| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said slowly [slowly]" |
| | dialogueSentences | 51 | | tagDensity | 0.098 | | leniency | 0.196 | | rawRatio | 0.2 | | effectiveRatio | 0.039 | |
| 91.69% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1203 | | 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) | |
| 41.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1203 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "gloom" | | 1 | "silence" | | 2 | "stomach" | | 3 | "flickered" | | 4 | "velvet" | | 5 | "silk" | | 6 | "pulse" | | 7 | "flicked" | | 8 | "raced" | | 9 | "wavered" | | 10 | "glinting" |
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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 | 108 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 108 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 154 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 7 | | totalWords | 1190 | | ratio | 0.006 | | matches | | 0 | "murder" | | 1 | "wrong" | | 2 | "is" | | 3 | "what" | | 4 | "Information—Price Negotiable" | | 5 | "sucked" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 823 | | uniqueNames | 10 | | maxNameDensity | 1.94 | | worstName | "Cole" | | maxWindowNameDensity | 5 | | worstWindowName | "Eva" | | discoveredNames | | Tube | 1 | | Quinn | 14 | | Camden | 1 | | Town | 1 | | London | 1 | | Sergeant | 1 | | Cole | 16 | | Price | 1 | | Eva | 12 | | Morris | 2 |
| | persons | | 0 | "Quinn" | | 1 | "Sergeant" | | 2 | "Cole" | | 3 | "Eva" | | 4 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "Town" | | 2 | "London" |
| | globalScore | 0.528 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like human teeth on a velvet cushi" |
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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 | 1190 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 154 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 19.19 | | std | 13.96 | | cv | 0.727 | | sampleLengths | | 0 | 57 | | 1 | 29 | | 2 | 53 | | 3 | 25 | | 4 | 33 | | 5 | 25 | | 6 | 35 | | 7 | 2 | | 8 | 21 | | 9 | 21 | | 10 | 17 | | 11 | 37 | | 12 | 34 | | 13 | 5 | | 14 | 28 | | 15 | 6 | | 16 | 54 | | 17 | 7 | | 18 | 6 | | 19 | 35 | | 20 | 9 | | 21 | 13 | | 22 | 12 | | 23 | 6 | | 24 | 33 | | 25 | 8 | | 26 | 54 | | 27 | 2 | | 28 | 6 | | 29 | 11 | | 30 | 9 | | 31 | 28 | | 32 | 8 | | 33 | 46 | | 34 | 9 | | 35 | 17 | | 36 | 11 | | 37 | 11 | | 38 | 13 | | 39 | 6 | | 40 | 32 | | 41 | 12 | | 42 | 15 | | 43 | 6 | | 44 | 30 | | 45 | 7 | | 46 | 11 | | 47 | 14 | | 48 | 33 | | 49 | 10 |
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| 98.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 108 | | matches | | 0 | "were painted" | | 1 | "being followed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 149 | | matches | (empty) | |
| 31.54% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 154 | | ratio | 0.039 | | matches | | 0 | "Now, it was just another forgotten pocket of London—except for the body." | | 1 | "The usual detritus of an abandoned station littered the ground—discarded takeout containers, a broken umbrella, a single scuffed loafer." | | 2 | "Brass, tarnished with age, its needle spinning lazily before settling on a direction that made no sense—pointing straight at the wall." | | 3 | "But as she ran her fingers along the surface, she felt it—a seam." | | 4 | "A third had a sign that read *Information—Price Negotiable*." | | 5 | "The way the body had looked—like something had *sucked* the life out of him." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 830 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.02289156626506024 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.006024096385542169 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 154 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 154 | | mean | 7.73 | | std | 5.6 | | cv | 0.725 | | sampleLengths | | 0 | 10 | | 1 | 14 | | 2 | 21 | | 3 | 12 | | 4 | 12 | | 5 | 17 | | 6 | 18 | | 7 | 16 | | 8 | 12 | | 9 | 3 | | 10 | 2 | | 11 | 1 | | 12 | 1 | | 13 | 13 | | 14 | 12 | | 15 | 7 | | 16 | 9 | | 17 | 8 | | 18 | 1 | | 19 | 5 | | 20 | 3 | | 21 | 25 | | 22 | 8 | | 23 | 19 | | 24 | 4 | | 25 | 4 | | 26 | 2 | | 27 | 5 | | 28 | 16 | | 29 | 5 | | 30 | 16 | | 31 | 2 | | 32 | 15 | | 33 | 29 | | 34 | 8 | | 35 | 11 | | 36 | 2 | | 37 | 21 | | 38 | 3 | | 39 | 2 | | 40 | 8 | | 41 | 9 | | 42 | 5 | | 43 | 6 | | 44 | 2 | | 45 | 4 | | 46 | 3 | | 47 | 13 | | 48 | 13 | | 49 | 13 |
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| 56.06% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.36363636363636365 | | totalSentences | 154 | | uniqueOpeners | 56 | |
| 35.84% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 93 | | matches | | 0 | "Instead, she turned her attention" |
| | ratio | 0.011 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 93 | | matches | | 0 | "His tie was loose, sleeves" | | 1 | "She adjusted the worn leather" | | 2 | "His eyes were open, glassy," | | 3 | "She knelt, brushing her fingers" | | 4 | "She stood, sweeping the beam" | | 5 | "She stepped closer to the" | | 6 | "She crouched again, nudging it" | | 7 | "She slipped it into an" | | 8 | "She shook off the sensation." | | 9 | "She didn’t answer." | | 10 | "It was just concrete, cracked" | | 11 | "she said slowly" | | 12 | "He stepped forward, squinting." | | 13 | "She pressed her palm against" | | 14 | "He hesitated, then keyed the" | | 15 | "She shoved harder." | | 16 | "She shook him off." | | 17 | "They set the vial down" | | 18 | "She adjusted her round glasses," | | 19 | "She turned back to Eva." |
| | ratio | 0.29 | |
| 8.39% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 93 | | matches | | 0 | "The abandoned Tube station reeked" | | 1 | "Harlow Quinn stepped over the" | | 2 | "The beam of her torch" | | 3 | "Detective Sergeant Cole waved her" | | 4 | "His tie was loose, sleeves" | | 5 | "She adjusted the worn leather" | | 6 | "The victim lay sprawled across" | | 7 | "Cole crouched beside the body," | | 8 | "Quinn’s torch flickered over the" | | 9 | "His eyes were open, glassy," | | 10 | "She knelt, brushing her fingers" | | 11 | "Rigor had already set in." | | 12 | "She stood, sweeping the beam" | | 13 | "The usual detritus of an" | | 14 | "Nothing out of place." | | 15 | "Nothing that screamed *murder*." | | 16 | "Cole held up a wallet." | | 17 | "Quinn exhaled through her nose." | | 18 | "She stepped closer to the" | | 19 | "A small, circular object, half-buried" |
| | ratio | 0.903 | |
| 53.76% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 93 | | matches | | 0 | "Now, it was just another" |
| | ratio | 0.011 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 3 | | matches | | 0 | "The victim lay sprawled across the tracks, limbs twisted at angles that made her stomach clench." | | 1 | "Male, mid-thirties, dressed in a rumpled suit that had seen better days." | | 2 | "Brass, tarnished with age, its needle spinning lazily before settling on a direction that made no sense—pointing straight at the wall." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 51 | | tagDensity | 0.039 | | leniency | 0.078 | | rawRatio | 0 | | effectiveRatio | 0 | |