| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 1 | | adverbTags | | 0 | "Davies had already [already]" |
| | dialogueSentences | 33 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0.083 | | effectiveRatio | 0.061 | |
| 88.22% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 849 | | totalAiIsmAdverbs | 2 | | 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) | |
| 52.89% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 849 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "processed" | | 1 | "weight" | | 2 | "chill" | | 3 | "footsteps" | | 4 | "echoing" | | 5 | "silence" | | 6 | "etched" |
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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 | 1 | | narrationSentences | 69 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 69 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 91 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 846 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 69.09% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 618 | | uniqueNames | 12 | | maxNameDensity | 1.62 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 10 | | Quinn | 2 | | Forty-one | 1 | | London | 3 | | Camden | 2 | | Town | 1 | | Victorian | 1 | | Morris | 2 | | Cornwall | 1 | | High | 1 | | Street | 1 | | Davies | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Victorian" | | 3 | "Morris" | | 4 | "Davies" |
| | places | | 0 | "London" | | 1 | "Camden" | | 2 | "Town" | | 3 | "Cornwall" | | 4 | "High" | | 5 | "Street" |
| | globalScore | 0.691 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 846 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 91 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 36 | | mean | 23.5 | | std | 17.61 | | cv | 0.749 | | sampleLengths | | 0 | 30 | | 1 | 35 | | 2 | 28 | | 3 | 34 | | 4 | 35 | | 5 | 8 | | 6 | 24 | | 7 | 41 | | 8 | 20 | | 9 | 2 | | 10 | 64 | | 11 | 5 | | 12 | 40 | | 13 | 16 | | 14 | 4 | | 15 | 3 | | 16 | 5 | | 17 | 1 | | 18 | 2 | | 19 | 31 | | 20 | 31 | | 21 | 28 | | 22 | 20 | | 23 | 5 | | 24 | 9 | | 25 | 39 | | 26 | 3 | | 27 | 46 | | 28 | 70 | | 29 | 27 | | 30 | 34 | | 31 | 4 | | 32 | 35 | | 33 | 22 | | 34 | 40 | | 35 | 5 |
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| 95.09% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 69 | | matches | | 0 | "were curled" | | 1 | "been found" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 110 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 91 | | ratio | 0.011 | | matches | | 0 | "And Harlow Quinn had learned, over eighteen years, to trust that feeling in her gut—the one that had kept her alive when other detectives had ended up like Morris." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 296 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 11 | | adverbRatio | 0.037162162162162164 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.013513513513513514 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 91 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 91 | | mean | 9.3 | | std | 6.6 | | cv | 0.71 | | sampleLengths | | 0 | 15 | | 1 | 15 | | 2 | 20 | | 3 | 15 | | 4 | 11 | | 5 | 15 | | 6 | 1 | | 7 | 1 | | 8 | 8 | | 9 | 26 | | 10 | 3 | | 11 | 8 | | 12 | 7 | | 13 | 12 | | 14 | 3 | | 15 | 2 | | 16 | 8 | | 17 | 11 | | 18 | 13 | | 19 | 10 | | 20 | 20 | | 21 | 11 | | 22 | 4 | | 23 | 8 | | 24 | 2 | | 25 | 6 | | 26 | 2 | | 27 | 12 | | 28 | 9 | | 29 | 11 | | 30 | 12 | | 31 | 13 | | 32 | 7 | | 33 | 5 | | 34 | 26 | | 35 | 10 | | 36 | 4 | | 37 | 16 | | 38 | 4 | | 39 | 3 | | 40 | 5 | | 41 | 1 | | 42 | 2 | | 43 | 6 | | 44 | 15 | | 45 | 2 | | 46 | 4 | | 47 | 4 | | 48 | 7 | | 49 | 5 |
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| 94.51% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.6043956043956044 | | totalSentences | 91 | | uniqueOpeners | 55 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 62 | | matches | | 0 | "Her hands were curled at" | | 1 | "She stopped at the edge" | | 2 | "He left to make the" | | 3 | "It looked almost ceremonial." | | 4 | "She crouched again, examining the" | | 5 | "She checked the coat pockets" | | 6 | "She held it up to" | | 7 | "She'd seen the file." | | 8 | "Her partner had been investigating" | | 9 | "She walked toward the tunnel" | | 10 | "It pointed deeper into the" | | 11 | "She descended into the dark." |
| | ratio | 0.194 | |
| 80.97% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 62 | | matches | | 0 | "The body lay arranged on" | | 1 | "Detective Harlow Quinn crouched beside" | | 2 | "Davies had already processed the" | | 3 | "Harlow noted the absence before" | | 4 | "The victim's dark hair fanned" | | 5 | "Davies consulted his notebook" | | 6 | "Harlow leaned closer." | | 7 | "The woman had been young," | | 8 | "Her hands were curled at" | | 9 | "Davies shifted his weight" | | 10 | "Harlow stood, her joints protesting" | | 11 | "The victim wore trainers." | | 12 | "Harlow walked the perimeter, her" | | 13 | "The station was Camden Town," | | 14 | "Graffiti artists had tagged the" | | 15 | "Someone had tried to burn" | | 16 | "She stopped at the edge" | | 17 | "The tunnel stretched into darkness," | | 18 | "He left to make the" | | 19 | "Harlow returned to the body," |
| | ratio | 0.758 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 3 | | matches | | 0 | "Davies had already, his gloved hand hovering above the victim's head" | | 1 | "Harlow stood, her joints protesting the cold" | | 2 | "Harlow walked, her footsteps echoing in the hollow space" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 33 | | tagDensity | 0.03 | | leniency | 0.061 | | rawRatio | 1 | | effectiveRatio | 0.061 | |