| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "Her voice trembled slightly [slightly]" |
| | dialogueSentences | 40 | | tagDensity | 0.275 | | leniency | 0.55 | | rawRatio | 0.091 | | effectiveRatio | 0.05 | |
| 84.47% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1288 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "lazily" | | 1 | "slowly" | | 2 | "slightly" |
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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) | |
| 45.65% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1288 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "echoed" | | 2 | "stark" | | 3 | "scanning" | | 4 | "weight" | | 5 | "pristine" | | 6 | "etched" | | 7 | "intricate" | | 8 | "maw" | | 9 | "flicker" | | 10 | "chaotic" | | 11 | "trembled" |
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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 | 79 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 79 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1284 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 805 | | uniqueNames | 8 | | maxNameDensity | 1.74 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Harlow" | | discoveredNames | | Tube | 1 | | Quinn | 1 | | Brighton | 1 | | Thorne | 8 | | Harlow | 14 | | North | 1 | | Kowalski | 1 | | Eva | 8 |
| | persons | | 0 | "Quinn" | | 1 | "Thorne" | | 2 | "Harlow" | | 3 | "Kowalski" | | 4 | "Eva" |
| | places | | | globalScore | 0.63 | | windowScore | 0.5 | |
| 34.62% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | glossingSentenceCount | 3 | | matches | | 0 | "as if welcoming the darkness" | | 1 | "looked like the petals of a flower" | | 2 | "sigils that seemed to shift in the uneven light" |
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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 | 1284 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 107 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 22.93 | | std | 13.74 | | cv | 0.599 | | sampleLengths | | 0 | 44 | | 1 | 69 | | 2 | 23 | | 3 | 7 | | 4 | 29 | | 5 | 37 | | 6 | 13 | | 7 | 1 | | 8 | 9 | | 9 | 4 | | 10 | 36 | | 11 | 27 | | 12 | 41 | | 13 | 41 | | 14 | 32 | | 15 | 27 | | 16 | 35 | | 17 | 5 | | 18 | 16 | | 19 | 46 | | 20 | 29 | | 21 | 28 | | 22 | 9 | | 23 | 29 | | 24 | 29 | | 25 | 31 | | 26 | 5 | | 27 | 2 | | 28 | 50 | | 29 | 18 | | 30 | 16 | | 31 | 28 | | 32 | 32 | | 33 | 30 | | 34 | 34 | | 35 | 32 | | 36 | 30 | | 37 | 20 | | 38 | 11 | | 39 | 8 | | 40 | 31 | | 41 | 3 | | 42 | 29 | | 43 | 10 | | 44 | 5 | | 45 | 29 | | 46 | 22 | | 47 | 10 | | 48 | 21 | | 49 | 13 |
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| 96.38% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 79 | | matches | | 0 | "was etched" | | 1 | "was broken" | | 2 | "been ripped" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 139 | | matches | | 0 | "wasn't pointing" | | 1 | "was pointing" |
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| 89.45% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 107 | | ratio | 0.019 | | matches | | 0 | "The poster, peeling and faded, advertised holidays in Brighton—a stark contrast to the corpse cooling in the shadows." | | 1 | "A flicker of movement caught her eye—shadows that didn't align with the placement of the lights." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 808 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.02599009900990099 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.013613861386138614 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 12 | | std | 7.94 | | cv | 0.662 | | sampleLengths | | 0 | 22 | | 1 | 22 | | 2 | 25 | | 3 | 26 | | 4 | 18 | | 5 | 13 | | 6 | 10 | | 7 | 7 | | 8 | 8 | | 9 | 12 | | 10 | 9 | | 11 | 37 | | 12 | 9 | | 13 | 4 | | 14 | 1 | | 15 | 8 | | 16 | 1 | | 17 | 4 | | 18 | 12 | | 19 | 13 | | 20 | 11 | | 21 | 27 | | 22 | 9 | | 23 | 8 | | 24 | 18 | | 25 | 2 | | 26 | 2 | | 27 | 2 | | 28 | 41 | | 29 | 6 | | 30 | 26 | | 31 | 8 | | 32 | 13 | | 33 | 6 | | 34 | 8 | | 35 | 11 | | 36 | 16 | | 37 | 5 | | 38 | 16 | | 39 | 35 | | 40 | 11 | | 41 | 10 | | 42 | 11 | | 43 | 8 | | 44 | 4 | | 45 | 9 | | 46 | 15 | | 47 | 9 | | 48 | 8 | | 49 | 17 |
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| 63.55% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.4205607476635514 | | totalSentences | 107 | | uniqueOpeners | 45 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 41.62% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 74 | | matches | | 0 | "She ignored the uniformed officer" | | 1 | "She adjusted the cuffs of" | | 2 | "Her sharp jawline tightened as" | | 3 | "He looked exhausted, his tie" | | 4 | "He gestured to the body" | | 5 | "She didn't kneel immediately." | | 6 | "She walked a slow circle" | | 7 | "His chest was a ruin" | | 8 | "She crouched down, resting her" | | 9 | "She leaned in close to" | | 10 | "She reached into a pocket" | | 11 | "She hovered her hands over" | | 12 | "It was small, almost delicate," | | 13 | "She pointed to the pristine" | | 14 | "She reached for it, brushing" | | 15 | "It was a compass." | | 16 | "She held it flat." | | 17 | "It wasn't pointing North." | | 18 | "It was pointing directly at" | | 19 | "She stood up, slipping the" |
| | ratio | 0.446 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 74 | | matches | | 0 | "Water dripped somewhere in the" | | 1 | "The air hung heavy and" | | 2 | "Harlow Quinn ducked under the" | | 3 | "She ignored the uniformed officer" | | 4 | "The poster, peeling and faded," | | 5 | "She adjusted the cuffs of" | | 6 | "Her sharp jawline tightened as" | | 7 | "DS Thorne straightened up, clicking" | | 8 | "He looked exhausted, his tie" | | 9 | "He gestured to the body" | | 10 | "Harlow stepped closer, her eyes" | | 11 | "She didn't kneel immediately." | | 12 | "Thorne blinked, rubbing a hand" | | 13 | "She walked a slow circle" | | 14 | "The victim lay on his" | | 15 | "His chest was a ruin" | | 16 | "She crouched down, resting her" | | 17 | "She leaned in close to" | | 18 | "The eyes were open, staring" | | 19 | "Thorne sighed, pulling out his" |
| | ratio | 0.986 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 1 | | matches | | 0 | "Water dripped somewhere in the darkness, a rhythmic, hollow plinking sound that echoed off the tiled walls of the abandoned Tube station." |
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| 34.09% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 2 | | matches | | 0 | "Thorne’s voice dropped, conspiratorial but uneasy" | | 1 | "Eva looked up, her green eyes wide and serious" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | 0 | "Harlow corrected (correct)" |
| | dialogueSentences | 40 | | tagDensity | 0.1 | | leniency | 0.2 | | rawRatio | 0.25 | | effectiveRatio | 0.05 | |