| 60.47% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 3 | | adverbTags | | 0 | "Quinn said quietly [quietly]" | | 1 | "Eva said softly [softly]" | | 2 | "Quinn said quietly [quietly]" |
| | dialogueSentences | 43 | | tagDensity | 0.442 | | leniency | 0.884 | | rawRatio | 0.158 | | effectiveRatio | 0.14 | |
| 84.66% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1630 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "carefully" | | 1 | "sharply" | | 2 | "softly" | | 3 | "perfectly" | | 4 | "gently" |
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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) | |
| 75.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1630 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "measured" | | 1 | "flicker" | | 2 | "scanning" | | 3 | "pristine" | | 4 | "etched" | | 5 | "trembled" | | 6 | "flickered" |
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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 | 144 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 144 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 168 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1630 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 24 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 70 | | wordCount | 1342 | | uniqueNames | 18 | | maxNameDensity | 2.09 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 28 | | Metropolitan | 1 | | Police | 1 | | Tube | 1 | | Camden | 3 | | Veil | 3 | | Market | 1 | | Morris | 3 | | Shoreditch | 1 | | Kowalski | 2 | | Jor | 1 | | Eva | 18 | | Shade | 1 | | London | 1 | | Compass | 2 | | British | 1 | | Museum | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Morris" | | 4 | "Kowalski" | | 5 | "Eva" | | 6 | "Compass" | | 7 | "Museum" |
| | places | | 0 | "Shoreditch" | | 1 | "London" | | 2 | "British" |
| | globalScore | 0.457 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 93 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.613 | | wordCount | 1630 | | matches | | 0 | "not at the body but at the wall behind it" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 168 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 26.29 | | std | 21.02 | | cv | 0.8 | | sampleLengths | | 0 | 95 | | 1 | 66 | | 2 | 33 | | 3 | 33 | | 4 | 5 | | 5 | 64 | | 6 | 12 | | 7 | 79 | | 8 | 11 | | 9 | 33 | | 10 | 9 | | 11 | 47 | | 12 | 5 | | 13 | 7 | | 14 | 5 | | 15 | 19 | | 16 | 41 | | 17 | 8 | | 18 | 19 | | 19 | 53 | | 20 | 8 | | 21 | 5 | | 22 | 5 | | 23 | 51 | | 24 | 19 | | 25 | 31 | | 26 | 45 | | 27 | 39 | | 28 | 28 | | 29 | 15 | | 30 | 37 | | 31 | 8 | | 32 | 6 | | 33 | 22 | | 34 | 59 | | 35 | 59 | | 36 | 24 | | 37 | 8 | | 38 | 14 | | 39 | 54 | | 40 | 15 | | 41 | 15 | | 42 | 58 | | 43 | 7 | | 44 | 11 | | 45 | 2 | | 46 | 7 | | 47 | 40 | | 48 | 29 | | 49 | 9 |
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| 95.52% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 144 | | matches | | 0 | "been bricked" | | 1 | "been pulled" | | 2 | "was laid" | | 3 | "were unrumpled" | | 4 | "was gone" |
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| 20.63% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 223 | | matches | | 0 | "were guarding" | | 1 | "was tucking" | | 2 | "was forming" | | 3 | "was already dropping" | | 4 | "was cooling" | | 5 | "was coming" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 168 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1345 | | adjectiveStacks | 1 | | stackExamples | | 0 | "lay untouched beside him." |
| | adverbCount | 37 | | adverbRatio | 0.0275092936802974 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.011895910780669145 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 168 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 168 | | mean | 9.7 | | std | 7.17 | | cv | 0.739 | | sampleLengths | | 0 | 28 | | 1 | 6 | | 2 | 25 | | 3 | 36 | | 4 | 26 | | 5 | 1 | | 6 | 3 | | 7 | 8 | | 8 | 28 | | 9 | 12 | | 10 | 15 | | 11 | 6 | | 12 | 14 | | 13 | 19 | | 14 | 5 | | 15 | 5 | | 16 | 18 | | 17 | 22 | | 18 | 19 | | 19 | 9 | | 20 | 3 | | 21 | 4 | | 22 | 35 | | 23 | 17 | | 24 | 10 | | 25 | 6 | | 26 | 2 | | 27 | 5 | | 28 | 8 | | 29 | 3 | | 30 | 8 | | 31 | 5 | | 32 | 20 | | 33 | 3 | | 34 | 6 | | 35 | 6 | | 36 | 7 | | 37 | 5 | | 38 | 6 | | 39 | 3 | | 40 | 20 | | 41 | 5 | | 42 | 3 | | 43 | 4 | | 44 | 2 | | 45 | 3 | | 46 | 19 | | 47 | 5 | | 48 | 25 | | 49 | 5 |
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| 37.72% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 22 | | diversityRatio | 0.30538922155688625 | | totalSentences | 167 | | uniqueOpeners | 51 | |
| 54.20% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 123 | | matches | | 0 | "Somewhere in the arches, a" | | 1 | "Then she reached into her" |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 123 | | matches | | 0 | "Her worn leather watch on" | | 1 | "She knew that because DS" | | 2 | "She had traded a week's" | | 3 | "It had felt obscene to" | | 4 | "She was tucking hair behind" | | 5 | "She surveyed the space with" | | 6 | "Her green eyes were tired." | | 7 | "She stepped past Eva, crouching" | | 8 | "His hands were empty, palms" | | 9 | "Hers would be the second." | | 10 | "She gestured to the man's" | | 11 | "She had seen one of" | | 12 | "She had dismissed it as" | | 13 | "She turned to the wall." | | 14 | "He had walked himself to" | | 15 | "She remembered Morris's last night." | | 16 | "She remembered finding a brass" | | 17 | "She'd logged it as evidence" | | 18 | "She took out her phone," | | 19 | "She took a sample of" |
| | ratio | 0.268 | |
| 45.37% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 102 | | totalSentences | 123 | | matches | | 0 | "Detective Harlow Quinn descended the" | | 1 | "The air down here was" | | 2 | "The abandoned Tube station beneath" | | 3 | "Her worn leather watch on" | | 4 | "The Veil Market moved locations" | | 5 | "She knew that because DS" | | 6 | "The bone token in her" | | 7 | "She had traded a week's" | | 8 | "It had felt obscene to" | | 9 | "Eva Kowalski was already there." | | 10 | "Quinn felt her jaw tighten." | | 11 | "Eva Kowalski, five-four in boots," | | 12 | "The worn leather satchel full" | | 13 | "She was tucking hair behind" | | 14 | "Eva said, not looking up" | | 15 | "Quinn didn't answer immediately." | | 16 | "She surveyed the space with" | | 17 | "Dealer by all accounts, known" | | 18 | "Neck broken at an unnatural" | | 19 | "Eva said, finally meeting her" |
| | ratio | 0.829 | |
| 40.65% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 123 | | matches | | 0 | "As if something had pulled" |
| | ratio | 0.008 | |
| 66.87% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 47 | | technicalSentenceCount | 5 | | matches | | 0 | "Detective Harlow Quinn descended the last flight of concrete steps with the kind of measured tread that had kept her alive for eighteen years on the Metropolita…" | | 1 | "She surveyed the space with military precision, taking in the stalls of black glass and bone, the hanging jars of pickled things, the stallholders standing in a…" | | 2 | "The skin around his throat was pale, almost translucent, with faint dark bruising in a pattern that wasn't human fingers." | | 3 | "She thought about the clique she had been building a case on for months, the art dealers and antiquarians and one junior archivist at the British Museum's restr…" | | 4 | "She was a woman who believed in evidence, in footprints and fibers and ballistics." |
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| 46.05% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 3 | | matches | | 0 | "Eva said, not looking up from the body" | | 1 | "Quinn said, more to herself than Eva" | | 2 | "Quinn said, not accusing, stating" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 18 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 43 | | tagDensity | 0.419 | | leniency | 0.837 | | rawRatio | 0 | | effectiveRatio | 0 | |