| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.38% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1383 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 85.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1383 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "structure" | | 1 | "could feel" | | 2 | "flicked" | | 3 | "footsteps" |
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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 | 108 | | matches | | |
| 89.95% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 0 | | narrationSentences | 108 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 108 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1392 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1387 | | uniqueNames | 15 | | maxNameDensity | 0.94 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | Harlow | 1 | | Quinn | 13 | | Mornington | 1 | | Crescent | 1 | | Herrera | 7 | | Delancey | 1 | | Street | 1 | | Tube | 2 | | Town | 1 | | Victorian | 1 | | Morris | 3 | | Bermondsey | 1 | | Christopher | 1 | | Three | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Morris" | | 4 | "Christopher" |
| | places | | 0 | "Camden" | | 1 | "Mornington" | | 2 | "Crescent" | | 3 | "Delancey" | | 4 | "Street" | | 5 | "Town" | | 6 | "Victorian" | | 7 | "Bermondsey" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | 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 | 1392 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 108 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 48 | | std | 35.9 | | cv | 0.748 | | sampleLengths | | 0 | 50 | | 1 | 85 | | 2 | 68 | | 3 | 43 | | 4 | 95 | | 5 | 9 | | 6 | 77 | | 7 | 28 | | 8 | 26 | | 9 | 78 | | 10 | 94 | | 11 | 7 | | 12 | 103 | | 13 | 5 | | 14 | 15 | | 15 | 70 | | 16 | 40 | | 17 | 68 | | 18 | 25 | | 19 | 12 | | 20 | 148 | | 21 | 11 | | 22 | 57 | | 23 | 67 | | 24 | 16 | | 25 | 55 | | 26 | 4 | | 27 | 12 | | 28 | 24 |
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| 98.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 108 | | matches | | 0 | "was gone" | | 1 | "been permitted" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 237 | | matches | | 0 | "was going" | | 1 | "was handing" | | 2 | "was turning" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 108 | | ratio | 0.074 | | matches | | 0 | "Her watch — worn leather, water-darkened now — said 11:47." | | 1 | "Camden Town's forgotten sibling — closed in the seventies, sealed, bricked, forgotten by everyone except the taggers who'd found it and the city workers who hadn't bothered to chase them off." | | 2 | "You didn't follow a suspect into an unknown structure at midnight, alone, without backup, without a warrant, without so much as a working radio — hers had drowned an hour ago in the same gutter that had taken her umbrella." | | 3 | "The people he met, the packages he moved, the patients he treated in flats with the curtains drawn — none of it fit a pattern she could name." | | 4 | "Inside, the old station went down farther than a Tube station should — steps that spiraled rather than descended straight, tiled walls green with mold, a smell that was wet stone and something else, something faintly sweet and turned." | | 5 | "A low murmur of them, many, the sound of a crowd in a place a crowd had no business being — and beneath the voices, a kind of music, thin and reedy, like a flute played badly and proudly." | | 6 | "There were things on those tables she could not identify and things she did not want to, jars of fluid with shapes suspended in them, bundles of dried herbs bound with black thread, coins and cards and teeth — teeth, small pale teeth, laid out in rows like a currency." | | 7 | "Her fingers closed on the thing she'd picked up off the alley floor twenty minutes ago, the small pale thing Herrera had dropped and not noticed, which she had stepped on and stopped and bent down and taken without knowing why — a knucklebone, drilled through, strung on a cord." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1386 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 40 | | adverbRatio | 0.02886002886002886 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.005050505050505051 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 108 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 108 | | mean | 12.89 | | std | 11.64 | | cv | 0.903 | | sampleLengths | | 0 | 14 | | 1 | 24 | | 2 | 8 | | 3 | 4 | | 4 | 2 | | 5 | 1 | | 6 | 4 | | 7 | 19 | | 8 | 30 | | 9 | 15 | | 10 | 14 | | 11 | 3 | | 12 | 15 | | 13 | 20 | | 14 | 16 | | 15 | 7 | | 16 | 7 | | 17 | 10 | | 18 | 9 | | 19 | 2 | | 20 | 5 | | 21 | 17 | | 22 | 28 | | 23 | 11 | | 24 | 14 | | 25 | 27 | | 26 | 5 | | 27 | 1 | | 28 | 9 | | 29 | 9 | | 30 | 25 | | 31 | 4 | | 32 | 31 | | 33 | 17 | | 34 | 3 | | 35 | 25 | | 36 | 5 | | 37 | 5 | | 38 | 16 | | 39 | 5 | | 40 | 21 | | 41 | 4 | | 42 | 8 | | 43 | 40 | | 44 | 8 | | 45 | 3 | | 46 | 14 | | 47 | 28 | | 48 | 4 | | 49 | 5 |
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| 52.16% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.37962962962962965 | | totalSentences | 108 | | uniqueOpeners | 41 | |
| 33.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 99 | | matches | | | ratio | 0.01 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 99 | | matches | | 0 | "It came down in sheets" | | 1 | "She'd lost her umbrella somewhere" | | 2 | "She hadn't lost him." | | 3 | "She'd been on him since" | | 4 | "He was fast." | | 5 | "He cut left down a" | | 6 | "It hid the sound of" | | 7 | "Her watch — worn leather," | | 8 | "She'd noted the time when" | | 9 | "She had the advantage he" | | 10 | "He'd straightened up after that." | | 11 | "He walked like a man" | | 12 | "He went through a gap" | | 13 | "She put one hand on" | | 14 | "You didn't follow a suspect" | | 15 | "It fit a shape." | | 16 | "She could feel the shape." | | 17 | "It was there in the" | | 18 | "She thought about him then," | | 19 | "They'd told her the scene" |
| | ratio | 0.333 | |
| 81.21% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 99 | | matches | | 0 | "The rain had been falling" | | 1 | "It came down in sheets" | | 2 | "She'd lost her umbrella somewhere" | | 3 | "She hadn't lost him." | | 4 | "She'd been on him since" | | 5 | "Quinn had watched from across" | | 6 | "He was fast." | | 7 | "He cut left down a" | | 8 | "Quinn went over the pallets" | | 9 | "The rain filled the alley" | | 10 | "It hid the sound of" | | 11 | "Her watch — worn leather," | | 12 | "She'd noted the time when" | | 13 | "Morris had taught her that." | | 14 | "Morris had taught her a" | | 15 | "The alley spilled onto a" | | 16 | "Herrera was already at the" | | 17 | "Quinn closed the distance, coat" | | 18 | "She had the advantage he" | | 19 | "He'd straightened up after that." |
| | ratio | 0.758 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 99 | | matches | | 0 | "Because they hadn't seen her." | | 1 | "Because none of them had" |
| | ratio | 0.02 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 2 | | matches | | 0 | "You didn't follow a suspect into an unknown structure at midnight, alone, without backup, without a warrant, without so much as a working radio — hers had drown…" | | 1 | "Inside, the old station went down farther than a Tube station should — steps that spiraled rather than descended straight, tiled walls green with mold, a smell …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |