TOON Prompt Generator

Every API call to your LLM costs you money based on tokens consumed. Not just the AI’s response, but your input too. 2025 pricing ranges from $1.25-$6 per million input tokens and $10-$15 per million output tokens. When you’re sending structured data in prompts, your format choice can double or triple those costs.

Regular text prompts waste tokens on verbose descriptions. JSON seems better, but look closer. You’re paying for quotes around every key and value. Braces for every object. Colons. Commas. Repeated key names for each array item. If you’re sending product catalogs, user lists, or training examples to an LLM, those characters add up fast.

The TOON prompt generator solves this by converting your structured data into a token-efficient format that cuts costs by 30-60%. Same information, dramatically fewer tokens charged to your account.

What is a TOON Prompt?

A TOON prompt generator is an AI-powered tool that converts your inputs into optimized TOON format. Think of it as a translator that takes what you’d naturally write and restructures it into the compact TOON format.

TOON stands for Token-Oriented Object Notation. It’s a compact serialization format built specifically for LLM interactions.

Here’s how it works. Textual prompts use a lot of tokens, and JSON repeats field names for every single entry. TOON declares fields once at the top, then lists values in a table-like format. The structure stays explicit, but the clutter disappears. This helps arrange your data for maximum token efficiency.

Here’s an example:

JSON format:

{
  "task": "Recommend movies based on user preferences",
  "user_preferences": {
    "genres": ["sci-fi", "thriller"],
    "rating_min": 7.5,
    "year_min": 2015
  },
  "movies": [
    {"title": "Inception", "genre": "sci-fi", "rating": 8.8, "year": 2010},
    {"title": "Dune", "genre": "sci-fi", "rating": 8.0, "year": 2021},
    {"title": "Twisters", "genre": "thriller", "rating": 7.1, "year": 2024},
    {"title": "Oppenheimer", "genre": "thriller", "rating": 8.5, "year": 2023}
  ],
  "output": "Filter and rank movies matching preferences"
}

~ 280 tokens

TOON format:

task: Recommend movies matching user preferences

preferences[2]{genre, ratingMin, yearMin}:
  sci-fi, 7.5, 2015
  thriller, 7.5, 2015

movies[4]{title, genre, rating, year}:
  Inception, sci-fi, 8.8, 2010
  Dune, sci-fi, 8.0, 2021
  Twisters, thriller, 7.1, 2024
  Oppenheimer, thriller, 8.5, 2023

Output: Rank and return movies matching all criteria.

~140 tokens (50% reduction)

Same data. Way fewer tokens. You can see the field names appear once, not three times.

TOON is completely lossless. You can convert between JSON and TOON without losing a single piece of information. It’s still human-readable, just stripped to essentials.

Normal Text Prompt vs JSON Prompt vs TOON Prompt

Let’s compare three ways you typically send structured data to LLMs, and see how each format impacts your token count.

Normal Text Prompt

This is how you might naturally describe your task in a prompt:

“I have four products in my inventory. The first is a mechanical keyboard with SKU MK-4401, priced at $89, with 156 units in stock. The second is a wireless mouse with SKU WM-4402, priced at $34, with 203 units in stock. The third is an ergonomic chair with SKU EC-4403, priced at $299, with 47 units in stock. The fourth is a monitor arm with SKU MA-4404, priced at $125, with 89 units in stock.”

This reads naturally to humans, but it’s extremely verbose. The AI has to parse through all the connecting words to get the actual data points. Every product needs “the first is,” “priced at,” “with” repeated multiple times. Approximate token count: 95-100 tokens.

JSON Prompt

This is the standard structured approach developers use for JSON prompting:

[{“sku”:”MK-4401″,”product”:”mechanical keyboard”,”price”:89,”stock”:156},{“sku”:”WM-4402″,”product”:”wireless mouse”,”price”:34,”stock”:203},{“sku”:”EC-4403″,”product”:”ergonomic chair”,”price”:299,”stock”:47},{“sku”:”MA-4404″,”product”:”monitor arm”,”price”:125,”stock”:89}]

Much cleaner and more effective than text prompts in most cases. The AI knows exactly what fields exist and what to do. ~55-60 tokens. 

But the problem is you’re paying for quotes around every key and value. Braces for every object. Colons. Commas. Repeated key names like “sku,” “product,” “price,” “stock” for each item. 

All those brackets, braces, and punctuation wrapping every single value add up fast. You’re still wasting significant tokens on structural overhead.

TOON Prompt

TOON prompts eliminate all that repetition and structural bloat. Field names are declared exactly once at the top, then you list pure values in clean rows:

inventory[4]{sku,product,price,stock}:
MK-4401, mechanical keyboard,89,156
WM-4402, wireless mouse,34,203
EC-4403, ergonomic chair,299,47
MA-4404, monitor arm,125,89

After that, it’s pure data in clean rows, no repeated keys, no extra punctuation wrapping every value. Approximate token count: 35-40 tokens.

Why Use TOON Prompts?

You know what a TOON prompt is. Now let’s talk about why it matters for your wallet, your app’s speed, and your data’s reliability. Three main benefits make TOON worth the switch.

Token Cost Reduction

Those 30-60% token savings we mentioned? That translates directly to 30-60% lower API bills. If you’re spending $1,000 monthly on Claude or GPT-4 API calls for structured data processing, TOON drops that to $400-700 for the exact same workload.

Here’s how it adds up. Say you process 100 customer records in a single prompt. JSON might burn 2,847 tokens. TOON handles the same data in 1,228 tokens. That’s 1,619 tokens saved per prompt. Run this 1,000 times daily, and you’ve cut millions of tokens monthly. TOON keeps your data clean while saving tokens, which means your budget stretches further without sacrificing quality.

Performance Improvement

Smaller prompts mean faster responses. LLMs process fewer tokens, which cuts down generation time. This matters when you’re building real-time chatbots or handling high-volume batch processing.

Think about it. Your LLM reads through every token before generating output. Feed it 1,228 tokens instead of 2,847, and it starts responding quicker. The difference might be milliseconds per request, but multiply that across thousands of API calls, and your users notice the speed bump.

Improved Data Parsing Accuracy

The tabular structure we showed earlier isn’t just compact. It’s clearer for AI to interpret. When data sits in neat columns with explicit headers, LLMs make fewer parsing mistakes.

JSON’s nested brackets and scattered key names can confuse models, especially with complex datasets. TOON’s row-column format removes ambiguity. The model knows exactly where each field starts and ends, which reduces hallucinations and extraction errors.

How Does Feedough’s TOON Prompt Generator Work?

The TOON prompt generator handles everything behind the scenes. You enter your data or task, hit generate, and get a properly formatted TOON in seconds.

• Pattern Recognition: Scans your data for repeated structures, uniform fields, and consistent keys. Detects data types (strings, numbers, booleans) and field relationships instantly.
• Intelligent Format Selection: Trained on serialization best practices. Recognizes if your data is deeply nested or irregular, flags edge cases (empty values, special characters, mixed types), and suggests alternatives if needed.
• Automated Conversion: Extracts unique field names, counts array lengths, and formats values into clean rows. Outputs properly formatted TOON ready for your LLM to parse.

Benefits of Using Feedough’s TOON Prompt Generator

You know TOON prompt saves tokens. But here’s what the generator itself brings to the table.

1. Immediate Cost Savings

Start cutting your API bills right now. The generator works with whatever LLM setup you’re already running. No need to refactor your code or change how your application talks to the API. You’re literally saving money from the first prompt you convert.

That’s the thing about this tool. It fits into your workflow without disrupting it.

2. Zero Learning Curve

You don’t need to memorize TOON syntax rules or spend hours reading documentation. The TOON prompt generator handles all the technical formatting decisions for you. Paste your prompt, click convert, and you’re done. You get an optimized prompt in TOON format.

It’s built for developers who want results, not homework.

3. Time Efficiency

Manual formatting takes forever. You’re talking hours of tedious work for what the generator does in seconds. That time goes back to building features your users actually care about.

What this means for you: less time formatting data, more time shipping product.

4. Enterprise Scalability

You get consistent, reliable output whether you’re a solo developer or running production at scale. The generator holds up when your project grows. And that’s exactly when you need it most.

The TOON prompt generator takes a proven optimization technique and makes it accessible to anyone working with LLMs. You get immediate cost savings, faster workflows, and reliable results without the manual overhead. Start optimizing your prompts today and watch your token costs drop.