| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn said quietly [quietly]" |
| | dialogueSentences | 40 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.063 | | effectiveRatio | 0.05 | |
| 84.19% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1581 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "precisely" | | 1 | "very" | | 2 | "lazily" |
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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) | |
| 93.67% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1581 | | totalAiIsms | 2 | | 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 | 0 | | narrationSentences | 122 | | matches | (empty) | |
| 96.02% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 1 | | narrationSentences | 122 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 146 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1581 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 56 | | wordCount | 1179 | | uniqueNames | 20 | | maxNameDensity | 1.19 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Eva" | | discoveredNames | | Northern | 2 | | Line | 2 | | Harlow | 1 | | Quinn | 14 | | Camden | 2 | | Transport | 1 | | London | 1 | | Eva | 13 | | Kowalski | 1 | | Freya | 8 | | Eliphas | 1 | | Levi | 1 | | Underground | 1 | | Three | 1 | | Morris | 1 | | Woolwich | 2 | | Tube | 1 | | Thames | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Eva" | | 3 | "Kowalski" | | 4 | "Freya" | | 5 | "Eliphas" | | 6 | "Levi" | | 7 | "Morris" |
| | places | | 0 | "London" | | 1 | "Three" | | 2 | "Woolwich" | | 3 | "Thames" | | 4 | "Veil" |
| | globalScore | 0.906 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 69 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like bone dust compressed and glaz" |
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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 | 1581 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 146 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 25.5 | | std | 21.29 | | cv | 0.835 | | sampleLengths | | 0 | 30 | | 1 | 37 | | 2 | 51 | | 3 | 12 | | 4 | 14 | | 5 | 46 | | 6 | 31 | | 7 | 42 | | 8 | 3 | | 9 | 92 | | 10 | 35 | | 11 | 1 | | 12 | 16 | | 13 | 49 | | 14 | 7 | | 15 | 18 | | 16 | 5 | | 17 | 13 | | 18 | 73 | | 19 | 22 | | 20 | 3 | | 21 | 11 | | 22 | 21 | | 23 | 5 | | 24 | 57 | | 25 | 11 | | 26 | 18 | | 27 | 2 | | 28 | 32 | | 29 | 28 | | 30 | 31 | | 31 | 24 | | 32 | 25 | | 33 | 20 | | 34 | 9 | | 35 | 11 | | 36 | 62 | | 37 | 41 | | 38 | 10 | | 39 | 5 | | 40 | 84 | | 41 | 38 | | 42 | 6 | | 43 | 13 | | 44 | 2 | | 45 | 4 | | 46 | 69 | | 47 | 4 | | 48 | 21 | | 49 | 9 |
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| 90.88% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 122 | | matches | | 0 | "were folded" | | 1 | "were frosted" | | 2 | "was etched" | | 3 | "been replaced" | | 4 | "being pulled" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 193 | | matches | | 0 | "was picking" | | 1 | "were looking" | | 2 | "was digging" | | 3 | "was weeping" | | 4 | "was tucking" | | 5 | "was hammering" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 146 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 365 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 7 | | adverbRatio | 0.019178082191780823 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 146 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 146 | | mean | 10.83 | | std | 9.62 | | cv | 0.889 | | sampleLengths | | 0 | 30 | | 1 | 10 | | 2 | 27 | | 3 | 5 | | 4 | 6 | | 5 | 2 | | 6 | 2 | | 7 | 25 | | 8 | 11 | | 9 | 12 | | 10 | 14 | | 11 | 6 | | 12 | 7 | | 13 | 14 | | 14 | 1 | | 15 | 4 | | 16 | 14 | | 17 | 31 | | 18 | 9 | | 19 | 2 | | 20 | 3 | | 21 | 6 | | 22 | 9 | | 23 | 13 | | 24 | 3 | | 25 | 2 | | 26 | 13 | | 27 | 11 | | 28 | 7 | | 29 | 3 | | 30 | 13 | | 31 | 16 | | 32 | 27 | | 33 | 5 | | 34 | 30 | | 35 | 1 | | 36 | 16 | | 37 | 3 | | 38 | 38 | | 39 | 8 | | 40 | 7 | | 41 | 8 | | 42 | 10 | | 43 | 5 | | 44 | 13 | | 45 | 27 | | 46 | 27 | | 47 | 19 | | 48 | 22 | | 49 | 3 |
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| 54.94% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.3793103448275862 | | totalSentences | 145 | | uniqueOpeners | 55 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 100 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 100 | | matches | | 0 | "She ducked under the tape." | | 1 | "Her boots found the dead" | | 2 | "She pulled her notebook from" | | 3 | "Her left wrist, always." | | 4 | "She checked it as a" | | 5 | "Her closely cropped salt-and-pepper hair" | | 6 | "She felt the cold settling" | | 7 | "She had eighteen years of" | | 8 | "Her worn leather satchel, full" | | 9 | "She saw the body and" | | 10 | "Her green eyes went very" | | 11 | "She glanced up, freckled complexion" | | 12 | "She looked at Quinn." | | 13 | "She knelt again, close enough" | | 14 | "She leaned in." | | 15 | "They were frosted." | | 16 | "She was digging in her" | | 17 | "She held it over the" | | 18 | "It didn't waver." | | 19 | "It pointed, trembling violently, like" |
| | ratio | 0.3 | |
| 80.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 76 | | totalSentences | 100 | | matches | | 0 | "The call had come in" | | 1 | "She ducked under the tape." | | 2 | "The air down here was" | | 3 | "Her boots found the dead" | | 4 | "The station sign still read" | | 5 | "Freya from forensics gave her" | | 6 | "She pulled her notebook from" | | 7 | "The worn leather strap of" | | 8 | "Her left wrist, always." | | 9 | "She checked it as a" | | 10 | "The body lay in the" | | 11 | "Her closely cropped salt-and-pepper hair" | | 12 | "She felt the cold settling" | | 13 | "The tiles around the body" | | 14 | "The cut was deep enough" | | 15 | "There should have been arterial" | | 16 | "Freya said behind her" | | 17 | "Quinn didn't answer." | | 18 | "She had eighteen years of" | | 19 | "People who killed for kicks" |
| | ratio | 0.76 | |
| 50.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 100 | | matches | | 0 | "As if something very cold" |
| | ratio | 0.01 | |
| 17.86% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 7 | | matches | | 0 | "Freya from forensics gave her a nod that didn't reach her eyes." | | 1 | "She had eighteen years of decorated service and it had taught her that people who killed for money didn't carry bodies down two flights of service stairs and th…" | | 2 | "Five-four in a second-hand wool coat that was too big for her, curly red hair escaping from under a beanie, round glasses fogging instantly in the cold." | | 3 | "The entry requirement she'd read about in Eva's annotated copy of Eliphas Levi, the copy that had gotten Eva banned from bringing her own books into the restric…" | | 4 | "As if something very cold had stood directly over him for a very long time." | | 5 | "She was digging in her satchel, pulling out layers of notebooks and plastic-sleeved papers until she found what she wanted." | | 6 | "The casing had a patina of verdigris that made it look ancient, but the glass was clear." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 2 | | fancyTags | | 0 | "Eva whispered (whisper)" | | 1 | "Eva breathed (breathe)" |
| | dialogueSentences | 40 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0.167 | | effectiveRatio | 0.1 | |