inputs, locate information and create evaluators. This library is two things: a very simple model and utilities that inference it (eg. fuzzy deduplication). The target platform is CPU, and it’s intended to be light, fast and pip installable — a library that lowers the barrier to working with strings semantically. You don’t need to install pytorch to use it, or any deep learning runtimes. How can this be accomplished? The model is simply token embeddings that are…
2024 · github.com · its alternatives →
6
Agents.json – OpenAPI Specification for LLMs▲212
Hey HN, we’re building an open specification that lets agents discover and invoke APIs with natural language, built on the OpenAPI standard. agents.json clearly defines the contract between LLMs and API as a standard that's open, observable, and replicable. Here’s a walkthrough of how it works: https://youtu.be/kby2Wdt2Dtk?si=59xGCDy48Zzwr7ND. There’s 2 parts to this: 1. An agents.json file describes how to link API calls together into outcome-based tools for LLMs. This file sits alongside an OpenAPI file. 2. The agents.json SDK loads agents.json files as tools for an LLM that…
2025 · github.com · its alternatives →
7
Min.js style compression of tech docs for LLM context▲177
Min.js Style Compression of Tech Docs for LLM Context - marv1nnnnn/llm-min.txt
2025 · github.com · its alternatives →
8
toon-parse▲6
Fit 40% more context into your LLM prompts for free
Dec 2025 · pypi.org · its alternatives →
9
LCON – Ludicrously Compact Object Notation▲35
Ludicrously Compact Object Notation. Contribute to ar-nelson/lcon development by creating an account on GitHub.
2014 · github.com · its alternatives →
10CW
Chat with your contacts on different platforms without an app▲63
LLM-driven development: Tron is the best way to build app.
2021 · fiotron.com · its alternatives →
11
Robust LLM extractor for websites in TypeScript▲72
We've been building data pipelines that scrape websites and extract structured data for a while now. If you've done this, you know the drill: you write CSS selectors, the site changes its layout, everything breaks at 2am, and you spend your morning rewriting parsers. LLMs seemed like the obvious fix — just throw the HTML at GPT and ask for JSON. Except in practice, it's more painful than that: - Raw HTML is full of nav bars, footers, and tracking junk that eats your token budget. A typical product page is 80% noise. - LLMs return malformed JSON more often than you'd expect, especially with…
Mar 2026 · github.com · its alternatives →
12CE
Convert English to Cron Expressions▲108
2022 · cronprompt.com · its alternatives →
13
A Fast, Malloc-Free C++14 Json Parser and Encoder▲98
Meta programming utilities for C++14. Merged in matt-42/lithium - matt-42/iod
2014 · github.com · its alternatives →
14
JSON Master▲82
Format, repair, convert, and visualize JSON, XML, YAML, CSV, and TOML. Free developer platform with advanced visualizers and AI-powered syntax repair.
2020 · jsonmaster.com · its alternatives →
15
KSON, a love-letter to the humans maintaining computer configuration▲34
Hi friends, I'm really excited to introduce KSON, which just entered public beta! Anywhere a human is reading or editing YAML/JSON/TOML, KSON may be used as a more effective interface on that data. If you are such a human, we invite you to participate in this beta. tl;dr Check out the website [1], play with the online playground [2], install the library for your programming language [3], edit in your favorite editor [4], discuss and give feedback [5], contribute to the project [6]. (A personal note about this project: I love software. Machines made of words! Such a wonder. KSON…
2025 · kson.org · its alternatives →
16
Fine-grained stylistic control of LLMs using model arithmetic▲85
We developed a new framework that enables flexible control of generated text in language models. By combining several models and/or system prompts in one mathematical formula, it lets you tweak your style and combine model outputs with ease. A handy tool for those working with LLMs, looking for more fine-grained control of stylistic output. More details in our paper: https://arxiv.org/abs/2311.14479. Feedback and potential applications are welcome.
2023 · github.com · its alternatives →
17AS
A surprisingly effective way to predict token importance in LLM prompts▲14
We explored a novel method to gauge the significance of tokens in prompts given to large language models, without needing direct model access. Essentially, we just did an ablation study on the prompt using cosine similarity of the embeddings as the measure. We got surprisingly promising results when comparing this really simple approach to integrated gradients. Curious to hear thoughts from the community!
2023 · heatmap.demos.watchful.io · its alternatives →
18
LJSON: JSON extended with pure functions▲39
JSON extended with pure functions. Contribute to VictorTaelin/LJSON development by creating an account on GitHub.
2015 · github.com · its alternatives →
19
Litellm – Simple library to standardize OpenAI, Cohere, Azure LLM I/O▲62
I built this library because langchain was too bloated and I needed a simple abstraction to call multiple LLM APIs. litellm has two functions - completion(), embedding()
2023 · github.com · its alternatives →
20
`tc` like `wc` but for LLM tokens▲8
Little tool that I made to understand how (un)reasonable my prompts are.
Jan 2026 · github.com · its alternatives →
21
Toonifyit▲6
Cut AI token costs 30-60% with smarter JSON encoding
Nov 2025 · toonifyit.com · its alternatives →
22
A tool to Convert JSON schemas into TypeScript Deno classes▲43
Hello all To preface this is just something I've been making as a learning exercise, so all feedback is appreciated. This is a tool that converts JSON schemas into TypeScript utility classes for use in Deno. Automatic Type Generation: Typescript interfaces for the compressed and uncompressed versions of your data. Compression & Decompression: Compress and decompress your data. Validation: Built-in data validation using Ajv ensures your data adheres to the schema. Reusability: Once generated, the utility classes can be used in other Deno projects. It currently only supports a subset of JSON…
2023 · github.com · its alternatives →
23
Bible translated using LLMs from source Greek and Hebrew▲55
Built an auditable AI (Bible) translation pipeline: Hebrew/Greek source packets -> verse JSON with notes rolling up to chapters, books, and testaments. Final texts compiled with metrics (TTR, n-grams). This is the first full-text example as far as I know (Gen Z bible doesn't count). There are hallucinations and issues, but the overall quality surprised me. LLMs have a lot of promise translating and rendering 'accessible' more ancient texts. The technology has a lot of benefit for the faithful, that I think is only beginning to be explored.
Jan 2026 · biblexica.com · its alternatives →
24
Local LLM code-generation with Gemma 4 e2B via JSON AST to Clojure▲22
JSON AST > Clojure. Contribute to quadracollision/llmisp development by creating an account on GitHub.
May 2026 · github.com · its alternatives →

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