| 73.02% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 4 | | adverbTags | | 0 | "Her voice echoed oddly [oddly]" | | 1 | "She stood again [again]" | | 2 | "She crouched again [again]" | | 3 | "Eva said quietly [quietly]" |
| | dialogueSentences | 63 | | tagDensity | 0.349 | | leniency | 0.698 | | rawRatio | 0.182 | | effectiveRatio | 0.127 | |
| 87.19% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1561 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "carefully" | | 1 | "completely" | | 2 | "slowly" |
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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) | |
| 67.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1561 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "silence" | | 1 | "echoed" | | 2 | "familiar" | | 3 | "scanning" | | 4 | "etched" | | 5 | "intricate" | | 6 | "magnetic" | | 7 | "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 | 119 | | matches | (empty) | |
| 94.84% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 1 | | narrationSentences | 119 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 159 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1553 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1017 | | uniqueNames | 6 | | maxNameDensity | 1.08 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 11 | | London | 1 | | Davies | 9 | | Eva | 5 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Davies" | | 3 | "Eva" | | 4 | "Morris" |
| | places | | | globalScore | 0.959 | | windowScore | 0.833 | |
| 48.65% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | glossingSentenceCount | 3 | | matches | | 0 | "quite make out" | | 1 | "quite make out" | | 2 | "seemed completely absorbed in the book spread before her" |
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| 71.22% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.288 | | wordCount | 1553 | | matches | | 0 | "Not the natural darkness of an abandoned station, but something thicker" | | 1 | "Not by electricity, but by something else" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 159 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 61 | | mean | 25.46 | | std | 19.64 | | cv | 0.771 | | sampleLengths | | 0 | 26 | | 1 | 55 | | 2 | 1 | | 3 | 6 | | 4 | 28 | | 5 | 42 | | 6 | 3 | | 7 | 57 | | 8 | 37 | | 9 | 4 | | 10 | 43 | | 11 | 61 | | 12 | 56 | | 13 | 4 | | 14 | 25 | | 15 | 49 | | 16 | 1 | | 17 | 15 | | 18 | 26 | | 19 | 8 | | 20 | 6 | | 21 | 36 | | 22 | 34 | | 23 | 12 | | 24 | 34 | | 25 | 30 | | 26 | 5 | | 27 | 1 | | 28 | 39 | | 29 | 5 | | 30 | 46 | | 31 | 4 | | 32 | 63 | | 33 | 6 | | 34 | 29 | | 35 | 37 | | 36 | 9 | | 37 | 2 | | 38 | 1 | | 39 | 3 | | 40 | 39 | | 41 | 55 | | 42 | 41 | | 43 | 50 | | 44 | 21 | | 45 | 11 | | 46 | 36 | | 47 | 52 | | 48 | 6 | | 49 | 29 |
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| 93.47% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 119 | | matches | | 0 | "been decommissioned" | | 1 | "was etched" | | 2 | "was lit" | | 3 | "were lined" |
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| 40.32% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 167 | | matches | | 0 | "was starting" | | 1 | "wasn't pointing" | | 2 | "was playing" | | 3 | "was pointing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 159 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1023 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.03616813294232649 | | lyAdverbCount | 17 | | lyAdverbRatio | 0.016617790811339198 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 159 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 159 | | mean | 9.77 | | std | 7.23 | | cv | 0.741 | | sampleLengths | | 0 | 10 | | 1 | 11 | | 2 | 5 | | 3 | 17 | | 4 | 12 | | 5 | 3 | | 6 | 3 | | 7 | 20 | | 8 | 1 | | 9 | 3 | | 10 | 3 | | 11 | 18 | | 12 | 10 | | 13 | 15 | | 14 | 20 | | 15 | 7 | | 16 | 3 | | 17 | 12 | | 18 | 7 | | 19 | 38 | | 20 | 4 | | 21 | 7 | | 22 | 4 | | 23 | 3 | | 24 | 3 | | 25 | 16 | | 26 | 4 | | 27 | 32 | | 28 | 11 | | 29 | 5 | | 30 | 11 | | 31 | 22 | | 32 | 23 | | 33 | 16 | | 34 | 9 | | 35 | 11 | | 36 | 5 | | 37 | 4 | | 38 | 5 | | 39 | 2 | | 40 | 2 | | 41 | 2 | | 42 | 4 | | 43 | 13 | | 44 | 12 | | 45 | 10 | | 46 | 11 | | 47 | 13 | | 48 | 15 | | 49 | 1 |
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| 65.83% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.42138364779874216 | | totalSentences | 159 | | uniqueOpeners | 67 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 107 | | matches | | 0 | "Just the wet rasp of" | | 1 | "Officially, it didn't exist." | | 2 | "Just the stale, damp air" | | 3 | "Somewhere in the darkness beyond" |
| | ratio | 0.037 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 107 | | matches | | 0 | "She didn't turn." | | 1 | "Her voice echoed oddly off" | | 2 | "He gestured toward the far" | | 3 | "He handed her a tablet" | | 4 | "She walked toward the officers," | | 5 | "His suit probably cost more" | | 6 | "His watch was silver, elegant," | | 7 | "She looked up at Davies." | | 8 | "She moved toward the nearest" | | 9 | "She crouched again." | | 10 | "It wasn't pointing north." | | 11 | "She didn't recognise them, but" | | 12 | "She turned the compass over" | | 13 | "She stood again, walking toward" | | 14 | "She crouched again, running her" | | 15 | "She walked toward the sound," | | 16 | "She drew her weapon and" | | 17 | "She pushed it open and" | | 18 | "She wore round glasses and" | | 19 | "Her voice was calm, almost" |
| | ratio | 0.243 | |
| 67.48% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 107 | | matches | | 0 | "The body lay where the" | | 1 | "Something that seemed to breathe." | | 2 | "Detective Harlow Quinn crouched at" | | 3 | "The silence down here pressed" | | 4 | "She didn't turn." | | 5 | "Davies could wait." | | 6 | "Her voice echoed oddly off" | | 7 | "Davies appeared at her shoulder," | | 8 | "He gestured toward the far" | | 9 | "He handed her a tablet" | | 10 | "The incident report glowed on" | | 11 | "Quinn studied the report." | | 12 | "The station had been decommissioned" | | 13 | "Nothing but a line on" | | 14 | "Davies's voice carried the particular" | | 15 | "Quinn stood, her knees protesting." | | 16 | "The ache in her lower" | | 17 | "She walked toward the officers," | | 18 | "The body belonged to a" | | 19 | "His suit probably cost more" |
| | ratio | 0.785 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 107 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 2 | | matches | | 0 | "Just the wet rasp of her own breathing and, somewhere further in, the faint murmur of voices that shouldn't exist." | | 1 | "She walked toward the officers, her sharp jaw set in a line that had intimidate seasoned criminals and frustrated superintendents in equal measure." |
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| 34.09% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 4 | | matches | | 0 | "Davies appeared, his flashlight beam cutting through the dark" | | 1 | "A young constable stepped, eager to show initiative" | | 2 | "Quinn stood, her eyes scanning the platform" | | 3 | "the woman said, as if that explained everything" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 63 | | tagDensity | 0.079 | | leniency | 0.159 | | rawRatio | 0.2 | | effectiveRatio | 0.032 | |