| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 2 | | adverbTags | | 0 | "he said quietly [quietly]" | | 1 | "she said slowly [slowly]" |
| | dialogueSentences | 54 | | tagDensity | 0.352 | | leniency | 0.704 | | rawRatio | 0.105 | | effectiveRatio | 0.074 | |
| 87.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1638 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "suddenly" | | 3 | "very" |
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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) | |
| 75.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1638 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "scanning" | | 1 | "streaming" | | 2 | "weight" | | 3 | "measured" | | 4 | "calculating" | | 5 | "flickered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 131 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 131 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 166 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1638 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 48 | | wordCount | 1212 | | uniqueNames | 13 | | maxNameDensity | 2.06 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | London | 1 | | Harlow | 1 | | Quinn | 25 | | Brewer | 1 | | Street | 2 | | Lexington | 1 | | Victorian | 1 | | Spanish | 2 | | Received | 1 | | Pronunciation | 1 | | Morris | 3 | | Tomás | 8 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Spanish" | | 3 | "Morris" | | 4 | "Tomás" | | 5 | "Market" |
| | places | | 0 | "London" | | 1 | "Brewer" | | 2 | "Street" | | 3 | "Lexington" | | 4 | "Received" |
| | globalScore | 0.469 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 85 | | glossingSentenceCount | 1 | | matches | | 0 | "ere all along, apparently" |
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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 | 1638 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 166 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 71 | | mean | 23.07 | | std | 16.53 | | cv | 0.716 | | sampleLengths | | 0 | 26 | | 1 | 67 | | 2 | 55 | | 3 | 51 | | 4 | 42 | | 5 | 13 | | 6 | 42 | | 7 | 11 | | 8 | 51 | | 9 | 54 | | 10 | 33 | | 11 | 19 | | 12 | 12 | | 13 | 47 | | 14 | 22 | | 15 | 17 | | 16 | 13 | | 17 | 1 | | 18 | 19 | | 19 | 5 | | 20 | 28 | | 21 | 42 | | 22 | 51 | | 23 | 7 | | 24 | 37 | | 25 | 4 | | 26 | 19 | | 27 | 3 | | 28 | 9 | | 29 | 18 | | 30 | 2 | | 31 | 25 | | 32 | 19 | | 33 | 20 | | 34 | 2 | | 35 | 35 | | 36 | 10 | | 37 | 39 | | 38 | 13 | | 39 | 2 | | 40 | 54 | | 41 | 13 | | 42 | 5 | | 43 | 43 | | 44 | 43 | | 45 | 33 | | 46 | 21 | | 47 | 19 | | 48 | 15 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 131 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 215 | | matches | | 0 | "was running" | | 1 | "was stopping" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 166 | | ratio | 0.012 | | matches | | 0 | "One advertised TEETH - ALL SORTS." | | 1 | "Another promised HONEST ANSWERS - ALWAYS." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1212 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 41 | | adverbRatio | 0.03382838283828383 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.006600660066006601 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 166 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 166 | | mean | 9.87 | | std | 7.16 | | cv | 0.725 | | sampleLengths | | 0 | 7 | | 1 | 19 | | 2 | 25 | | 3 | 9 | | 4 | 5 | | 5 | 10 | | 6 | 6 | | 7 | 12 | | 8 | 8 | | 9 | 14 | | 10 | 18 | | 11 | 8 | | 12 | 4 | | 13 | 3 | | 14 | 22 | | 15 | 16 | | 16 | 13 | | 17 | 2 | | 18 | 5 | | 19 | 12 | | 20 | 19 | | 21 | 4 | | 22 | 13 | | 23 | 9 | | 24 | 20 | | 25 | 3 | | 26 | 10 | | 27 | 5 | | 28 | 6 | | 29 | 11 | | 30 | 5 | | 31 | 25 | | 32 | 1 | | 33 | 1 | | 34 | 8 | | 35 | 10 | | 36 | 9 | | 37 | 11 | | 38 | 24 | | 39 | 10 | | 40 | 6 | | 41 | 6 | | 42 | 11 | | 43 | 12 | | 44 | 4 | | 45 | 3 | | 46 | 12 | | 47 | 21 | | 48 | 12 | | 49 | 14 |
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| 55.62% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.37349397590361444 | | totalSentences | 166 | | uniqueOpeners | 62 | |
| 54.20% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 123 | | matches | | 0 | "Somewhere in the crowd, a" | | 1 | "Just darkness, and a figure" |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 123 | | matches | | 0 | "She rounded the corner onto" | | 1 | "His crime was running." | | 2 | "Her watch read 2:47 AM." | | 3 | "She descended, water streaming from" | | 4 | "Her wet coat became a" | | 5 | "She pushed it open and" | | 6 | "He hadn't looked back." | | 7 | "He belonged here." | | 8 | "She took two steps forward," | | 9 | "He was her age, maybe" | | 10 | "His accent was foreign, something" | | 11 | "He said it without inflection" | | 12 | "He glanced past her, toward" | | 13 | "He passed it over and" | | 14 | "She thought of DS Morris." | | 15 | "They'd shown her things in" | | 16 | "She'd never stopped looking." | | 17 | "He said it like an" | | 18 | "She pulled her badge back" | | 19 | "He looked at the suspect," |
| | ratio | 0.26 | |
| 16.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 109 | | totalSentences | 123 | | matches | | 0 | "The rain hammered London like" | | 1 | "Detective Harlow Quinn ran through" | | 2 | "The suspect had bolted from" | | 3 | "Quinn had been tailing him" | | 4 | "The man moved like he" | | 5 | "Quinn liked that in a" | | 6 | "Mistakes were easier to find" | | 7 | "She rounded the corner onto" | | 8 | "The coat, fifty meters ahead," | | 9 | "Quinn's hand went to her" | | 10 | "The man's hands had been" | | 11 | "His crime was running." | | 12 | "That was enough." | | 13 | "The gap between the buildings" | | 14 | "Rain sheeted down the brick" | | 15 | "The suspect's coat disappeared down" | | 16 | "Her watch read 2:47 AM." | | 17 | "The steps led to a" | | 18 | "A current of warmer air" | | 19 | "Something chemical and sweet." |
| | ratio | 0.886 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 123 | | matches | (empty) | | ratio | 0 | |
| 99.13% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 3 | | matches | | 0 | "He was her age, maybe older, with a face like weathered leather and dark eyes that measured her without apparent interest." | | 1 | "A case that had started simple and ended in a hospital room, Morris staring at the ceiling, his eyes seeing something that wasn't there." | | 2 | "Something that had left him catatonic and retired on medical grounds." |
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| 72.37% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn showed, her hand steady despite everything" | | 1 | "The keeper smiled, and the expression made Quinn's skin prickle" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 54 | | tagDensity | 0.148 | | leniency | 0.296 | | rawRatio | 0 | | effectiveRatio | 0 | |