| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 86 | | tagDensity | 0.105 | | leniency | 0.209 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.59% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2075 | | 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) | |
| 83.13% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2075 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "comfortable" | | 1 | "pulse" | | 2 | "glint" | | 3 | "etched" | | 4 | "trembled" | | 5 | "flickered" | | 6 | "perfect" |
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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 | 0 | | narrationSentences | 171 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 171 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 248 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 4 | | totalWords | 2072 | | ratio | 0.002 | | matches | | 0 | "LOWER CAMDEN" | | 1 | "LOWER CAMDEN." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 61.89% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 53 | | wordCount | 1589 | | uniqueNames | 5 | | maxNameDensity | 1.76 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 28 | | Tube | 1 | | Sergeant | 1 | | Bell | 22 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Bell" |
| | places | (empty) | | globalScore | 0.619 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 118 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed smaller than the wound should have made it" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 0.965 | | wordCount | 2072 | | matches | | 0 | "no footprints but" | | 1 | "not by fire but by absence: a patch" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 248 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 132 | | mean | 15.7 | | std | 17.98 | | cv | 1.145 | | sampleLengths | | 0 | 16 | | 1 | 9 | | 2 | 59 | | 3 | 52 | | 4 | 5 | | 5 | 66 | | 6 | 4 | | 7 | 4 | | 8 | 22 | | 9 | 67 | | 10 | 3 | | 11 | 5 | | 12 | 6 | | 13 | 4 | | 14 | 11 | | 15 | 4 | | 16 | 51 | | 17 | 3 | | 18 | 20 | | 19 | 6 | | 20 | 6 | | 21 | 5 | | 22 | 1 | | 23 | 47 | | 24 | 4 | | 25 | 27 | | 26 | 7 | | 27 | 4 | | 28 | 4 | | 29 | 6 | | 30 | 56 | | 31 | 27 | | 32 | 5 | | 33 | 5 | | 34 | 7 | | 35 | 5 | | 36 | 8 | | 37 | 6 | | 38 | 5 | | 39 | 54 | | 40 | 39 | | 41 | 4 | | 42 | 3 | | 43 | 6 | | 44 | 4 | | 45 | 3 | | 46 | 9 | | 47 | 2 | | 48 | 10 | | 49 | 36 |
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| 86.80% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 9 | | totalSentences | 171 | | matches | | 0 | "been closed" | | 1 | "been walled" | | 2 | "been drawn" | | 3 | "were blackened" | | 4 | "was mottled" | | 5 | "was blackened" | | 6 | "been stabbed" | | 7 | "been caught" | | 8 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 255 | | matches | | 0 | "was not lying" | | 1 | "was looking" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 248 | | ratio | 0.012 | | matches | | 0 | "Whoever had drawn it had done so after the dust settled—or before the station filled with people." | | 1 | "In the brief dimness, Quinn heard a sound from the rails—a deep, distant clatter, like a train approaching through miles of tunnel." | | 2 | "The bloodless wound was the seam where the crossing had taken him—or where something had taken its price." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1595 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.02006269592476489 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.003134796238244514 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 248 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 248 | | mean | 8.35 | | std | 6.1 | | cv | 0.73 | | sampleLengths | | 0 | 16 | | 1 | 9 | | 2 | 22 | | 3 | 11 | | 4 | 26 | | 5 | 8 | | 6 | 21 | | 7 | 8 | | 8 | 15 | | 9 | 5 | | 10 | 23 | | 11 | 14 | | 12 | 29 | | 13 | 4 | | 14 | 4 | | 15 | 4 | | 16 | 11 | | 17 | 7 | | 18 | 6 | | 19 | 16 | | 20 | 10 | | 21 | 6 | | 22 | 3 | | 23 | 5 | | 24 | 21 | | 25 | 3 | | 26 | 4 | | 27 | 1 | | 28 | 6 | | 29 | 4 | | 30 | 11 | | 31 | 4 | | 32 | 5 | | 33 | 10 | | 34 | 6 | | 35 | 7 | | 36 | 23 | | 37 | 3 | | 38 | 20 | | 39 | 6 | | 40 | 2 | | 41 | 4 | | 42 | 5 | | 43 | 1 | | 44 | 4 | | 45 | 10 | | 46 | 4 | | 47 | 17 | | 48 | 8 | | 49 | 4 |
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| 43.55% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.29838709677419356 | | totalSentences | 248 | | uniqueOpeners | 74 | |
| 21.23% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 157 | | matches | | | ratio | 0.006 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 157 | | matches | | 0 | "She crouched beside the body" | | 1 | "He had the comfortable look" | | 2 | "He wore it like a" | | 3 | "She looked back at the" | | 4 | "His coat was expensive but" | | 5 | "His hands lay open beside" | | 6 | "She studied it through the" | | 7 | "She checked the worn leather" | | 8 | "She had been awake since" | | 9 | "Her closely cropped hair prickled" | | 10 | "She buttoned her coat." | | 11 | "They followed the platform to" | | 12 | "Its padlock hung from one" | | 13 | "They began halfway up the" | | 14 | "He straightened, frowning." | | 15 | "She had heard that complaint" | | 16 | "She had made a career" | | 17 | "She returned to the body." | | 18 | "She looked at the man’s" | | 19 | "His trousers, too." |
| | ratio | 0.255 | |
| 45.99% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 130 | | totalSentences | 157 | | matches | | 0 | "The station had been closed" | | 1 | "Detective Harlow Quinn found it" | | 2 | "She crouched beside the body" | | 3 | "Dust silvered the man’s coat" | | 4 | "The ticket protruding from it" | | 5 | "A string of work lights" | | 6 | "Someone had chalked a circle" | | 7 | "The line was too neat" | | 8 | "Sergeant Bell stood over a" | | 9 | "He had the comfortable look" | | 10 | "Quinn glanced at him." | | 11 | "Bell was young enough to" | | 12 | "He wore it like a" | | 13 | "She looked back at the" | | 14 | "The dead man was in" | | 15 | "His coat was expensive but" | | 16 | "His hands lay open beside" | | 17 | "A dark stain spread over" | | 18 | "Bell followed her gaze." | | 19 | "Quinn held out her hand." |
| | ratio | 0.828 | |
| 31.85% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 157 | | matches | | 0 | "Whoever had drawn it had" |
| | ratio | 0.006 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 66 | | technicalSentenceCount | 3 | | matches | | 0 | "The ticket protruding from it was clean, cream-colored, printed with a destination that had not existed on any Tube map Quinn had ever seen: **LOWER CAMDEN**." | | 1 | "She had heard that complaint before, from colleagues who preferred the clean, easy story." | | 2 | "Yet dust coated the backs of his hands and the shoulders of his coat, as if he had lain in the station for hours." |
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| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 1 | | matches | | 0 | "Bell said, his certainty finally giving way to unease" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 86 | | tagDensity | 0.081 | | leniency | 0.163 | | rawRatio | 0 | | effectiveRatio | 0 | |