| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 28 | | adverbTagCount | 2 | | adverbTags | | 0 | "earth had ever [ever]" | | 1 | "she said instead [instead]" |
| | dialogueSentences | 61 | | tagDensity | 0.459 | | leniency | 0.918 | | rawRatio | 0.071 | | effectiveRatio | 0.066 | |
| 84.87% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1652 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slowly" | | 1 | "precisely" | | 2 | "very" | | 3 | "gently" |
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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) | |
| 96.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1652 | | totalAiIsms | 1 | | found | | | highlights | | |
| 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 | 79 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 79 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 111 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 64 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 6 | | totalWords | 1670 | | ratio | 0.004 | | matches | | 0 | "Aur" | | 1 | "fringe" | | 2 | "Fiancé." | | 3 | "home" | | 4 | "secret room" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 27 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 55 | | wordCount | 1135 | | uniqueNames | 15 | | maxNameDensity | 1.59 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Beth" | | discoveredNames | | Silas | 3 | | Prague | 1 | | Cairo | 1 | | Baltic | 1 | | Rory | 1 | | Aurora | 18 | | Welsh | 1 | | Vaughan | 3 | | Beth | 18 | | Bethan | 3 | | Marlboros | 1 | | Cardiff | 1 | | Woodville | 1 | | Northern | 1 | | Megabus | 1 |
| | persons | | 0 | "Silas" | | 1 | "Rory" | | 2 | "Aurora" | | 3 | "Vaughan" | | 4 | "Beth" |
| | places | | 0 | "Prague" | | 1 | "Cairo" | | 2 | "Cardiff" |
| | globalScore | 0.707 | | windowScore | 0.5 | |
| 57.41% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | glossingSentenceCount | 2 | | matches | | 0 | "seemed important to get it right" | | 1 | "vening wanted, apparently, and she was tired" |
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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 | 1670 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 111 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 55 | | mean | 30.36 | | std | 32.2 | | cv | 1.06 | | sampleLengths | | 0 | 62 | | 1 | 23 | | 2 | 77 | | 3 | 29 | | 4 | 56 | | 5 | 14 | | 6 | 36 | | 7 | 144 | | 8 | 3 | | 9 | 3 | | 10 | 59 | | 11 | 14 | | 12 | 16 | | 13 | 11 | | 14 | 17 | | 15 | 55 | | 16 | 4 | | 17 | 71 | | 18 | 67 | | 19 | 6 | | 20 | 3 | | 21 | 5 | | 22 | 21 | | 23 | 98 | | 24 | 45 | | 25 | 6 | | 26 | 18 | | 27 | 9 | | 28 | 66 | | 29 | 3 | | 30 | 2 | | 31 | 16 | | 32 | 13 | | 33 | 27 | | 34 | 24 | | 35 | 2 | | 36 | 6 | | 37 | 3 | | 38 | 92 | | 39 | 18 | | 40 | 61 | | 41 | 11 | | 42 | 1 | | 43 | 70 | | 44 | 23 | | 45 | 2 | | 46 | 4 | | 47 | 11 | | 48 | 119 | | 49 | 22 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 79 | | matches | | |
| 86.36% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 176 | | matches | | 0 | "was polishing" | | 1 | "was wearing" | | 2 | "wasn't stopping" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 2 | | flaggedSentences | 6 | | totalSentences | 111 | | ratio | 0.054 | | matches | | 0 | "Behind him, the mirror was crowded with bottles and, above those, the maps — Prague in 1961, Cairo, a hand-inked chart of the Baltic with someone's pencil arcs still on it." | | 1 | "Aurora had known Bethan Vaughan through four different colours of hair — the pillar-box red, the green that had turned pond-scum in chlorine, the bleach that broke off in the sink, the blue-black that had run down her neck in the rain like something from a crime scene." | | 2 | "The hug was wrong in the way that hugs between people who used to sleep top-to-tail in a single bed are wrong after seven years — too careful, too much air between the ribs." | | 3 | "The small crescent scar there, white as a fingernail clipping, from going through her grandmother's greenhouse at the age of nine — Beth had been there for that too, had run for the adults, had been sick in the hydrangeas afterwards." | | 4 | "She thought about all the things she could say: that she hadn't been ringing to be rescued, only to hear a voice she'd known since she was six; that she'd got out anyway, on her own, on a Megabus with a rucksack and one shoe wet through; that she was proud of it in a way she couldn't ever explain to her father." | | 5 | "Behind her, Bethan Vaughan made a sound Aurora hadn't heard in seven years — a short delighted bark, entirely too loud for the room." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 549 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.023679417122040074 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.007285974499089253 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 111 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 111 | | mean | 15.05 | | std | 14.28 | | cv | 0.949 | | sampleLengths | | 0 | 29 | | 1 | 33 | | 2 | 4 | | 3 | 19 | | 4 | 20 | | 5 | 31 | | 6 | 19 | | 7 | 7 | | 8 | 29 | | 9 | 2 | | 10 | 4 | | 11 | 50 | | 12 | 14 | | 13 | 15 | | 14 | 21 | | 15 | 28 | | 16 | 4 | | 17 | 48 | | 18 | 4 | | 19 | 20 | | 20 | 9 | | 21 | 31 | | 22 | 3 | | 23 | 3 | | 24 | 34 | | 25 | 7 | | 26 | 18 | | 27 | 14 | | 28 | 5 | | 29 | 7 | | 30 | 4 | | 31 | 7 | | 32 | 4 | | 33 | 3 | | 34 | 14 | | 35 | 11 | | 36 | 38 | | 37 | 6 | | 38 | 4 | | 39 | 54 | | 40 | 17 | | 41 | 26 | | 42 | 6 | | 43 | 35 | | 44 | 6 | | 45 | 3 | | 46 | 5 | | 47 | 12 | | 48 | 9 | | 49 | 32 |
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| 65.77% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.43243243243243246 | | totalSentences | 111 | | uniqueOpeners | 48 | |
| 99.50% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 67 | | matches | | 0 | "Then it stopped, and she" | | 1 | "Just a shape you carried." |
| | ratio | 0.03 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 67 | | matches | | 0 | "She put a foot on" | | 1 | "She turned around slowly, the" | | 2 | "she gestured, a small neat" | | 3 | "It was the hair." | | 4 | "She was wearing a coat" | | 5 | "She used to smell of" | | 6 | "She glanced up" | | 7 | "His signet ring caught the" | | 8 | "He went back to the" | | 9 | "she searched, and settled on" | | 10 | "It was nothing." | | 11 | "It was a quarter of" | | 12 | "She heard herself add, hating" | | 13 | "She said it gently, which" | | 14 | "She pressed her lips together" | | 15 | "Her voice came out strange" | | 16 | "She thought about all the" | | 17 | "She said none of it." | | 18 | "she said instead, and stood" | | 19 | "She led Beth past the" |
| | ratio | 0.299 | |
| 49.55% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 67 | | matches | | 0 | "Rain had followed her in" | | 1 | "Aurora set the insulated bag" | | 2 | "Silas didn't look up from" | | 3 | "The green neon out front" | | 4 | "She put a foot on" | | 5 | "*Aur*, with the Welsh burr" | | 6 | "She turned around slowly, the" | | 7 | "Bethan Vaughan said" | | 8 | "she gestured, a small neat" | | 9 | "The strangest part wasn't Beth's" | | 10 | "It was the hair." | | 11 | "Aurora had known Bethan Vaughan" | | 12 | "This hair was brown." | | 13 | "She was wearing a coat" | | 14 | "The hug was wrong in" | | 15 | "Beth smelled of something clean" | | 16 | "She used to smell of" | | 17 | "Aurora slid into the booth." | | 18 | "The bench let out its" | | 19 | "A beat, precisely measured" |
| | ratio | 0.821 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 67 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 7 | | matches | | 0 | "The strangest part wasn't Beth's face, which was the same face, the wide mouth and the crooked incisor and the eyebrows that had always done their own commentar…" | | 1 | "Aurora had known Bethan Vaughan through four different colours of hair — the pillar-box red, the green that had turned pond-scum in chlorine, the bleach that br…" | | 2 | "Mid-brown, cut in a way that had cost money, tucked behind one ear with a plain gold stud in it." | | 3 | "On the table in front of her sat a tall glass of soda water with a wheel of lime in it and a plate that had held, at some point, olives." | | 4 | "The hug was wrong in the way that hugs between people who used to sleep top-to-tail in a single bed are wrong after seven years — too careful, too much air betw…" | | 5 | "That she was twenty-five and delivering wonton soup to men in dressing gowns and it was, on most days, the best thing that had ever happened to her." | | 6 | "That she had forgiven Beth in about 2019, quietly, without telling her, which was possibly the cruellest thing she'd ever done to anybody." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 28 | | uselessAdditionCount | 1 | | matches | | 0 | "Beth laughed, and the laugh was the old one, too loud for the room, and for a second the whole seven years folded up like a map and it was Beth in the corner of the Woodville with her boots on the table telling three rugby players to grow up" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 2 | | fancyTags | | 0 | "Beth laughed (laugh)" | | 1 | "She heard (hear)" |
| | dialogueSentences | 61 | | tagDensity | 0.246 | | leniency | 0.492 | | rawRatio | 0.133 | | effectiveRatio | 0.066 | |