Because your LLM doesnt need another 4,000-character JSON blob to cry about.
The Scene Every Cloud Architect Knows Too Well
Its Friday evening. Youve just wrapped up a solid week of architecture reviews and CI/CD firefighting.
Then suddenlyPagerDuty pings.
Your AI-powered deployment validator has failed again.
The LLM was supposed to summarise an Azure App Service deployment manifest.
Instead, it choked on a 19KB JSON blob and replied:
I cannot process this PowerPoint file.
You check the logs.
The JSON blob fed into the LLM has:
- 42 services
- 118 policy rules
- 7 nested objects spelling doom
- And a token bill that could fund a small island nation
Meanwhile, your FinOps team messages you:
Why did one prompt consume 18,432 tokens?!
Just as you stare into the void, contemplating a career in the tea-making business
TOON walks in quietly.
Like a minimalist samurai.
Ready to solve your token trauma.
Meet TOONToken-Oriented Object Notation
A compact, human-readable, LLM-friendly format designed for the AI era.
TOON is what happens when JSON goes to coding bootcamp, takes minimalism seriously, and stops hoarding punctuation.
Its designed to serialise structured data in a way that LLMs understand more easilyusing fewer tokens and with fewer hallucinations.
If JSON is a 20-page resume,
TOON is the clean 1-page CV that actually gets read.
Why TOON Matters (Especially If You Live in the Cloud)
LLMs struggle with noisy punctuation, long prompts, deeply nested brackets, and repeated field names.
TOON fixes that by:
- Removing unnecessary syntax
- Flattening repetitive structures
- Compressing arrays into tabular form
- Reducing token count by 3060%
For engineers dealing with:
- API specs
- Kubernetes manifests
- Azure Bicep outputs
- CI/CD summaries
- Observability logs
TOON becomes an instant superpower.
Few Cloud & DevOps Examples
ExampleKubernetes Pod Health Summary
JSON
{
"namespace": "prod",
"pods": [
{ "name": "web-7f984d", "status": "Running", "restarts": 1 },
{ "name": "payments-4f29d1", "status": "CrashLoopBackOff", "restarts": 5 }
]
}
TOON
namespace: prod
pods[2]{name,status,restarts}:
web-7f984d,Running,1
payments-4f29d1,CrashLoopBackOff,5
Example 2 Observability Metrics (from official TOON benchmarks)
JSON (5 rows)
{
"metrics": [
{
"date": "2025-01-01",
"views": 5715,
"clicks": 211,
"conversions": 28,
"revenue": 7976.46,
"bounceRate": 0.47
}
]
}
TOON
metrics[5]{date,views,clicks,conversions,revenue,bounceRate}:
2025-01-01,5715,211,28,7976.46,0.47
...
Perfect for telemetry, Grafana streams, log analysis, and dashboards.
When Should You Use TOON? (Straight from the Spec)
Use TOON When:
- Your data is mostly flat or semi-flat
- Youre sending structured data to an LLM
- You want to reduce token costs
- You need to handle large arrays of similar objects
- Youre feeding logs, metrics, or infra configs to an AI agent
Avoid TOON When:
- Your structure is deeply nested (complex trees, recursive objects)
- You need strong schema validation
- Youre interacting with APIs expecting strict JSON
- Your data has highly irregular shapes
A good rule:
If JSON looks like a mazekeep JSON.
If JSON looks like a spreadsheetuse TOON.
TOON vs JSON vs YAMLDeveloper Cage Match
| Feature | JSON | YAML | TOON |
| Readability | Good | Great | Excellent |
| Token Efficiency | Meh | Better | 🔥 Best |
| LLM Accuracy | Decent | Moderate | Highest |
| Human Happiness | Medium | Low (indentation PTSD) | High |
| Ideal Use | APIs | Configs | AI prompts |
Installation & Quick Start (Developers Love This Part)
CLI (no installation required)
npx @toon-format/cli input.json -o output.toon
Pipe from stdin
echo '{"name":"Ada"}' | npx @toon-format/cli
Library (TypeScript)
npm install @toon-format/toon
Usage
import { encode } from '@toon-format/toon';
console.log(encode({
users: [
{id: 1, name: 'Alice'},
{id: 2, name: 'Bob'}
]
}));
Final ThoughtsThe Future Is TOON-Shaped
TOON isnt just another data format.
Its a practical upgrade for anyone using LLMs in Cloud or DevOps.
It reduces token costs.
It improves AI accuracy.
It removes JSON noise.
It cleans up your prompts.
And most importantly
It gives your AI agents a fighting chance to understand your infrastructure.
Try converting one of your ugly JSON prompts today.
Your LLMand your token billwill thank you.
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