diff --git a/README.md b/README.md
index bd86a94..cc39d28 100644
--- a/README.md
+++ b/README.md
@@ -198,14 +198,14 @@ Benchmarks test LLM comprehension across different input formats using 209 data
 Each format's overall performance, balancing accuracy against token cost:
 
 ```
-TOON           ████████████████████   26.8  │  73.9% acc  │  2,759 tokens
+TOON           ████████████████████   26.9  │  73.9% acc  │  2,744 tokens
 JSON compact   █████████████████░░░   22.9  │  70.7% acc  │  3,081 tokens
 YAML           ██████████████░░░░░░   18.6  │  69.0% acc  │  3,719 tokens
 JSON           ███████████░░░░░░░░░   15.3  │  69.7% acc  │  4,545 tokens
 XML            ██████████░░░░░░░░░░   13.0  │  67.1% acc  │  5,167 tokens
 ```
 
-TOON achieves **73.9%** accuracy (vs JSON's 69.7%) while using **39.3% fewer tokens**.
+TOON achieves **73.9%** accuracy (vs JSON's 69.7%) while using **39.6% fewer tokens**.
 
 **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.
 
@@ -248,7 +248,7 @@ grok-4-fast-non-reasoning
 ```
 
 > [!TIP] Results Summary
-> TOON achieves **73.9% accuracy** (vs JSON's 69.7%) while using **39.3% fewer tokens** on these datasets.
+> TOON achieves **73.9% accuracy** (vs JSON's 69.7%) while using **39.6% fewer tokens** on these datasets.
 
 <details>
 <summary><strong>Performance by dataset, model, and question type</strong></summary>
@@ -280,7 +280,7 @@ grok-4-fast-non-reasoning
 
 | Format | Accuracy | Tokens | Correct/Total |
 | ------ | -------- | ------ | ------------- |
-| `toon` | 81.1% | 7,282 | 133/164 |
+| `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 |
@@ -313,7 +313,7 @@ grok-4-fast-non-reasoning
 | Format | Accuracy | Tokens | Correct/Total |
 | ------ | -------- | ------ | ------------- |
 | `json-compact` | 63.3% | 4,819 | 76/120 |
-| `toon` | 57.5% | 5,874 | 69/120 |
+| `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 |
@@ -323,7 +323,7 @@ grok-4-fast-non-reasoning
 | Format | Accuracy | Tokens | Correct/Total |
 | ------ | -------- | ------ | ------------- |
 | `json-compact` | 92.2% | 574 | 107/116 |
-| `toon` | 95.7% | 671 | 111/116 |
+| `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 |
@@ -367,7 +367,7 @@ grok-4-fast-non-reasoning
 | ------ | -------- | ------ | ------------- |
 | `csv` | 75.0% | 489 | 3/4 |
 | `yaml` | 100.0% | 996 | 4/4 |
-| `toon` | 100.0% | 1,039 | 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 |
@@ -378,7 +378,7 @@ grok-4-fast-non-reasoning
 | ------ | -------- | ------ | ------------- |
 | `csv` | 100.0% | 329 | 4/4 |
 | `xml` | 100.0% | 1,411 | 4/4 |
-| `toon` | 75.0% | 1,003 | 3/4 |
+| `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 |
@@ -514,34 +514,34 @@ Datasets with nested or semi-uniform structures. CSV excluded as it cannot prope
 ```
 🛒 E-commerce orders with nested structures  ┊  Tabular: 33%
    │
-   TOON                █████████████░░░░░░░    73,271 tokens
-   ├─ vs JSON          (−32.7%)               108,806 tokens
-   ├─ vs JSON compact  (+6.2%)                 68,975 tokens
-   ├─ vs YAML          (−13.6%)                84,780 tokens
-   └─ vs XML           (−40.1%)               122,406 tokens
+   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
 
 🧾 Semi-uniform event logs  ┊  Tabular: 50%
    │
-   TOON                █████████████████░░░   155,211 tokens
-   ├─ vs JSON          (−13.9%)               180,176 tokens
-   ├─ vs JSON compact  (+21.5%)               127,731 tokens
-   ├─ vs YAML          (+0.5%)                154,505 tokens
-   └─ vs XML           (−24.2%)               204,777 tokens
+   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
 
 🧩 Deeply nested configuration  ┊  Tabular: 0%
    │
-   TOON                ██████████████░░░░░░       636 tokens
-   ├─ vs JSON          (−30.8%)                   919 tokens
-   ├─ vs JSON compact  (+12.8%)                   564 tokens
-   ├─ vs YAML          (−5.5%)                    673 tokens
-   └─ vs XML           (−36.9%)                 1,008 tokens
+   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
 
 ──────────────────────────────────── Total ────────────────────────────────────
-   TOON                ████████████████░░░░   229,118 tokens
-   ├─ vs JSON          (−21.0%)               289,901 tokens
-   ├─ vs JSON compact  (+16.1%)               197,270 tokens
-   ├─ vs YAML          (−4.5%)                239,958 tokens
-   └─ vs XML           (−30.2%)               328,191 tokens
+   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
 ```
 
 #### Flat-Only Track
diff --git a/benchmarks/results/retrieval-accuracy.md b/benchmarks/results/retrieval-accuracy.md
index 3b48e69..868103b 100644
--- a/benchmarks/results/retrieval-accuracy.md
+++ b/benchmarks/results/retrieval-accuracy.md
@@ -36,14 +36,14 @@ Benchmarks test LLM comprehension across different input formats using 209 data
 Each format's overall performance, balancing accuracy against token cost:
 
 ```
-TOON           ████████████████████   26.8  │  73.9% acc  │  2,759 tokens
+TOON           ████████████████████   26.9  │  73.9% acc  │  2,744 tokens
 JSON compact   █████████████████░░░   22.9  │  70.7% acc  │  3,081 tokens
 YAML           ██████████████░░░░░░   18.6  │  69.0% acc  │  3,719 tokens
 JSON           ███████████░░░░░░░░░   15.3  │  69.7% acc  │  4,545 tokens
 XML            ██████████░░░░░░░░░░   13.0  │  67.1% acc  │  5,167 tokens
 ```
 
-TOON achieves **73.9%** accuracy (vs JSON's 69.7%) while using **39.3% fewer tokens**.
+TOON achieves **73.9%** accuracy (vs JSON's 69.7%) while using **39.6% fewer tokens**.
 
 **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.
 
@@ -86,7 +86,7 @@ grok-4-fast-non-reasoning
 ```
 
 > [!TIP] Results Summary
-> TOON achieves **73.9% accuracy** (vs JSON's 69.7%) while using **39.3% fewer tokens** on these datasets.
+> TOON achieves **73.9% accuracy** (vs JSON's 69.7%) while using **39.6% fewer tokens** on these datasets.
 
 <details>
 <summary><strong>Performance by dataset, model, and question type</strong></summary>
@@ -118,7 +118,7 @@ grok-4-fast-non-reasoning
 
 | Format | Accuracy | Tokens | Correct/Total |
 | ------ | -------- | ------ | ------------- |
-| `toon` | 81.1% | 7,282 | 133/164 |
+| `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 |
@@ -151,7 +151,7 @@ grok-4-fast-non-reasoning
 | Format | Accuracy | Tokens | Correct/Total |
 | ------ | -------- | ------ | ------------- |
 | `json-compact` | 63.3% | 4,819 | 76/120 |
-| `toon` | 57.5% | 5,874 | 69/120 |
+| `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 |
@@ -161,7 +161,7 @@ grok-4-fast-non-reasoning
 | Format | Accuracy | Tokens | Correct/Total |
 | ------ | -------- | ------ | ------------- |
 | `json-compact` | 92.2% | 574 | 107/116 |
-| `toon` | 95.7% | 671 | 111/116 |
+| `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 |
@@ -205,7 +205,7 @@ grok-4-fast-non-reasoning
 | ------ | -------- | ------ | ------------- |
 | `csv` | 75.0% | 489 | 3/4 |
 | `yaml` | 100.0% | 996 | 4/4 |
-| `toon` | 100.0% | 1,039 | 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 |
@@ -216,7 +216,7 @@ grok-4-fast-non-reasoning
 | ------ | -------- | ------ | ------------- |
 | `csv` | 100.0% | 329 | 4/4 |
 | `xml` | 100.0% | 1,411 | 4/4 |
-| `toon` | 75.0% | 1,003 | 3/4 |
+| `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 |
diff --git a/benchmarks/results/token-efficiency.md b/benchmarks/results/token-efficiency.md
index fca2ac1..b9d2734 100644
--- a/benchmarks/results/token-efficiency.md
+++ b/benchmarks/results/token-efficiency.md
@@ -5,34 +5,34 @@ Datasets with nested or semi-uniform structures. CSV excluded as it cannot prope
 ```
 🛒 E-commerce orders with nested structures  ┊  Tabular: 33%
    │
-   TOON                █████████████░░░░░░░    73,271 tokens
-   ├─ vs JSON          (−32.7%)               108,806 tokens
-   ├─ vs JSON compact  (+6.2%)                 68,975 tokens
-   ├─ vs YAML          (−13.6%)                84,780 tokens
-   └─ vs XML           (−40.1%)               122,406 tokens
+   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
 
 🧾 Semi-uniform event logs  ┊  Tabular: 50%
    │
-   TOON                █████████████████░░░   155,211 tokens
-   ├─ vs JSON          (−13.9%)               180,176 tokens
-   ├─ vs JSON compact  (+21.5%)               127,731 tokens
-   ├─ vs YAML          (+0.5%)                154,505 tokens
-   └─ vs XML           (−24.2%)               204,777 tokens
+   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
 
 🧩 Deeply nested configuration  ┊  Tabular: 0%
    │
-   TOON                ██████████████░░░░░░       636 tokens
-   ├─ vs JSON          (−30.8%)                   919 tokens
-   ├─ vs JSON compact  (+12.8%)                   564 tokens
-   ├─ vs YAML          (−5.5%)                    673 tokens
-   └─ vs XML           (−36.9%)                 1,008 tokens
+   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
 
 ──────────────────────────────────── Total ────────────────────────────────────
-   TOON                ████████████████░░░░   229,118 tokens
-   ├─ vs JSON          (−21.0%)               289,901 tokens
-   ├─ vs JSON compact  (+16.1%)               197,270 tokens
-   ├─ vs YAML          (−4.5%)                239,958 tokens
-   └─ vs XML           (−30.2%)               328,191 tokens
+   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
 ```
 
 #### Flat-Only Track
diff --git a/docs/guide/benchmarks.md b/docs/guide/benchmarks.md
index 380a082..24a8e16 100644
--- a/docs/guide/benchmarks.md
+++ b/docs/guide/benchmarks.md
@@ -52,14 +52,14 @@ Benchmarks test LLM comprehension across different input formats using 209 data
 Each format's overall performance, balancing accuracy against token cost:
 
 ```
-TOON           ████████████████████   26.8  │  73.9% acc  │  2,759 tokens
+TOON           ████████████████████   26.9  │  73.9% acc  │  2,744 tokens
 JSON compact   █████████████████░░░   22.9  │  70.7% acc  │  3,081 tokens
 YAML           ██████████████░░░░░░   18.6  │  69.0% acc  │  3,719 tokens
 JSON           ███████████░░░░░░░░░   15.3  │  69.7% acc  │  4,545 tokens
 XML            ██████████░░░░░░░░░░   13.0  │  67.1% acc  │  5,167 tokens
 ```
 
-TOON achieves **73.9%** accuracy (vs JSON's 69.7%) while using **39.3% fewer tokens**.
+TOON achieves **73.9%** accuracy (vs JSON's 69.7%) while using **39.6% fewer tokens**.
 
 **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.
 
@@ -102,7 +102,7 @@ grok-4-fast-non-reasoning
 ```
 
 > [!TIP] Results Summary
-> TOON achieves **73.9% accuracy** (vs JSON's 69.7%) while using **39.3% fewer tokens** on these datasets.
+> TOON achieves **73.9% accuracy** (vs JSON's 69.7%) while using **39.6% fewer tokens** on these datasets.
 
 <details>
 <summary><strong>Performance by dataset, model, and question type</strong></summary>
@@ -134,7 +134,7 @@ grok-4-fast-non-reasoning
 
 | Format | Accuracy | Tokens | Correct/Total |
 | ------ | -------- | ------ | ------------- |
-| `toon` | 81.1% | 7,282 | 133/164 |
+| `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 |
@@ -167,7 +167,7 @@ grok-4-fast-non-reasoning
 | Format | Accuracy | Tokens | Correct/Total |
 | ------ | -------- | ------ | ------------- |
 | `json-compact` | 63.3% | 4,819 | 76/120 |
-| `toon` | 57.5% | 5,874 | 69/120 |
+| `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 |
@@ -177,7 +177,7 @@ grok-4-fast-non-reasoning
 | Format | Accuracy | Tokens | Correct/Total |
 | ------ | -------- | ------ | ------------- |
 | `json-compact` | 92.2% | 574 | 107/116 |
-| `toon` | 95.7% | 671 | 111/116 |
+| `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 |
@@ -221,7 +221,7 @@ grok-4-fast-non-reasoning
 | ------ | -------- | ------ | ------------- |
 | `csv` | 75.0% | 489 | 3/4 |
 | `yaml` | 100.0% | 996 | 4/4 |
-| `toon` | 100.0% | 1,039 | 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 |
@@ -232,7 +232,7 @@ grok-4-fast-non-reasoning
 | ------ | -------- | ------ | ------------- |
 | `csv` | 100.0% | 329 | 4/4 |
 | `xml` | 100.0% | 1,411 | 4/4 |
-| `toon` | 75.0% | 1,003 | 3/4 |
+| `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 |
@@ -368,34 +368,34 @@ Datasets with nested or semi-uniform structures. CSV excluded as it cannot prope
 ```
 🛒 E-commerce orders with nested structures  ┊  Tabular: 33%
    │
-   TOON                █████████████░░░░░░░    73,271 tokens
-   ├─ vs JSON          (−32.7%)               108,806 tokens
-   ├─ vs JSON compact  (+6.2%)                 68,975 tokens
-   ├─ vs YAML          (−13.6%)                84,780 tokens
-   └─ vs XML           (−40.1%)               122,406 tokens
+   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
 
 🧾 Semi-uniform event logs  ┊  Tabular: 50%
    │
-   TOON                █████████████████░░░   155,211 tokens
-   ├─ vs JSON          (−13.9%)               180,176 tokens
-   ├─ vs JSON compact  (+21.5%)               127,731 tokens
-   ├─ vs YAML          (+0.5%)                154,505 tokens
-   └─ vs XML           (−24.2%)               204,777 tokens
+   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
 
 🧩 Deeply nested configuration  ┊  Tabular: 0%
    │
-   TOON                ██████████████░░░░░░       636 tokens
-   ├─ vs JSON          (−30.8%)                   919 tokens
-   ├─ vs JSON compact  (+12.8%)                   564 tokens
-   ├─ vs YAML          (−5.5%)                    673 tokens
-   └─ vs XML           (−36.9%)                 1,008 tokens
+   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
 
 ──────────────────────────────────── Total ────────────────────────────────────
-   TOON                ████████████████░░░░   229,118 tokens
-   ├─ vs JSON          (−21.0%)               289,901 tokens
-   ├─ vs JSON compact  (+16.1%)               197,270 tokens
-   ├─ vs YAML          (−4.5%)                239,958 tokens
-   └─ vs XML           (−30.2%)               328,191 tokens
+   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
 ```
 
 #### Flat-Only Track
diff --git a/packages/toon/src/decode/parser.ts b/packages/toon/src/decode/parser.ts
index 69a2f31..73e56ec 100644
--- a/packages/toon/src/decode/parser.ts
+++ b/packages/toon/src/decode/parser.ts
@@ -9,25 +9,25 @@ export function parseArrayHeaderLine(
   content: string,
   defaultDelimiter: Delimiter,
 ): { header: ArrayHeaderInfo, inlineValues?: string } | undefined {
-  const trimmed = content.trimStart()
+  const trimmedToken = content.trimStart()
 
   // Find the bracket segment, accounting for quoted keys that may contain brackets
   let bracketStart = -1
 
   // For quoted keys, find bracket after closing quote (not inside the quoted string)
-  if (trimmed.startsWith(DOUBLE_QUOTE)) {
-    const closingQuoteIndex = findClosingQuote(trimmed, 0)
+  if (trimmedToken.startsWith(DOUBLE_QUOTE)) {
+    const closingQuoteIndex = findClosingQuote(trimmedToken, 0)
     if (closingQuoteIndex === -1) {
       return
     }
 
-    const afterQuote = trimmed.slice(closingQuoteIndex + 1)
+    const afterQuote = trimmedToken.slice(closingQuoteIndex + 1)
     if (!afterQuote.startsWith(OPEN_BRACKET)) {
       return
     }
 
     // Calculate position in original content and find bracket after the quoted key
-    const leadingWhitespace = content.length - trimmed.length
+    const leadingWhitespace = content.length - trimmedToken.length
     const keyEndIndex = leadingWhitespace + closingQuoteIndex + 1
     bracketStart = content.indexOf(OPEN_BRACKET, keyEndIndex)
   }
@@ -72,7 +72,6 @@ export function parseArrayHeaderLine(
   }
 
   const afterColon = content.slice(colonIndex + 1).trim()
-
   const bracketContent = content.slice(bracketStart + 1, bracketEnd)
 
   // Try to parse bracket segment
@@ -196,37 +195,37 @@ export function mapRowValuesToPrimitives(values: string[]): JsonPrimitive[] {
 // #region Primitive and key parsing
 
 export function parsePrimitiveToken(token: string): JsonPrimitive {
-  const trimmed = token.trim()
+  const trimmedToken = token.trim()
 
   // Empty token
-  if (!trimmed) {
+  if (!trimmedToken) {
     return ''
   }
 
   // Quoted string (if starts with quote, it MUST be properly quoted)
-  if (trimmed.startsWith(DOUBLE_QUOTE)) {
-    return parseStringLiteral(trimmed)
+  if (trimmedToken.startsWith(DOUBLE_QUOTE)) {
+    return parseStringLiteral(trimmedToken)
   }
 
   // Boolean or null literals
-  if (isBooleanOrNullLiteral(trimmed)) {
-    if (trimmed === TRUE_LITERAL)
+  if (isBooleanOrNullLiteral(trimmedToken)) {
+    if (trimmedToken === TRUE_LITERAL)
       return true
-    if (trimmed === FALSE_LITERAL)
+    if (trimmedToken === FALSE_LITERAL)
       return false
-    if (trimmed === NULL_LITERAL)
+    if (trimmedToken === NULL_LITERAL)
       return null
   }
 
   // Numeric literal
-  if (isNumericLiteral(trimmed)) {
-    const parsedNumber = Number.parseFloat(trimmed)
+  if (isNumericLiteral(trimmedToken)) {
+    const parsedNumber = Number.parseFloat(trimmedToken)
     // Normalize negative zero to positive zero
     return Object.is(parsedNumber, -0) ? 0 : parsedNumber
   }
 
   // Unquoted string
-  return trimmed
+  return trimmedToken
 }
 
 export function parseStringLiteral(token: string): string {