| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 36 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.40% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1724 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "very" | | 1 | "slowly" | | 2 | "really" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 82.60% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1724 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "measured" | | 1 | "silence" | | 2 | "flicker" | | 3 | "stomach" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 109 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 109 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 128 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 59 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1735 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 15 | | wordCount | 1449 | | uniqueNames | 10 | | maxNameDensity | 0.21 | | worstName | "Looked" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Looked" | | discoveredNames | | Tuesday | 2 | | Eva | 2 | | Moreau | 1 | | Good | 1 | | French | 1 | | January | 1 | | Soho | 1 | | Looked | 3 | | London | 2 | | Silas | 1 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Looked" | | 3 | "Silas" |
| | places | | 0 | "January" | | 1 | "Soho" | | 2 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 39.71% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like it had been poured onto him" | | 1 | "as if asking permission, came to rest over her clasped hands" | | 2 | "sounded like a confession" |
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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 | 1735 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 128 | | matches | | 0 | "learned that lesson" | | 1 | "hear that her" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 36.91 | | std | 27 | | cv | 0.731 | | sampleLengths | | 0 | 24 | | 1 | 82 | | 2 | 11 | | 3 | 13 | | 4 | 77 | | 5 | 6 | | 6 | 58 | | 7 | 5 | | 8 | 46 | | 9 | 20 | | 10 | 25 | | 11 | 3 | | 12 | 82 | | 13 | 10 | | 14 | 68 | | 15 | 5 | | 16 | 12 | | 17 | 17 | | 18 | 4 | | 19 | 46 | | 20 | 80 | | 21 | 61 | | 22 | 44 | | 23 | 51 | | 24 | 53 | | 25 | 84 | | 26 | 79 | | 27 | 15 | | 28 | 49 | | 29 | 40 | | 30 | 58 | | 31 | 5 | | 32 | 4 | | 33 | 72 | | 34 | 29 | | 35 | 75 | | 36 | 35 | | 37 | 39 | | 38 | 3 | | 39 | 4 | | 40 | 71 | | 41 | 17 | | 42 | 31 | | 43 | 60 | | 44 | 12 | | 45 | 19 | | 46 | 31 |
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| 89.17% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 109 | | matches | | 0 | "been poured" | | 1 | "been ambushed" | | 2 | "were gone" | | 3 | "was annoyed" | | 4 | "been told" |
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| 94.18% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 252 | | matches | | 0 | "were waiting" | | 1 | "was introducing" | | 2 | "was protecting" | | 3 | "was beginning" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 128 | | ratio | 0.078 | | matches | | 0 | "Rory was halfway out of her work clothes, one leg still in her trousers, when she heard it — three measured raps against the wood of her door, the sound of a man who knew exactly how long to wait between knocks to make the silence feel deliberate." | | 1 | "She pulled her trousers back up, grabbed the first thing that wasn't a weapon — a chipped mug of cold tea — and crossed to the peephole." | | 2 | "Lucien Moreau leaned on his ivory-handled cane like it was the most natural thing in the world to be standing outside her door at eleven-fifteen on a Tuesday, his platinum hair combed back, his mismatched eyes — one amber, one black as a starless sky — lifted toward the peephole as though he could see straight through it." | | 3 | "Instead he inclined his head, just a fraction, and she watched the light from her flat catch the sharp line of his jaw, the pale column of his throat where his collar sat open — one button undone, always one button undone, even in January, as if the cold had personally wronged him and he refused to acknowledge it." | | 4 | "\"Because I was wrong.\" He said it simply, the way he said most things — as if the truth were a small, polite guest he was introducing to the room for the first time." | | 5 | "She had a whole list — a literal list, written on the back of a takeout menu and pinned above the kettle — of things she would say if she ever saw him again, and not one of them was kind." | | 6 | "Replaced by the sight of him — the way the light caught the silver at his temples, the way his gloved hand rested on the head of his cane, the way he held himself a little off-balance, as though the leg he favored were a secret he was protecting." | | 7 | "He had the decency, at least, not to look around — not to inventory the evidence of her small, careful life, the books borrowed from Eva and stacked by the radiator, the jacket slung over the back of a chair, the small crescent-shaped scar on her left wrist catching the light as she folded her arms across her chest." | | 8 | "\"—at being here. In person. Saying the wrong thing in the right way. I have been told this is a flaw.\"" | | 9 | "His mouth curved, the smallest fraction, and there it was — the thing that had undone her the first time, the thing she had tried to outrun in two different flats in two different boroughs." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 556 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.03597122302158273 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.007194244604316547 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 128 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 128 | | mean | 13.55 | | std | 13.37 | | cv | 0.987 | | sampleLengths | | 0 | 24 | | 1 | 48 | | 2 | 10 | | 3 | 24 | | 4 | 5 | | 5 | 6 | | 6 | 5 | | 7 | 6 | | 8 | 1 | | 9 | 1 | | 10 | 27 | | 11 | 5 | | 12 | 45 | | 13 | 6 | | 14 | 58 | | 15 | 5 | | 16 | 4 | | 17 | 4 | | 18 | 3 | | 19 | 22 | | 20 | 8 | | 21 | 5 | | 22 | 12 | | 23 | 1 | | 24 | 3 | | 25 | 4 | | 26 | 21 | | 27 | 4 | | 28 | 3 | | 29 | 3 | | 30 | 4 | | 31 | 16 | | 32 | 59 | | 33 | 7 | | 34 | 3 | | 35 | 13 | | 36 | 21 | | 37 | 4 | | 38 | 4 | | 39 | 26 | | 40 | 5 | | 41 | 6 | | 42 | 6 | | 43 | 9 | | 44 | 8 | | 45 | 4 | | 46 | 34 | | 47 | 12 | | 48 | 6 | | 49 | 3 |
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| 47.40% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 26 | | diversityRatio | 0.40625 | | totalSentences | 128 | | uniqueOpeners | 52 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 98 | | matches | | 0 | "Of course he didn't." | | 1 | "Instead he inclined his head," | | 2 | "Somewhere down the street a" |
| | ratio | 0.031 | |
| 11.84% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 51 | | totalSentences | 98 | | matches | | 0 | "She froze with her thumb" | | 1 | "She didn't get many visitors." | | 2 | "She had made sure of" | | 3 | "She pulled her trousers back" | | 4 | "Her stomach dropped through the" | | 5 | "She had learned that lesson" | | 6 | "she said, and her voice" | | 7 | "he agreed, in that accented" | | 8 | "He didn't flinch." | | 9 | "He had the kind of" | | 10 | "He lifted a bottle from" | | 11 | "She stared at it." | | 12 | "She stared at him." | | 13 | "She felt, with the precision" | | 14 | "She gripped the edge of" | | 15 | "He said it simply, the" | | 16 | "She should have closed the" | | 17 | "She knew that." | | 18 | "She had a whole list" | | 19 | "She had rehearsed them in" |
| | ratio | 0.52 | |
| 87.55% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 98 | | matches | | 0 | "The knock came at quarter" | | 1 | "Rory was halfway out of" | | 2 | "She froze with her thumb" | | 3 | "She didn't get many visitors." | | 4 | "She had made sure of" | | 5 | "The knocks didn't come again." | | 6 | "She pulled her trousers back" | | 7 | "The hallway beyond was dim," | | 8 | "Her stomach dropped through the" | | 9 | "Lucien Moreau leaned on his" | | 10 | "Rory set her jaw." | | 11 | "She had learned that lesson" | | 12 | "Several of them, in fact." | | 13 | "she said, and her voice" | | 14 | "he agreed, in that accented" | | 15 | "He didn't flinch." | | 16 | "He had the kind of" | | 17 | "He lifted a bottle from" | | 18 | "A red, expensive, the kind" | | 19 | "She stared at it." |
| | ratio | 0.745 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 98 | | matches | | 0 | "Whoever it was, they were" | | 1 | "As though he always had." | | 2 | "Now he was here, and" |
| | ratio | 0.031 | |
| 51.28% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 5 | | matches | | 0 | "Rory was halfway out of her work clothes, one leg still in her trousers, when she heard it — three measured raps against the wood of her door, the sound of a ma…" | | 1 | "Lucien Moreau leaned on his ivory-handled cane like it was the most natural thing in the world to be standing outside her door at eleven-fifteen on a Tuesday, h…" | | 2 | "Instead he inclined his head, just a fraction, and she watched the light from her flat catch the sharp line of his jaw, the pale column of his throat where his …" | | 3 | "Replaced by the sight of him — the way the light caught the silver at his temples, the way his gloved hand rested on the head of his cane, the way he held himse…" | | 4 | "His mouth curved, the smallest fraction, and there it was — the thing that had undone her the first time, the thing she had tried to outrun in two different fla…" |
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| 93.75% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 36 | | tagDensity | 0.306 | | leniency | 0.611 | | rawRatio | 0.091 | | effectiveRatio | 0.056 | |