| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 24 | | adverbTagCount | 2 | | adverbTags | | 0 | "Theo asked quietly [quietly]" | | 1 | "Theo said finally [finally]" |
| | dialogueSentences | 57 | | tagDensity | 0.421 | | leniency | 0.842 | | rawRatio | 0.083 | | effectiveRatio | 0.07 | |
| 93.08% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1446 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 79.25% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1446 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "eyebrow" | | 1 | "could feel" | | 2 | "flicked" | | 3 | "silence" | | 4 | "warmth" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 101 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 101 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 133 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1437 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 29 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 1039 | | uniqueNames | 13 | | maxNameDensity | 1.25 | | worstName | "Theo" | | maxWindowNameDensity | 3 | | worstWindowName | "Theo" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Silas | 5 | | Golden | 1 | | Empress | 1 | | Tuesday | 1 | | Marsh | 1 | | Rory | 12 | | Thames | 1 | | Theo | 13 | | Cardiff | 1 | | London | 1 | | Evan | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Rory" | | 4 | "Theo" | | 5 | "Evan" |
| | places | | 0 | "Marsh" | | 1 | "Thames" | | 2 | "Cardiff" | | 3 | "London" |
| | globalScore | 0.874 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1437 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 133 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 60 | | mean | 23.95 | | std | 24.9 | | cv | 1.04 | | sampleLengths | | 0 | 85 | | 1 | 7 | | 2 | 6 | | 3 | 103 | | 4 | 43 | | 5 | 2 | | 6 | 18 | | 7 | 52 | | 8 | 3 | | 9 | 36 | | 10 | 81 | | 11 | 8 | | 12 | 3 | | 13 | 40 | | 14 | 2 | | 15 | 2 | | 16 | 43 | | 17 | 41 | | 18 | 4 | | 19 | 3 | | 20 | 60 | | 21 | 4 | | 22 | 60 | | 23 | 7 | | 24 | 2 | | 25 | 3 | | 26 | 3 | | 27 | 24 | | 28 | 3 | | 29 | 55 | | 30 | 7 | | 31 | 3 | | 32 | 61 | | 33 | 6 | | 34 | 2 | | 35 | 1 | | 36 | 1 | | 37 | 46 | | 38 | 59 | | 39 | 2 | | 40 | 14 | | 41 | 5 | | 42 | 56 | | 43 | 21 | | 44 | 8 | | 45 | 2 | | 46 | 5 | | 47 | 43 | | 48 | 47 | | 49 | 51 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 101 | | matches | | |
| 53.48% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 182 | | matches | | 0 | "was staring" | | 1 | "wasn’t watching" | | 2 | "was listening" | | 3 | "was always listening" |
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| 56.93% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 133 | | ratio | 0.03 | | matches | | 0 | "The bar was quiet for a Tuesday—two old men arguing softly over a folded newspaper, a woman in the corner reading a paperback with the spine cracked white." | | 1 | "He stopped a few feet away, and she watched him take her in—the delivery jacket, the damp hair, the cup of tea instead of a glass of wine." | | 2 | "He loosened his tie with one finger, a gesture she remembered from late nights in the library, and she felt a sudden, unwelcome ache for the person she’d been then—the girl who’d argued about tort law until the porters kicked them out, who’d worn her hair in a neat knot and never flinched at a raised voice." | | 3 | "His eyes flicked to the door and back to her, and something in his face shifted—a door opening onto a room he’d spent years pretending wasn’t there." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1046 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.028680688336520075 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.008604206500956023 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 133 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 133 | | mean | 10.8 | | std | 10.07 | | cv | 0.932 | | sampleLengths | | 0 | 25 | | 1 | 38 | | 2 | 22 | | 3 | 7 | | 4 | 4 | | 5 | 2 | | 6 | 14 | | 7 | 28 | | 8 | 19 | | 9 | 26 | | 10 | 16 | | 11 | 21 | | 12 | 3 | | 13 | 10 | | 14 | 9 | | 15 | 2 | | 16 | 10 | | 17 | 8 | | 18 | 2 | | 19 | 24 | | 20 | 13 | | 21 | 13 | | 22 | 3 | | 23 | 25 | | 24 | 11 | | 25 | 5 | | 26 | 18 | | 27 | 10 | | 28 | 28 | | 29 | 5 | | 30 | 3 | | 31 | 12 | | 32 | 5 | | 33 | 3 | | 34 | 3 | | 35 | 11 | | 36 | 29 | | 37 | 2 | | 38 | 2 | | 39 | 6 | | 40 | 30 | | 41 | 3 | | 42 | 4 | | 43 | 7 | | 44 | 3 | | 45 | 5 | | 46 | 26 | | 47 | 4 | | 48 | 3 | | 49 | 4 |
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| 45.11% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3157894736842105 | | totalSentences | 133 | | uniqueOpeners | 42 | |
| 39.68% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 84 | | matches | | 0 | "Then he looked at Rory’s" |
| | ratio | 0.012 | |
| 0.95% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 46 | | totalSentences | 84 | | matches | | 0 | "He looked up, took in" | | 1 | "He poured her tea without" | | 2 | "She was halfway through the" | | 3 | "She set the cup down" | | 4 | "He wore a charcoal suit" | | 5 | "He was staring at her" | | 6 | "He laughed, but it was" | | 7 | "His colleagues hovered behind him." | | 8 | "He waved them toward a" | | 9 | "He stopped a few feet" | | 10 | "He stopped himself" | | 11 | "He repeated it like a" | | 12 | "He wasn’t watching them openly," | | 13 | "He was listening." | | 14 | "He was always listening." | | 15 | "He didn’t sit." | | 16 | "It had become a password," | | 17 | "She could feel Theo waiting," | | 18 | "He loosened his tie with" | | 19 | "he said, not unkindly" |
| | ratio | 0.548 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 84 | | matches | | 0 | "The Raven’s Nest smelled of" | | 1 | "Rory came down the back" | | 2 | "He looked up, took in" | | 3 | "He poured her tea without" | | 4 | "The bar was quiet for" | | 5 | "The walls were crowded with" | | 6 | "Rory sat on the stool" | | 7 | "The scar on her left" | | 8 | "She was halfway through the" | | 9 | "Rory didn’t look up until" | | 10 | "The voice went through her" | | 11 | "She set the cup down" | | 12 | "He wore a charcoal suit" | | 13 | "He was staring at her" | | 14 | "He laughed, but it was" | | 15 | "His colleagues hovered behind him." | | 16 | "He waved them toward a" | | 17 | "Theo came closer, his shoes" | | 18 | "He stopped a few feet" | | 19 | "Something changed in his face." |
| | ratio | 0.929 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 89.29% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 3 | | matches | | 0 | "Rory came down the back stairs with her delivery bag still over one shoulder, her black hair damp at the ends, and found Silas behind the bar drying a glass wit…" | | 1 | "Older, broader through the shoulders, his dark hair cut close at the sides and styled with something that cost more than her weekly shop." | | 2 | "He loosened his tie with one finger, a gesture she remembered from late nights in the library, and she felt a sudden, unwelcome ache for the person she’d been t…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 24 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 17 | | fancyCount | 2 | | fancyTags | | 0 | "He laughed (laugh)" | | 1 | "He repeated (repeat)" |
| | dialogueSentences | 57 | | tagDensity | 0.298 | | leniency | 0.596 | | rawRatio | 0.118 | | effectiveRatio | 0.07 | |