| 96.55% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 3 | | adverbTags | | 0 | "A young constable stood stiffly [stiffly]" | | 1 | "She turned back [back]" | | 2 | "Jenkins said softly [softly]" |
| | dialogueSentences | 58 | | tagDensity | 0.345 | | leniency | 0.69 | | rawRatio | 0.15 | | effectiveRatio | 0.103 | |
| 77.25% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1099 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "very" | | 1 | "slightly" | | 2 | "quickly" | | 3 | "softly" |
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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) | |
| 72.70% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1099 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "etched" | | 1 | "intricate" | | 2 | "traced" |
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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 | 96 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 96 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 132 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1091 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 52.47% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 769 | | uniqueNames | 11 | | maxNameDensity | 1.95 | | worstName | "Jenkins" | | maxWindowNameDensity | 3 | | worstWindowName | "Jenkins" | | discoveredNames | | Harlow | 11 | | Quinn | 1 | | Camden | 1 | | Town | 1 | | Art | 1 | | Deco | 1 | | Morris | 3 | | Jenkins | 15 | | Abandoned | 1 | | Said | 1 | | Holloway | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Art" | | 3 | "Deco" | | 4 | "Morris" | | 5 | "Jenkins" | | 6 | "Said" |
| | places | | 0 | "Camden" | | 1 | "Town" | | 2 | "Abandoned" |
| | globalScore | 0.525 | | windowScore | 0.667 | |
| 68.03% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 2 | | matches | | 0 | "quite conquer" | | 1 | "looked like a stylised eye with a vertica" |
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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 | 1091 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 132 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 57 | | mean | 19.14 | | std | 15.17 | | cv | 0.792 | | sampleLengths | | 0 | 12 | | 1 | 61 | | 2 | 25 | | 3 | 17 | | 4 | 17 | | 5 | 45 | | 6 | 28 | | 7 | 47 | | 8 | 30 | | 9 | 5 | | 10 | 4 | | 11 | 17 | | 12 | 47 | | 13 | 1 | | 14 | 14 | | 15 | 14 | | 16 | 5 | | 17 | 28 | | 18 | 3 | | 19 | 20 | | 20 | 4 | | 21 | 7 | | 22 | 33 | | 23 | 6 | | 24 | 33 | | 25 | 38 | | 26 | 11 | | 27 | 22 | | 28 | 11 | | 29 | 38 | | 30 | 8 | | 31 | 1 | | 32 | 24 | | 33 | 56 | | 34 | 15 | | 35 | 3 | | 36 | 2 | | 37 | 15 | | 38 | 33 | | 39 | 4 | | 40 | 20 | | 41 | 15 | | 42 | 13 | | 43 | 52 | | 44 | 4 | | 45 | 8 | | 46 | 35 | | 47 | 13 | | 48 | 16 | | 49 | 29 |
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| 94.30% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 96 | | matches | | 0 | "been laid" | | 1 | "was composed" | | 2 | "was etched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 136 | | matches | (empty) | |
| 77.92% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 132 | | ratio | 0.023 | | matches | | 0 | "She remembered Morris doing the same thing—setting up a scene like a stage play for her to walk into." | | 1 | "A leather satchel lay beside him, open, its contents—a few notebooks, a brass compass, some bone tokens—spilled onto the gravel." | | 2 | "Within it, intricate symbols spiraled inward—not spray paint, not chalk." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 623 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 10 | | adverbRatio | 0.016051364365971106 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0032102728731942215 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 132 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 132 | | mean | 8.27 | | std | 5.53 | | cv | 0.669 | | sampleLengths | | 0 | 12 | | 1 | 28 | | 2 | 19 | | 3 | 14 | | 4 | 17 | | 5 | 8 | | 6 | 15 | | 7 | 2 | | 8 | 7 | | 9 | 10 | | 10 | 7 | | 11 | 4 | | 12 | 19 | | 13 | 8 | | 14 | 7 | | 15 | 13 | | 16 | 5 | | 17 | 10 | | 18 | 13 | | 19 | 5 | | 20 | 14 | | 21 | 3 | | 22 | 2 | | 23 | 10 | | 24 | 15 | | 25 | 15 | | 26 | 5 | | 27 | 4 | | 28 | 10 | | 29 | 7 | | 30 | 6 | | 31 | 12 | | 32 | 3 | | 33 | 6 | | 34 | 20 | | 35 | 1 | | 36 | 6 | | 37 | 8 | | 38 | 12 | | 39 | 2 | | 40 | 5 | | 41 | 13 | | 42 | 5 | | 43 | 2 | | 44 | 4 | | 45 | 4 | | 46 | 3 | | 47 | 11 | | 48 | 2 | | 49 | 2 |
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| 88.38% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.553030303030303 | | totalSentences | 132 | | uniqueOpeners | 73 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 96.19% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 84 | | matches | | 0 | "Their torches swept over Art" | | 1 | "She remembered Morris doing the" | | 2 | "She followed the trail through" | | 3 | "She stopped at the edge." | | 4 | "He looked up at her" | | 5 | "He stood, brushing grime from" | | 6 | "His face was composed, almost" | | 7 | "She moved closer, her own" | | 8 | "She crouched, ignoring the crunch" | | 9 | "She shone her light along" | | 10 | "She straightened, her beam catching" | | 11 | "She moved toward it." | | 12 | "It was a circle, about" | | 13 | "They looked burned into the" | | 14 | "She nudged the open satchel" | | 15 | "Its face was etched with" | | 16 | "She’d seen one like it" | | 17 | "she said, pointing at the" | | 18 | "He leaned down to collect" | | 19 | "It spun wildly for a" |
| | ratio | 0.31 | |
| 25.48% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 84 | | matches | | 0 | "Heels clicked against ceramic tiles" | | 1 | "Detective Harlow Quinn ducked under" | | 2 | "The usual crew of forensic" | | 3 | "Their torches swept over Art" | | 4 | "A young constable stood stiffly" | | 5 | "Harlow’s eyes tracked the glow-stick" | | 6 | "The constable cleared his throat" | | 7 | "Harlow gave the boy a" | | 8 | "Jenkins liked his theatrics." | | 9 | "She remembered Morris doing the" | | 10 | "The memory was a fist" | | 11 | "She followed the trail through" | | 12 | "The air grew colder, damper." | | 13 | "A smell like wet stone" | | 14 | "The platform stretched away into" | | 15 | "She stopped at the edge." | | 16 | "A chalk outline." | | 17 | "A single forensic photographer circling" | | 18 | "He looked up at her" | | 19 | "He stood, brushing grime from" |
| | ratio | 0.869 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 66.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 3 | | matches | | 0 | "Heels clicked against ceramic tiles that glowed with their own faint light." | | 1 | "The usual crew of forensic techs in white coveralls milled about a lobby that hadn't seen commuters in decades." | | 2 | "And Jenkins, squatting on his haunches, peering at something in the dirt between the rails." |
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| 50.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 3 | | matches | | 0 | "She straightened, her beam catching something else" | | 1 | "Jenkins said, his voice tight" | | 2 | "Harlow stood, her mind clicking through facts" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 58 | | tagDensity | 0.069 | | leniency | 0.138 | | rawRatio | 0 | | effectiveRatio | 0 | |