| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "the way she'd once [once]" |
| | dialogueSentences | 52 | | tagDensity | 0.308 | | leniency | 0.615 | | rawRatio | 0.063 | | effectiveRatio | 0.038 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1309 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 77.08% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1309 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "traced" | | 1 | "weight" | | 2 | "silence" | | 3 | "perfect" | | 4 | "churned" | | 5 | "quivered" |
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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 | 92 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 92 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 128 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 51 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1309 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 869 | | uniqueNames | 9 | | maxNameDensity | 1.27 | | worstName | "Brennan" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Brennan" | | discoveredNames | | Quinn | 10 | | Adeyemi | 4 | | Vale | 1 | | Underground | 1 | | Brennan | 11 | | Clean | 1 | | Four | 1 | | Deptford | 1 | | Morris | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Adeyemi" | | 2 | "Vale" | | 3 | "Underground" | | 4 | "Brennan" | | 5 | "Morris" |
| | places | | | globalScore | 0.867 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | glossingSentenceCount | 1 | | matches | | 0 | "register and, apparently, whoever had strung" |
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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 | 1309 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 128 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 63 | | mean | 20.78 | | std | 18.64 | | cv | 0.897 | | sampleLengths | | 0 | 45 | | 1 | 9 | | 2 | 43 | | 3 | 36 | | 4 | 28 | | 5 | 3 | | 6 | 8 | | 7 | 33 | | 8 | 11 | | 9 | 1 | | 10 | 49 | | 11 | 26 | | 12 | 3 | | 13 | 9 | | 14 | 1 | | 15 | 32 | | 16 | 1 | | 17 | 35 | | 18 | 1 | | 19 | 11 | | 20 | 3 | | 21 | 46 | | 22 | 2 | | 23 | 1 | | 24 | 29 | | 25 | 26 | | 26 | 4 | | 27 | 1 | | 28 | 76 | | 29 | 7 | | 30 | 45 | | 31 | 14 | | 32 | 3 | | 33 | 3 | | 34 | 32 | | 35 | 17 | | 36 | 16 | | 37 | 24 | | 38 | 11 | | 39 | 73 | | 40 | 7 | | 41 | 46 | | 42 | 13 | | 43 | 46 | | 44 | 36 | | 45 | 13 | | 46 | 2 | | 47 | 32 | | 48 | 20 | | 49 | 9 |
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| 97.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 92 | | matches | | 0 | "been taken" | | 1 | "been taught" |
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| 58.16% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 141 | | matches | | 0 | "was taking" | | 1 | "was already walking" | | 2 | "was jutting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 128 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 878 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.03302961275626424 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.00683371298405467 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 128 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 128 | | mean | 10.23 | | std | 9.44 | | cv | 0.923 | | sampleLengths | | 0 | 24 | | 1 | 2 | | 2 | 2 | | 3 | 17 | | 4 | 9 | | 5 | 25 | | 6 | 5 | | 7 | 13 | | 8 | 8 | | 9 | 28 | | 10 | 2 | | 11 | 8 | | 12 | 18 | | 13 | 3 | | 14 | 8 | | 15 | 24 | | 16 | 9 | | 17 | 5 | | 18 | 6 | | 19 | 1 | | 20 | 20 | | 21 | 29 | | 22 | 10 | | 23 | 8 | | 24 | 2 | | 25 | 6 | | 26 | 3 | | 27 | 9 | | 28 | 1 | | 29 | 20 | | 30 | 12 | | 31 | 1 | | 32 | 13 | | 33 | 15 | | 34 | 7 | | 35 | 1 | | 36 | 11 | | 37 | 3 | | 38 | 29 | | 39 | 5 | | 40 | 7 | | 41 | 2 | | 42 | 2 | | 43 | 1 | | 44 | 2 | | 45 | 1 | | 46 | 4 | | 47 | 13 | | 48 | 1 | | 49 | 1 |
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| 90.10% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.578125 | | totalSentences | 128 | | uniqueOpeners | 74 | |
| 45.66% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 73 | | matches | | 0 | "Somewhere far off, water ticked" |
| | ratio | 0.014 | |
| 93.97% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 73 | | matches | | 0 | "She corrected herself as she" | | 1 | "He didn't look up" | | 2 | "He gestured up with two" | | 3 | "She squatted where the head" | | 4 | "She traced the drop with" | | 5 | "She angled the beam up" | | 6 | "She turned the beam down" | | 7 | "She reached out and touched" | | 8 | "She stood and turned, sweeping" | | 9 | "She pointed at the pool" | | 10 | "She looked up" | | 11 | "She was already walking, torch" | | 12 | "They came out of the" | | 13 | "They didn't turn round." | | 14 | "They didn't go back." | | 15 | "They simply stopped, as though" | | 16 | "He didn't answer." | | 17 | "He crouched by the prints" | | 18 | "He'd seen it, then." | | 19 | "It was scorched." |
| | ratio | 0.315 | |
| 42.19% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 73 | | matches | | 0 | "The tarpaulin over the escalator" | | 1 | "Something older, mineral, the way" | | 2 | "Constable Adeyemi held the torch" | | 3 | "Quinn took the steps anyway." | | 4 | "The abandoned station opened below" | | 5 | "Camden Vale, decommissioned in 1954," | | 6 | "She corrected herself as she" | | 7 | "Tallow stubs in jam jars," | | 8 | "Brennan only wore the camel-hair" | | 9 | "He didn't look up" | | 10 | "He gestured up with two" | | 11 | "Quinn walked around the body" | | 12 | "Brennan straightened up and his" | | 13 | "She squatted where the head" | | 14 | "The blood had gone tacky" | | 15 | "Quinn looked up." | | 16 | "The ventilation shaft was there," | | 17 | "Rust flaked from the hinge." | | 18 | "She traced the drop with" | | 19 | "Adeyemi passed it over." |
| | ratio | 0.836 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 93.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 2 | | matches | | 0 | "DI Brennan was already there, crouched on his heels in his good coat, which told her everything about how seriously he was taking it." | | 1 | "A compass, the size of a pocket watch, its face scratched over with small sharp marks that were not letters in any alphabet she'd been taught." |
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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 | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 52 | | tagDensity | 0.077 | | leniency | 0.154 | | rawRatio | 0 | | effectiveRatio | 0 | |