| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 26 | | adverbTagCount | 2 | | adverbTags | | 0 | "he said quietly [quietly]" | | 1 | "He smiled just [just]" |
| | dialogueSentences | 84 | | tagDensity | 0.31 | | leniency | 0.619 | | rawRatio | 0.077 | | effectiveRatio | 0.048 | |
| 90.60% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1595 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slowly" | | 1 | "very" | | 2 | "slightly" |
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| 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) | |
| 90.60% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1595 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "weight" | | 1 | "traced" | | 2 | "eyebrow" |
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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 | 1 | | narrationSentences | 129 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 129 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 187 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 24 | | totalWords | 1586 | | ratio | 0.015 | | matches | | 0 | "things to be dealt with later" | | 1 | "Silas, the girl is in trouble and I am too ill to do anything about it. Promise me." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 37 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 10 | | wordCount | 1036 | | uniqueNames | 9 | | maxNameDensity | 0.19 | | worstName | "Silas" | | maxWindowNameDensity | 0.5 | | worstWindowName | "Silas" | | discoveredNames | | London | 1 | | Underground | 1 | | Windmill | 1 | | Silas | 2 | | Blackwood | 1 | | Cardiff | 1 | | Tottenham | 1 | | Walthamstow | 1 | | Acton | 1 |
| | persons | | | places | | 0 | "London" | | 1 | "Windmill" | | 2 | "Cardiff" | | 3 | "Tottenham" | | 4 | "Walthamstow" | | 5 | "Acton" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 50 | | glossingSentenceCount | 1 | | matches | | 0 | "as if filing it away in some internal cabinet marked *things to be dealt with later" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1586 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 187 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 85 | | mean | 18.66 | | std | 22.42 | | cv | 1.202 | | sampleLengths | | 0 | 71 | | 1 | 68 | | 2 | 31 | | 3 | 3 | | 4 | 73 | | 5 | 3 | | 6 | 10 | | 7 | 106 | | 8 | 8 | | 9 | 13 | | 10 | 13 | | 11 | 12 | | 12 | 4 | | 13 | 25 | | 14 | 12 | | 15 | 24 | | 16 | 41 | | 17 | 5 | | 18 | 22 | | 19 | 3 | | 20 | 4 | | 21 | 57 | | 22 | 8 | | 23 | 9 | | 24 | 12 | | 25 | 4 | | 26 | 8 | | 27 | 20 | | 28 | 1 | | 29 | 40 | | 30 | 8 | | 31 | 7 | | 32 | 9 | | 33 | 8 | | 34 | 19 | | 35 | 10 | | 36 | 6 | | 37 | 45 | | 38 | 1 | | 39 | 11 | | 40 | 13 | | 41 | 15 | | 42 | 8 | | 43 | 54 | | 44 | 7 | | 45 | 3 | | 46 | 2 | | 47 | 48 | | 48 | 7 | | 49 | 17 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 129 | | matches | | 0 | "been said" | | 1 | "been swallowed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 189 | | matches | | |
| 51.18% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 187 | | ratio | 0.032 | | matches | | 0 | "And the smell of the place—old wood, spilled whisky, the particular must of leather and secrets—hit her like a memory she hadn't asked for." | | 1 | "His face did something complicated—a tightening at the jaw, a softening at the eyes, a small intake of breath that he tried to disguise by setting the glass down." | | 2 | "She stood in the middle of the room with her delivery bag still over her shoulder, a strap cutting into the wool of her coat, and looked at him properly for the first time in—how long?" | | 3 | "She watched his hands—those long, precise hands, the knuckles swollen now, the tendons standing out like rigging on a ship." | | 4 | "Whatever else he was—whatever else he had done, whatever else he had failed to do—the man knew how to stock a shelf." | | 5 | "It came out wrong—too sharp, too loud, a sound that startled both of them." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1050 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 33 | | adverbRatio | 0.03142857142857143 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005714285714285714 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 187 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 187 | | mean | 8.48 | | std | 7.94 | | cv | 0.936 | | sampleLengths | | 0 | 20 | | 1 | 21 | | 2 | 3 | | 3 | 3 | | 4 | 24 | | 5 | 3 | | 6 | 21 | | 7 | 18 | | 8 | 8 | | 9 | 9 | | 10 | 9 | | 11 | 23 | | 12 | 3 | | 13 | 5 | | 14 | 3 | | 15 | 4 | | 16 | 29 | | 17 | 10 | | 18 | 3 | | 19 | 4 | | 20 | 3 | | 21 | 20 | | 22 | 3 | | 23 | 6 | | 24 | 4 | | 25 | 12 | | 26 | 8 | | 27 | 3 | | 28 | 36 | | 29 | 2 | | 30 | 1 | | 31 | 26 | | 32 | 6 | | 33 | 8 | | 34 | 4 | | 35 | 4 | | 36 | 4 | | 37 | 5 | | 38 | 8 | | 39 | 7 | | 40 | 6 | | 41 | 7 | | 42 | 5 | | 43 | 4 | | 44 | 19 | | 45 | 4 | | 46 | 2 | | 47 | 5 | | 48 | 7 | | 49 | 23 |
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| 30.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 36 | | diversityRatio | 0.24064171122994651 | | totalSentences | 187 | | uniqueOpeners | 45 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 98 | | matches | | 0 | "Then she did." | | 1 | "Then she wished she hadn't." | | 2 | "Of course he did." |
| | ratio | 0.031 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 65 | | totalSentences | 98 | | matches | | 0 | "She paused with her hand" | | 1 | "She stepped inside." | | 2 | "His face did something complicated—a" | | 3 | "He looked older." | | 4 | "They all did." | | 5 | "She held up a hand" | | 6 | "He nodded, slowly, as if" | | 7 | "He gestured to a stool" | | 8 | "She didn't sit." | | 9 | "She stood in the middle" | | 10 | "He had come to the" | | 11 | "She had walked past him" | | 12 | "He had let her." | | 13 | "She had never written." | | 14 | "He had never called." | | 15 | "It was a lie, but" | | 16 | "He set the cloth down" | | 17 | "He looked at her." | | 18 | "He gave a small, tired" | | 19 | "She sat down." |
| | ratio | 0.663 | |
| 0.82% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 90 | | totalSentences | 98 | | matches | | 0 | "The green neon of the" | | 1 | "She paused with her hand" | | 2 | "The key turned." | | 3 | "The door opened." | | 4 | "She stepped inside." | | 5 | "The bar was quiet, the" | | 6 | "The black-and-white photographs on the" | | 7 | "A map of the London" | | 8 | "A photograph of a woman" | | 9 | "A faded poster for a" | | 10 | "Silas Blackwood looked up." | | 11 | "His face did something complicated—a" | | 12 | "The signet ring on his" | | 13 | "He looked older." | | 14 | "They all did." | | 15 | "She held up a hand" | | 16 | "He nodded, slowly, as if" | | 17 | "He gestured to a stool" | | 18 | "She didn't sit." | | 19 | "She stood in the middle" |
| | ratio | 0.918 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 98 | | matches | (empty) | | ratio | 0 | |
| 53.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 4 | | matches | | 0 | "Behind the bar, polishing a glass with a cloth that had seen better decades, stood a man she did not at first recognise." | | 1 | "Outside, a motorbike passed, its engine rising and falling like a question." | | 2 | "The small crescent-shaped scar on her left wrist, from a childhood accident, from a fall in the garden, from a life that had not yet learned to be careful." | | 3 | "The look of a man who had done the same arithmetic, with different numbers, and arrived at a different sum that still came to nothing." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 26 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 19 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 84 | | tagDensity | 0.226 | | leniency | 0.452 | | rawRatio | 0 | | effectiveRatio | 0 | |