The open reference library

Reference data.
Ready to use.

Look up facts for your code, study notes or AI prompts without rebuilding a reference table. Read 205 free datasets, then reuse the rows in JSON, YAML or TOON.

Browse all 205 datasetsUse the API →
Same facts. Three formats.Try the reference press ↓
phonetic-alphabet · first 8 rows108 bytes · TOON
data[8]{letter,code_word}:
  A,Alpha
  B,Bravo
  C,Charlie
  D,Delta
  E,Echo
  F,Foxtrot
  G,Golf
  H,Hotel
63% smaller than minified JSONRead the source table →
205 datasets · 27 subjectsCC0 public domainNo keys. No signup.104 practical guides

Start with the task

What are you building?

Explore the collections →
01

Build a reliable API

Make cache behavior, retries, and response headers explicit before your endpoint reaches production.

5 datasets · 3 guides 02

Give an agent better context

Ground answers in compact reference data, validate the shape, and measure the failures.

5 datasets · 4 guides 03

Query data with confidence

Choose joins, windows, indexes, and transaction boundaries from the question you need to answer.

6 datasets · 3 guides 04

Work safely in the terminal

Find files, recover Git work, and write shell commands that handle real filenames.

5 datasets · 1 guide 05

Make the web work for everyone

Build usable layouts, keyboard interactions, text search, and time handling.

5 datasets · 4 guides 06

Measure, evaluate, and operate

Connect service signals, background jobs, probability, and experiment design to real decisions.

6 datasets · 4 guides

Browse

205 datasets on 27 shelves.

Each spine is a category, as tall as the number of datasets it holds, and keeps its color wherever it appears on this site. Point at one to read it; select it to open it. Type / to search instead.

Code & models

Programming Languages

Syntax, features, and comparisons of major programming languages.

Open all 12 datasets →

Code & models

Data Structures

Fundamental data structures with properties and complexity analysis.

Open all 10 datasets →

Code & models

Algorithms

Classic algorithms, strategies, and complexity.

Open all 7 datasets →

Code & models

Design Patterns

Software design patterns with descriptions and use cases.

Open all 8 datasets →

Code & models

AI & ML Terms

Key terminology in artificial intelligence and machine learning.

Open all 12 datasets →

Systems & the web

Unix Commands

Common Unix/Linux shell commands and their usage.

Open all 11 datasets →

Systems & the web

DevOps

DevOps practices, CI/CD, and infrastructure as code.

Open all 7 datasets →

Systems & the web

Cloud Computing

Cloud service models, providers, and deployment patterns.

Open all 7 datasets →

Systems & the web

Networking

Network protocols, models, and architecture.

Open all 7 datasets →

Systems & the web

HTTP Status Codes

Complete reference of HTTP response status codes.

Open all 13 datasets →

Systems & the web

Web Technologies

Standards, protocols, and APIs for web development.

Open all 13 datasets →

Systems & the web

Database Types

Different database systems and their characteristics.

Open all 12 datasets →

Systems & the web

Cybersecurity

Security principles, threats, and defensive practices.

Open all 6 datasets →

Natural science

Mathematics

Core mathematical concepts, theorems, and notation.

Open all 9 datasets →

Natural science

Physics

Core physics concepts and laws.

Open all 6 datasets →

Natural science

Biology

Fundamental concepts in biology: cell biology, genetics, evolution, and ecology.

Open all 6 datasets →

People & society

History

Major historical events, civilizations, eras, and turning points that shaped the modern world.

Open all 6 datasets →

People & society

Philosophy

Major philosophical traditions, schools of thought, key thinkers, and fundamental questions.

Open all 6 datasets →

People & society

Psychology

Psychological concepts, disorders, and theories.

Open all 6 datasets →

People & society

Literature

Literary movements, genres, narrative techniques, and major works across history.

Open all 6 datasets →

What TOON removes

Same facts. Less syntax.

Scroll to watch eight real rows of the NATO phonetic alphabet lose everything a reader does not need — the keys repeated on every row, then the braces and quotes — until only the header and the values remain.

  • The JSONEight sample rows, with their original keys and values.
  • Keys, spelled on every row"letter" and "code_word" appear eight times each. They are the same eight times.
  • Repeated punctuationFor these uniform text rows, braces and quotes can go. Commas and newlines separate the values.
  • TOONThe keys, once, in a header. Every row is just values.
phonetic-alphabet · first 8 rows 292 → 108 bytes 
{"data":[data[8]{letter,code_word}:{"letter":"A","code_word":"Alpha"},{"letter":"B","code_word":"Bravo"},{"letter":"C","code_word":"Charlie"},{"letter":"D","code_word":"Delta"},{"letter":"E","code_word":"Echo"},{"letter":"F","code_word":"Foxtrot"},{"letter":"G","code_word":"Golf"},{"letter":"H","code_word":"Hotel"}]}

292 bytes as minified JSON, 108 as TOON: 63% smaller for these rows. Whole-catalog figures use a real tokenizer and are in the table below.

Visual browser

205 datasets, one cube each.

Every cube is one dataset. Every stack is one category, and its height is how many datasets that category holds — so the silhouette below is the catalog itself. Drag to turn it, hover to identify a cube, select it to open that dataset's page.

Loading the catalog…

Cube height is the number of datasets in that category. Color identifies the category and carries no other meaning.

Categories

  1. Programming Languages12
  2. HTTP Status Codes13
  3. Data Structures10
  4. Algorithms7
  5. AI & ML Terms12
  6. Web Technologies13
  7. Unix Commands11
  8. Design Patterns8
  9. Database Types12
  10. Operating Systems5
  11. Networking7
  12. Cybersecurity6
  13. Cloud Computing7
  14. DevOps7
  15. Mathematics9
  16. Physics6
  17. Chemistry5
  18. Biology6
  19. Astronomy5
  20. History6
  21. Geography5
  22. Economics5
  23. Philosophy6
  24. Literature6
  25. Linguistics5
  26. Psychology6
  27. Law5

Prefer a list you can read straight through? Open the full catalog — all 205 datasets, one page each →

TOON Studio

See the saving on your own data.

Paste JSON and this page encodes it in your browser with the same encoder the API uses. Byte counts are exact; token counts are labelled estimates. Table-shaped data saves the most — try a flat list of records, then a deeply nested config, and watch the number move.

Samples
JSON in llm-glossary
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  • —
  • —
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Token counts here are estimates from a character heuristic; the site-wide figures above use a real tokenizer. The browser encoder (js/toon.js) is held byte-identical to the server's by scripts/tests/toon-parity.php and checked against the reference TOON implementation by scripts/tests/toon-conformance.mjs.

Use cases

What it's for.

Use a known table when you need a specific key, code or definition. These guides show how to choose the rows, include their context and check the result.

Prompting

Give an agent a stable facts table

Give an agent the reference rows it needs, with their source and scope. Then check its answer against those values.

Read the template Cost

Compare the tokens your prompt needs

Measure the same payload in each format before choosing an encoding. Table-shaped data often becomes smaller in TOON; deeply nested or prose-heavy data may not.

See the measurement Correctness

Check an answer instead of trusting it

Compare the model's output against a known table and fail loudly when a value does not exist.

Read the method Architecture

Skip the index when you need one answer

When the answer is a known key or code, retrieve its row directly. Save semantic retrieval for questions that need it.

Read the argument

Choose a format

One dataset, three encodings.

The same data lives on the server once. What changes is what it costs in a prompt and how it reads in an editor.

Tokens to send all 205 datasets (o200k_base, as served)

  • JSONas served 272,226
  • YAML 218,093−20% vs JSON
  • JSON, minifiedno whitespace 197,572−27% vs JSON
  • TOON 183,346−33% vs JSON
Measured on all 205 datasets as served (1,322,052 bytes of JSON) and on the combined catalog index. Tokens: o200k_base.
PropertyJSONYAMLTOON
Readable by a human Yes, with punctuation noise Indented keys and values Yes — uniform rows become a table
Parser required Built into every language A YAML library A TOON library, or a line parser — this site publishes a small Python one
Nested data Native Native Native, plus a tabular form for uniform arrays
Size of the catalog index 72 KB 48 KB 37 KB (−49%)
Tokens, all 205 datasets 272,226 218,093 (−20%) 183,346 (−33%)
Against minified JSON Baseline: 197,572 tokens Larger −7% overall; 181 of 205 datasets smaller
Reach for it when Services exchange data and every language must parse it A human edits the file Table-shaped data goes into a prompt on every request

Best case: prime-numbers-list uses 60% fewer tokens in TOON than the served JSON. Every dataset page shows its own sizes in all three formats. Pick one and compare →

About

A reference you can inspect and reuse. Read the rows, field definitions, sources and editorial caveats together, then decide whether a dataset fits your task.

Maintained by Yunus Emre Vurgun to make compact reference tables available to people and software. How the catalog is organized →

Found a correction or have a question? Open the creator’s website → Include the dataset URL and the source for the correction. For new guides, follow the RSS feed.

Also from the author

How to Remain Valuable When Intelligence Becomes Cheap

Intelligence is becoming cheap. Judgment, ownership, and trust are not — this book maps the advantages that stay scarce.

Format
PDF + EPUB
Length
224 pages
Price
$3.84
  • The human edge: accountability, taste, and trust in an age of fluent machines
  • The economics: what gets commoditized, what stays scarce, and where to stand
  • Practical moves for people who build with AI every day
View ebook on Gumroad Read a free guide first

Start free: Decision biases checklist · How this catalog pays for itself · Grounding LLM answers

How to Remain Valuable When Intelligence Becomes Cheap, book cover
Open Data for AGI — Why Public, Free, and Open Datasets Matter, book cover

The book behind this catalog

Open Data for AGI

A practical brief on why public, free, and open datasets decide what AI systems become.

eBook · PDF · $4.99 · All site data stays free; the book is the argument, not a paywall.

View Open Data for AGI on Gumroad Read the free summary

The five machines0:00 / 8:50

Film · 8:50 · English captions

Five products gave the chatbot its own computer. Rented or owned?

Grok Bot, Meta Muse, ChatGPT Dots, OpenClaw and Hermes compared in an 8-minute film: what each one does, who it is for, what it costs, and rented versus owned.

Watch with chapters and transcript Read the comparison

Blog

Latest posts →

All 104 posts → · RSS

FAQ

Short answers.

Is YJTOON free to use?

Yes. All 205 datasets are published under CC0. Read or download them without an account, API key or payment. The dynamic API allows 120 requests per minute per IP; static downloads do not use that API limit. The author's ebooks are separate purchases on Gumroad.

What is TOON?

TOON (Token-Oriented Object Notation) is a compact text encoding for structured data, aimed at prompts rather than at storage. A uniform array of objects becomes a table: the field names are written once in a header and every row carries only values. The encoder here follows the public TOON format and is checked against its reference implementation on every build.

Read the grammar overview → · Try it on your own JSON →

How much does TOON actually save?

Measured with the o200k_base tokenizer across all 205 datasets: 183,346 tokens in TOON versus 272,226 in the JSON files this site serves — 33% fewer, and up to 60% fewer on the best dataset (prime-numbers-list). Against minified JSON the overall saving is only 7%, because prose-heavy datasets gain little; 181 of 205 datasets are still smaller in TOON than in minified JSON. TOON pays off most on table-shaped data.

See the measurement →

Do I need an API key?

No. Send a GET request to a documented endpoint. The API rate limiter stores a hash of the requesting IP address and a hash of browser headers to count requests and apply cooldowns. This describes the API limiter, not separate hosting access logs.

Can I use the data in a commercial product?

The datasets are published under CC0, with no attribution requirement for reuse, including commercial reuse. Check the source and editorial notes for the material you use. The data license does not establish that a reference is accurate, current or suitable for every purpose.

What CC0 actually covers →

How is this different from a vector database?

A vector index retrieves items by similarity. Reference tables support exact lookups when the answer is a known key, code, or rule. Use semantic retrieval for less structured questions; use a known row when you need a precise reference value.

When not to use a vector database →

How do I use a dataset?

Find a topic in the catalog or a task in Collections. Open a dataset to inspect its rows, fields, source notes and caveats. Then download JSON, YAML or TOON, or copy its API request into your project. No registration is part of that journey.

Inspect the HTTP status reference → · Read the API examples →

What should I check before relying on a reference?

These are editorial reference tables, not a live feed or a complete specification. Check each dataset’s scope, dates and caveats, then confirm version-sensitive details against the linked primary sources. A smaller encoding changes the format, not the reliability of the underlying facts.

What happens to JSON I paste into TOON Studio?

The encoder runs in this browser tab. Pasted input is not sent to the API by TOON Studio. Sample buttons fetch public datasets from this site. Copy any output you need before leaving; the studio does not save your input for you.

Try the browser encoder →

How should I cite a dataset?

Every dataset page includes a suggested citation and a permanent URL. Attribution is not required under CC0, but it helps other people find the source.

See a dataset page and its citation →

Search the library

Search by a topic, title, or keyword.

Start with a collection

Browse all 205 datasets