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@toon-format/toon - npm Package Compare versions

Comparing version
2.1.0
 to
2.2.0
+20
-2
dist/index.d.mts
//#region src/constants.d.ts
declare const DELIMITERS: {

@@ -134,2 +133,21 @@ readonly comma: ",";

//#endregion
//#region src/decode/errors.d.ts
/**
* Error thrown by the TOON decoder when input cannot be parsed.
*
* Extends `SyntaxError` so existing `instanceof SyntaxError` checks keep working.
* Adds structured location fields for programmatic consumers and richer CLI output.
*/
declare class ToonDecodeError extends SyntaxError {
/** 1-based line number where the error was detected, if known. */
readonly line?: number;
/** Raw source line (including indentation) where the error was detected, if known. */
readonly source?: string;
constructor(message: string, context?: {
line?: number;
source?: string;
cause?: unknown;
});
}
//#endregion
//#region src/index.d.ts

@@ -279,2 +297,2 @@ /**

//#endregion
export { DEFAULT_DELIMITER, DELIMITERS, type DecodeOptions, type DecodeStreamOptions, type Delimiter, type DelimiterKey, type EncodeOptions, type EncodeReplacer, type JsonArray, type JsonObject, type JsonPrimitive, type JsonStreamEvent, type JsonValue, type ResolvedDecodeOptions, type ResolvedEncodeOptions, decode, decodeFromLines, decodeStream, decodeStreamSync, encode, encodeLines };
export { DEFAULT_DELIMITER, DELIMITERS, type DecodeOptions, type DecodeStreamOptions, type Delimiter, type DelimiterKey, type EncodeOptions, type EncodeReplacer, type JsonArray, type JsonObject, type JsonPrimitive, type JsonStreamEvent, type JsonValue, type ResolvedDecodeOptions, type ResolvedEncodeOptions, ToonDecodeError, decode, decodeFromLines, decodeStream, decodeStreamSync, encode, encodeLines };
+2
-2
package.json
{
"name": "@toon-format/toon",
"type": "module",
"version": "2.1.0",
"version": "2.2.0",
"description": "Token-Oriented Object Notation (TOON) – Compact, human-readable, schema-aware encoding of JSON for LLM prompts",

@@ -36,3 +36,3 @@ "author": "Johann Schopplich <hello@johannschopplich.com>",

"devDependencies": {
"@toon-format/spec": "^3.0.0"
"@toon-format/spec": "^3.0.3"
},

@@ -39,0 +39,0 @@ "scripts": {

+184
-216
README.md

@@ -130,3 +130,3 @@ ![TOON logo with step‑by‑step guide](./.github/og.png)

- 📊 **Token-Efficient & Accurate:** TOON reaches 74% accuracy (vs JSON's 70%) while using ~40% fewer tokens in mixed-structure benchmarks across 4 models.
- 📊 **Token-Efficient & Accurate:** TOON reaches 76.4% accuracy (vs JSON's 75.0%) while using ~40% fewer tokens in mixed-structure benchmarks across 4 models.
- 🔁 **JSON Data Model:** Encodes the same objects, arrays, and primitives as JSON with deterministic, lossless round-trips.

@@ -148,3 +148,3 @@ - 🛤️ **LLM-Friendly Guardrails:** Explicit [N] lengths and {fields} headers give models a clear schema to follow, improving parsing reliability.

- **Semi-uniform arrays** (~40–60% tabular eligibility): Token savings diminish. Prefer JSON if your pipelines already rely on it.
- **Pure tabular data**: CSV is smaller than TOON for flat tables. TOON adds minimal overhead (~5-10%) to provide structure (array length declarations, field headers, delimiter scoping) that improves LLM reliability.
- **Pure tabular data**: CSV is smaller than TOON for flat tables. TOON adds minimal overhead (~5–10%) to provide structure (array length declarations, field headers, delimiter scoping) that improves LLM reliability.
- **Latency-critical applications**: If end-to-end response time is your top priority, benchmark on your exact setup. Some deployments (especially local/quantized models like Ollama) may process compact JSON faster despite TOON's lower token count. Measure TTFT, tokens/sec, and total time for both formats and use whichever is faster.

@@ -203,7 +203,7 @@

```
TOON ████████████████████ 26.9 acc%/1K tok │ 73.9% acc │ 2,744 tokens
JSON compact █████████████████░░░ 22.9 acc%/1K tok │ 70.7% acc │ 3,081 tokens
YAML ██████████████░░░░░░ 18.6 acc%/1K tok │ 69.0% acc │ 3,719 tokens
JSON ███████████░░░░░░░░░ 15.3 acc%/1K tok │ 69.7% acc │ 4,545 tokens
XML ██████████░░░░░░░░░░ 13.0 acc%/1K tok │ 67.1% acc │ 5,167 tokens
TOON ████████████████████ 27.7 acc%/1K tok │ 76.4% acc │ 2,759 tokens
JSON compact █████████████████░░░ 23.7 acc%/1K tok │ 73.7% acc │ 3,104 tokens
YAML ██████████████░░░░░░ 19.9 acc%/1K tok │ 74.5% acc │ 3,749 tokens
JSON ████████████░░░░░░░░ 16.4 acc%/1K tok │ 75.0% acc │ 4,587 tokens
XML ██████████░░░░░░░░░░ 13.8 acc%/1K tok │ 72.1% acc │ 5,221 tokens
```

@@ -214,3 +214,3 @@

> [!TIP]
> TOON achieves **73.9%** accuracy (vs JSON's 69.7%) while using **39.6% fewer tokens**.
> TOON achieves **76.4%** accuracy (vs JSON's 75.0%) while using **39.9% fewer tokens**.

@@ -232,9 +232,9 @@ **Note on CSV:** Excluded from ranking as it only supports 109 of 209 questions (flat tabular data only). While CSV is highly token-efficient for simple tabular data, it cannot represent nested structures that other formats handle.

gemini-2.5-flash
→ TOON ██████████████████░░ 87.6% (183/209)
CSV █████████████████░░░ 86.2% (94/109)
JSON compact ████████████████░░░░ 82.3% (172/209)
YAML ████████████████░░░░ 79.4% (166/209)
XML ████████████████░░░░ 79.4% (166/209)
JSON ███████████████░░░░░ 77.0% (161/209)
gemini-3-flash-preview
XML ████████████████████ 98.1% (205/209)
JSON ███████████████████░ 97.1% (203/209)
YAML ███████████████████░ 97.1% (203/209)
→ TOON ███████████████████░ 96.7% (202/209)
JSON compact ███████████████████░ 96.7% (202/209)
CSV ███████████████████░ 96.3% (105/109)

@@ -249,13 +249,13 @@ gpt-5-nano

grok-4-fast-non-reasoning
→ TOON ███████████░░░░░░░░░ 57.4% (120/209)
JSON ███████████░░░░░░░░░ 55.5% (116/209)
JSON compact ███████████░░░░░░░░░ 54.5% (114/209)
YAML ███████████░░░░░░░░░ 53.6% (112/209)
XML ███████████░░░░░░░░░ 52.6% (110/209)
CSV ██████████░░░░░░░░░░ 52.3% (57/109)
grok-4-1-fast-non-reasoning
→ TOON ████████████░░░░░░░░ 58.4% (122/209)
YAML ████████████░░░░░░░░ 57.9% (121/209)
JSON ███████████░░░░░░░░░ 56.5% (118/209)
XML ███████████░░░░░░░░░ 54.1% (113/209)
JSON compact ██████████░░░░░░░░░░ 52.2% (109/209)
CSV ██████████░░░░░░░░░░ 51.4% (56/109)
```
> [!TIP]
> TOON achieves **73.9% accuracy** (vs JSON's 69.7%) while using **39.6% fewer tokens** on these datasets.
> TOON achieves **76.4% accuracy** (vs JSON's 75.0%) while using **39.9% fewer tokens** on these datasets.

@@ -267,9 +267,9 @@ <details>

| Question Type | TOON | JSON compact | JSON | CSV | YAML | XML |
| Question Type | TOON | JSON | YAML | JSON compact | XML | CSV |
| ------------- | ---- | ---- | ---- | ---- | ---- | ---- |
| Field Retrieval | 99.6% | 99.3% | 99.3% | 100.0% | 98.2% | 98.9% |
| Aggregation | 54.4% | 47.2% | 48.8% | 44.0% | 47.6% | 41.3% |
| Filtering | 56.3% | 57.3% | 50.5% | 49.1% | 51.0% | 47.9% |
| Structure Awareness | 88.0% | 83.0% | 83.0% | 85.9% | 80.0% | 80.0% |
| Structural Validation | 70.0% | 45.0% | 50.0% | 80.0% | 60.0% | 80.0% |
| Field Retrieval | 99.6% | 99.3% | 98.5% | 98.5% | 98.9% | 100.0% |
| Aggregation | 61.9% | 61.9% | 59.9% | 58.3% | 54.4% | 50.9% |
| Filtering | 56.8% | 53.1% | 56.3% | 55.2% | 51.6% | 50.9% |
| Structure Awareness | 89.0% | 87.0% | 84.0% | 84.0% | 81.0% | 85.9% |
| Structural Validation | 70.0% | 60.0% | 60.0% | 55.0% | 85.0% | 80.0% |

@@ -282,8 +282,8 @@ #### Performance by Dataset

| ------ | -------- | ------ | ------------- |
| `csv` | 72.0% | 2,352 | 118/164 |
| `toon` | 73.8% | 2,518 | 121/164 |
| `json-compact` | 69.5% | 3,953 | 114/164 |
| `yaml` | 68.3% | 4,982 | 112/164 |
| `json-pretty` | 68.3% | 6,360 | 112/164 |
| `xml` | 69.5% | 7,324 | 114/164 |
| `csv` | 73.2% | 2,334 | 120/164 |
| `toon` | 73.2% | 2,498 | 120/164 |
| `json-compact` | 73.8% | 3,924 | 121/164 |
| `yaml` | 73.8% | 4,959 | 121/164 |
| `json-pretty` | 73.8% | 6,331 | 121/164 |
| `xml` | 74.4% | 7,296 | 122/164 |

@@ -294,7 +294,7 @@ ##### E-commerce orders with nested structures

| ------ | -------- | ------ | ------------- |
| `toon` | 81.1% | 7,232 | 133/164 |
| `json-compact` | 76.8% | 6,794 | 126/164 |
| `yaml` | 75.6% | 8,347 | 124/164 |
| `json-pretty` | 76.2% | 10,713 | 125/164 |
| `xml` | 74.4% | 12,023 | 122/164 |
| `toon` | 82.3% | 7,458 | 135/164 |
| `json-compact` | 78.7% | 7,110 | 129/164 |
| `yaml` | 79.9% | 8,755 | 131/164 |
| `json-pretty` | 79.3% | 11,234 | 130/164 |
| `xml` | 77.4% | 12,649 | 127/164 |

@@ -305,8 +305,8 @@ ##### Time-series analytics data

| ------ | -------- | ------ | ------------- |
| `csv` | 73.3% | 1,406 | 88/120 |
| `toon` | 72.5% | 1,548 | 87/120 |
| `json-compact` | 71.7% | 2,349 | 86/120 |
| `yaml` | 71.7% | 2,949 | 86/120 |
| `json-pretty` | 68.3% | 3,676 | 82/120 |
| `xml` | 68.3% | 4,384 | 82/120 |
| `csv` | 75.0% | 1,411 | 90/120 |
| `toon` | 78.3% | 1,553 | 94/120 |
| `json-compact` | 74.2% | 2,354 | 89/120 |
| `yaml` | 75.8% | 2,954 | 91/120 |
| `json-pretty` | 75.0% | 3,681 | 90/120 |
| `xml` | 72.5% | 4,389 | 87/120 |

@@ -317,8 +317,8 @@ ##### Top 100 GitHub repositories

| ------ | -------- | ------ | ------------- |
| `toon` | 62.9% | 8,779 | 83/132 |
| `csv` | 61.4% | 8,527 | 81/132 |
| `yaml` | 59.8% | 13,141 | 79/132 |
| `json-compact` | 55.3% | 11,464 | 73/132 |
| `json-pretty` | 56.1% | 15,157 | 74/132 |
| `xml` | 48.5% | 17,105 | 64/132 |
| `csv` | 65.9% | 8,527 | 87/132 |
| `toon` | 66.7% | 8,779 | 88/132 |
| `yaml` | 65.2% | 13,141 | 86/132 |
| `json-compact` | 59.8% | 11,464 | 79/132 |
| `json-pretty` | 63.6% | 15,157 | 84/132 |
| `xml` | 56.1% | 17,105 | 74/132 |

@@ -329,7 +329,7 @@ ##### Semi-uniform event logs

| ------ | -------- | ------ | ------------- |
| `json-compact` | 63.3% | 4,819 | 76/120 |
| `toon` | 57.5% | 5,799 | 69/120 |
| `json-pretty` | 59.2% | 6,797 | 71/120 |
| `yaml` | 48.3% | 5,827 | 58/120 |
| `xml` | 46.7% | 7,709 | 56/120 |
| `json-compact` | 68.3% | 4,839 | 82/120 |
| `toon` | 65.0% | 5,819 | 78/120 |
| `json-pretty` | 69.2% | 6,817 | 83/120 |
| `yaml` | 61.7% | 5,847 | 74/120 |
| `xml` | 58.3% | 7,729 | 70/120 |

@@ -340,7 +340,7 @@ ##### Deeply nested configuration

| ------ | -------- | ------ | ------------- |
| `json-compact` | 92.2% | 574 | 107/116 |
| `toon` | 95.7% | 666 | 111/116 |
| `yaml` | 91.4% | 686 | 106/116 |
| `json-pretty` | 94.0% | 932 | 109/116 |
| `xml` | 92.2% | 1,018 | 107/116 |
| `json-compact` | 90.5% | 568 | 105/116 |
| `toon` | 94.8% | 655 | 110/116 |
| `yaml` | 93.1% | 675 | 108/116 |
| `json-pretty` | 92.2% | 924 | 107/116 |
| `xml` | 91.4% | 1,013 | 106/116 |

@@ -351,8 +351,8 @@ ##### Valid complete dataset (control)

| ------ | -------- | ------ | ------------- |
| `toon` | 100.0% | 544 | 4/4 |
| `json-compact` | 100.0% | 795 | 4/4 |
| `yaml` | 100.0% | 1,003 | 4/4 |
| `json-pretty` | 100.0% | 1,282 | 4/4 |
| `csv` | 25.0% | 492 | 1/4 |
| `xml` | 0.0% | 1,467 | 0/4 |
| `toon` | 100.0% | 535 | 4/4 |
| `json-compact` | 100.0% | 787 | 4/4 |
| `yaml` | 100.0% | 992 | 4/4 |
| `json-pretty` | 100.0% | 1,274 | 4/4 |
| `xml` | 25.0% | 1,462 | 1/4 |
| `csv` | 0.0% | 483 | 0/4 |

@@ -363,8 +363,8 @@ ##### Array truncated: 3 rows removed from end

| ------ | -------- | ------ | ------------- |
| `csv` | 100.0% | 425 | 4/4 |
| `xml` | 100.0% | 1,251 | 4/4 |
| `toon` | 0.0% | 474 | 0/4 |
| `json-compact` | 0.0% | 681 | 0/4 |
| `json-pretty` | 0.0% | 1,096 | 0/4 |
| `yaml` | 0.0% | 859 | 0/4 |
| `csv` | 100.0% | 413 | 4/4 |
| `xml` | 100.0% | 1,243 | 4/4 |
| `toon` | 0.0% | 462 | 0/4 |
| `json-pretty` | 0.0% | 1,085 | 0/4 |
| `yaml` | 0.0% | 843 | 0/4 |
| `json-compact` | 0.0% | 670 | 0/4 |

@@ -375,8 +375,8 @@ ##### Extra rows added beyond declared length

| ------ | -------- | ------ | ------------- |
| `csv` | 100.0% | 566 | 4/4 |
| `toon` | 75.0% | 621 | 3/4 |
| `xml` | 100.0% | 1,692 | 4/4 |
| `yaml` | 75.0% | 1,157 | 3/4 |
| `json-compact` | 50.0% | 917 | 2/4 |
| `json-pretty` | 50.0% | 1,476 | 2/4 |
| `csv` | 100.0% | 550 | 4/4 |
| `toon` | 75.0% | 605 | 3/4 |
| `json-compact` | 75.0% | 901 | 3/4 |
| `xml` | 100.0% | 1,678 | 4/4 |
| `yaml` | 75.0% | 1,138 | 3/4 |
| `json-pretty` | 50.0% | 1,460 | 2/4 |

@@ -387,8 +387,8 @@ ##### Inconsistent field count (missing salary in row 10)

| ------ | -------- | ------ | ------------- |
| `csv` | 75.0% | 489 | 3/4 |
| `yaml` | 100.0% | 996 | 4/4 |
| `toon` | 100.0% | 1,019 | 4/4 |
| `json-compact` | 75.0% | 790 | 3/4 |
| `xml` | 100.0% | 1,458 | 4/4 |
| `json-pretty` | 75.0% | 1,274 | 3/4 |
| `csv` | 100.0% | 480 | 4/4 |
| `json-compact` | 100.0% | 782 | 4/4 |
| `yaml` | 100.0% | 985 | 4/4 |
| `toon` | 100.0% | 1,008 | 4/4 |
| `json-pretty` | 100.0% | 1,266 | 4/4 |
| `xml` | 100.0% | 1,453 | 4/4 |

@@ -399,8 +399,8 @@ ##### Missing required fields (no email in multiple rows)

| ------ | -------- | ------ | ------------- |
| `csv` | 100.0% | 329 | 4/4 |
| `xml` | 100.0% | 1,411 | 4/4 |
| `toon` | 75.0% | 983 | 3/4 |
| `yaml` | 25.0% | 960 | 1/4 |
| `json-pretty` | 25.0% | 1,230 | 1/4 |
| `json-compact` | 0.0% | 755 | 0/4 |
| `csv` | 100.0% | 340 | 4/4 |
| `xml` | 100.0% | 1,409 | 4/4 |
| `toon` | 75.0% | 974 | 3/4 |
| `json-pretty` | 50.0% | 1,225 | 2/4 |
| `yaml` | 25.0% | 951 | 1/4 |
| `json-compact` | 0.0% | 750 | 0/4 |

@@ -420,12 +420,12 @@ #### Performance by Model

##### gemini-2.5-flash
##### gemini-3-flash-preview
| Format | Accuracy | Correct/Total |
| ------ | -------- | ------------- |
| `toon` | 87.6% | 183/209 |
| `csv` | 86.2% | 94/109 |
| `json-compact` | 82.3% | 172/209 |
| `yaml` | 79.4% | 166/209 |
| `xml` | 79.4% | 166/209 |
| `json-pretty` | 77.0% | 161/209 |
| `xml` | 98.1% | 205/209 |
| `json-pretty` | 97.1% | 203/209 |
| `yaml` | 97.1% | 203/209 |
| `toon` | 96.7% | 202/209 |
| `json-compact` | 96.7% | 202/209 |
| `csv` | 96.3% | 105/109 |

@@ -443,12 +443,12 @@ ##### gpt-5-nano

##### grok-4-fast-non-reasoning
##### grok-4-1-fast-non-reasoning
| Format | Accuracy | Correct/Total |
| ------ | -------- | ------------- |
| `toon` | 57.4% | 120/209 |
| `json-pretty` | 55.5% | 116/209 |
| `json-compact` | 54.5% | 114/209 |
| `yaml` | 53.6% | 112/209 |
| `xml` | 52.6% | 110/209 |
| `csv` | 52.3% | 57/109 |
| `toon` | 58.4% | 122/209 |
| `yaml` | 57.9% | 121/209 |
| `json-pretty` | 56.5% | 118/209 |
| `xml` | 54.1% | 113/209 |
| `json-compact` | 52.2% | 109/209 |
| `csv` | 51.4% | 56/109 |

@@ -512,3 +512,3 @@ </details>

1. **Format conversion**: Each dataset is converted to all 6 formats (TOON, JSON compact, JSON, CSV, YAML, XML).
1. **Format conversion**: Each dataset is converted to all 6 formats (TOON, JSON, YAML, JSON compact, XML, CSV).
2. **Query LLM**: Each model receives formatted data + question in a prompt and extracts the answer.

@@ -519,3 +519,3 @@ 3. **Validate deterministically**: Answers are validated using type-aware comparison (e.g., `50000` = `$50,000`, `Engineering` = `engineering`, `2025-01-01` = `January 1, 2025`) without requiring an LLM judge.

- **Models tested**: `claude-haiku-4-5-20251001`, `gemini-2.5-flash`, `gpt-5-nano`, `grok-4-fast-non-reasoning`
- **Models tested**: `claude-haiku-4-5-20251001`, `gemini-3-flash-preview`, `gpt-5-nano`, `grok-4-1-fast-non-reasoning`
- **Token counting**: Using `gpt-tokenizer` with `o200k_base` encoding (GPT-5 tokenizer)

@@ -542,30 +542,30 @@ - **Temperature**: Not set (models use their defaults)

│
TOON █████████████░░░░░░░ 72,771 tokens
├─ vs JSON (−33.1%) 108,806 tokens
├─ vs JSON compact (+5.5%) 68,975 tokens
├─ vs YAML (−14.2%) 84,780 tokens
└─ vs XML (−40.5%) 122,406 tokens
TOON █████████████░░░░░░░ 73,126 tokens
├─ vs JSON (−33.3%) 109,599 tokens
├─ vs JSON compact (+5.3%) 69,459 tokens
├─ vs YAML (−14.4%) 85,415 tokens
└─ vs XML (−40.7%) 123,344 tokens
🧾 Semi-uniform event logs ┊ Tabular: 50%
│
TOON █████████████████░░░ 153,211 tokens
├─ vs JSON (−15.0%) 180,176 tokens
├─ vs JSON compact (+19.9%) 127,731 tokens
├─ vs YAML (−0.8%) 154,505 tokens
└─ vs XML (−25.2%) 204,777 tokens
TOON █████████████████░░░ 154,084 tokens
├─ vs JSON (−15.0%) 181,201 tokens
├─ vs JSON compact (+19.9%) 128,529 tokens
├─ vs YAML (−0.8%) 155,397 tokens
└─ vs XML (−25.2%) 205,859 tokens
🧩 Deeply nested configuration ┊ Tabular: 0%
│
TOON ██████████████░░░░░░ 631 tokens
├─ vs JSON (−31.3%) 919 tokens
├─ vs JSON compact (+11.9%) 564 tokens
├─ vs YAML (−6.2%) 673 tokens
└─ vs XML (−37.4%) 1,008 tokens
TOON ██████████████░░░░░░ 620 tokens
├─ vs JSON (−31.9%) 911 tokens
├─ vs JSON compact (+11.1%) 558 tokens
├─ vs YAML (−6.3%) 662 tokens
└─ vs XML (−38.2%) 1,003 tokens
──────────────────────────────────── Total ────────────────────────────────────
TOON ████████████████░░░░ 226,613 tokens
├─ vs JSON (−21.8%) 289,901 tokens
├─ vs JSON compact (+14.9%) 197,270 tokens
├─ vs YAML (−5.6%) 239,958 tokens
└─ vs XML (−31.0%) 328,191 tokens
TOON ████████████████░░░░ 227,830 tokens
├─ vs JSON (−21.9%) 291,711 tokens
├─ vs JSON compact (+14.7%) 198,546 tokens
├─ vs YAML (−5.7%) 241,474 tokens
└─ vs XML (−31.0%) 330,206 tokens
```

@@ -580,17 +580,17 @@

│
CSV ███████████████████░ 46,954 tokens
TOON ████████████████████ 49,831 tokens (+6.1% vs CSV)
├─ vs JSON (−60.7%) 126,860 tokens
├─ vs JSON compact (−36.8%) 78,856 tokens
├─ vs YAML (−50.0%) 99,706 tokens
└─ vs XML (−66.0%) 146,444 tokens
CSV ███████████████████░ 47,102 tokens
TOON ████████████████████ 49,919 tokens (+6.0% vs CSV)
├─ vs JSON (−60.7%) 127,063 tokens
├─ vs JSON compact (−36.9%) 79,059 tokens
├─ vs YAML (−50.1%) 100,011 tokens
└─ vs XML (−65.9%) 146,579 tokens
📈 Time-series analytics data ┊ Tabular: 100%
│
CSV ██████████████████░░ 8,388 tokens
TOON ████████████████████ 9,120 tokens (+8.7% vs CSV)
├─ vs JSON (−59.0%) 22,250 tokens
├─ vs JSON compact (−35.8%) 14,216 tokens
├─ vs YAML (−48.9%) 17,863 tokens
└─ vs XML (−65.7%) 26,621 tokens
CSV ██████████████████░░ 8,383 tokens
TOON ████████████████████ 9,115 tokens (+8.7% vs CSV)
├─ vs JSON (−59.0%) 22,245 tokens
├─ vs JSON compact (−35.9%) 14,211 tokens
├─ vs YAML (−49.0%) 17,858 tokens
└─ vs XML (−65.8%) 26,616 tokens

@@ -607,8 +607,8 @@ ⭐ Top 100 GitHub repositories ┊ Tabular: 100%

──────────────────────────────────── Total ────────────────────────────────────
CSV ███████████████████░ 63,854 tokens
TOON ████████████████████ 67,695 tokens (+6.0% vs CSV)
├─ vs JSON (−58.8%) 164,254 tokens
├─ vs JSON compact (−35.2%) 104,526 tokens
├─ vs YAML (−48.2%) 130,697 tokens
└─ vs XML (−64.4%) 190,160 tokens
CSV ███████████████████░ 63,997 tokens
TOON ████████████████████ 67,778 tokens (+5.9% vs CSV)
├─ vs JSON (−58.8%) 164,452 tokens
├─ vs JSON compact (−35.3%) 104,724 tokens
├─ vs YAML (−48.3%) 130,997 tokens
└─ vs XML (−64.4%) 190,290 tokens
```

@@ -623,3 +623,3 @@

**JSON** (22,250 tokens):
**JSON** (22,245 tokens):

@@ -631,39 +631,39 @@ ```json

"date": "2025-01-01",
"views": 5715,
"clicks": 211,
"conversions": 28,
"revenue": 7976.46,
"bounceRate": 0.47
"views": 6138,
"clicks": 174,
"conversions": 12,
"revenue": 2712.49,
"bounceRate": 0.35
},
{
"date": "2025-01-02",
"views": 7103,
"clicks": 393,
"conversions": 28,
"revenue": 8360.53,
"bounceRate": 0.32
"views": 4616,
"clicks": 274,
"conversions": 34,
"revenue": 9156.29,
"bounceRate": 0.56
},
{
"date": "2025-01-03",
"views": 7248,
"clicks": 378,
"conversions": 24,
"revenue": 3212.57,
"bounceRate": 0.5
"views": 4460,
"clicks": 143,
"conversions": 8,
"revenue": 1317.98,
"bounceRate": 0.59
},
{
"date": "2025-01-04",
"views": 2927,
"clicks": 77,
"conversions": 11,
"revenue": 1211.69,
"bounceRate": 0.62
"views": 4740,
"clicks": 125,
"conversions": 13,
"revenue": 2934.77,
"bounceRate": 0.37
},
{
"date": "2025-01-05",
"views": 3530,
"clicks": 82,
"conversions": 8,
"revenue": 462.77,
"bounceRate": 0.56
"views": 6428,
"clicks": 369,
"conversions": 19,
"revenue": 1317.24,
"bounceRate": 0.3
}

@@ -674,11 +674,11 @@ ]

**TOON** (9,120 tokens):
**TOON** (9,115 tokens):
```
metrics[5]{date,views,clicks,conversions,revenue,bounceRate}:
2025-01-01,5715,211,28,7976.46,0.47
2025-01-02,7103,393,28,8360.53,0.32
2025-01-03,7248,378,24,3212.57,0.5
2025-01-04,2927,77,11,1211.69,0.62
2025-01-05,3530,82,8,462.77,0.56
2025-01-01,6138,174,12,2712.49,0.35
2025-01-02,4616,274,34,9156.29,0.56
2025-01-03,4460,143,8,1317.98,0.59
2025-01-04,4740,125,13,2934.77,0.37
2025-01-05,6428,369,19,1317.24,0.3
```

@@ -859,3 +859,3 @@

[TOON Language Support](https://marketplace.visualstudio.com/items?itemName=vishalraut.vscode-toon) - Syntax highlighting, validation, conversion, and token analysis.
[TOON Language Support](https://marketplace.visualstudio.com/items?itemName=vishalraut.vscode-toon) – Syntax highlighting, validation, conversion, and token analysis.

@@ -868,7 +868,7 @@ ```bash

[tree-sitter-toon](https://github.com/3swordman/tree-sitter-toon) - Grammar for Tree-sitter-compatible editors (Neovim, Helix, Emacs, Zed).
[tree-sitter-toon](https://github.com/3swordman/tree-sitter-toon) – Grammar for Tree-sitter-compatible editors (Neovim, Helix, Emacs, Zed).
### Neovim
[toon.nvim](https://github.com/thalesgelinger/toon.nvim) - Lua-based plugin.
[toon.nvim](https://github.com/thalesgelinger/toon.nvim) – Lua-based plugin.

@@ -930,3 +930,3 @@ ### Other Editors

- [CLI](https://toonformat.dev/cli/) – Command-line tool for JSON↔TOON conversions
- [CLI](https://toonformat.dev/cli/) – Command-line tool for JSON↔TOON conversions
- [Using TOON with LLMs](https://toonformat.dev/guide/llm-prompts) – Prompting strategies & validation

@@ -943,38 +943,6 @@ - [Playgrounds](https://toonformat.dev/ecosystem/tools-and-playgrounds) – Interactive tools

> [!NOTE]
> When implementing TOON in other languages, please follow the [Specification](https://github.com/toon-format/spec/blob/main/SPEC.md) to ensure compatibility across implementations. The [conformance tests](https://github.com/toon-format/spec/tree/main/tests) provide language-agnostic test fixtures that validate your implementations.
TOON has official and community implementations across multiple languages including Python, Rust, Go, Java, Swift, .NET, and many more.
### Official Implementations
See the full list of implementations in the [documentation](https://toonformat.dev/ecosystem/implementations).
> [!TIP]
> These implementations are actively being developed by dedicated teams. Contributions are welcome! Join the effort by opening issues, submitting PRs, or discussing implementation details in the respective repositories.
- **.NET:** [toon_format](https://github.com/toon-format/toon-dotnet) *(in development)*
- **Dart:** [toon](https://github.com/toon-format/toon-dart) *(in development)*
- **Go:** [toon-go](https://github.com/toon-format/toon-go) *(in development)*
- **Java:** [JToon](https://github.com/toon-format/toon-java)
- **Julia:** [ToonFormat.jl](https://github.com/toon-format/ToonFormat.jl)
- **Python:** [toon_format](https://github.com/toon-format/toon-python)
- **Rust:** [toon_format](https://github.com/toon-format/toon-rust)
### Community Implementations
- **Apex:** [ApexToon](https://github.com/Eacaw/ApexToon)
- **C++:** [ctoon](https://github.com/mohammadraziei/ctoon)
- **Clojure:** [toon](https://github.com/vadelabs/toon)
- **Crystal:** [toon-crystal](https://github.com/mamantoha/toon-crystal)
- **Elixir:** [toon_ex](https://github.com/kentaro/toon_ex)
- **Gleam:** [toon_codec](https://github.com/axelbellec/toon_codec)
- **Go:** [gotoon](https://github.com/alpkeskin/gotoon)
- **Scala:** [toon4s](https://github.com/vim89/toon4s)
- **Lua/Neovim:** [toon.nvim](https://github.com/thalesgelinger/toon.nvim)
- **OCaml:** [ocaml-toon](https://github.com/davesnx/ocaml-toon)
- **Perl:** [Data::TOON](https://github.com/ytnobody/p5-Data-TOON)
- **PHP:** [toon-php](https://github.com/HelgeSverre/toon-php)
- **Laravel Framework:** [laravel-toon](https://github.com/jobmetric/laravel-toon)
- **R**: [toon](https://github.com/laresbernardo/toon)
- **Ruby:** [toon-ruby](https://github.com/andrepcg/toon-ruby)
- **Swift:** [TOONEncoder](https://github.com/mattt/TOONEncoder)
- **Kotlin:** [Kotlin-Toon Encoder/Decoder](https://github.com/vexpera-br/kotlin-toon)
## Credits

@@ -981,0 +949,0 @@ 

dist/index.mjs

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