| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.063 | | leniency | 0.125 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1197 | | totalAiIsmAdverbs | 1 | | 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) | |
| 79.11% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1197 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "flicked" | | 1 | "silence" | | 2 | "gloom" | | 3 | "resonated" | | 4 | "vibrated" |
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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 | 83 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 83 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1197 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 1085 | | uniqueNames | 17 | | maxNameDensity | 1.2 | | worstName | "Herrera" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Herrera" | | discoveredNames | | Herrera | 13 | | Camden | 1 | | Lock | 1 | | Quinn | 13 | | Spaniard | 1 | | Chalk | 1 | | Farm | 1 | | Road | 1 | | Morris | 4 | | Victorian | 1 | | Edwardian | 1 | | London | 2 | | Saint | 1 | | Christopher | 1 | | Purdey | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Herrera" | | 1 | "Quinn" | | 2 | "Spaniard" | | 3 | "Morris" | | 4 | "Victorian" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Market" |
| | places | | 0 | "Chalk" | | 1 | "Farm" | | 2 | "Road" | | 3 | "London" |
| | globalScore | 0.901 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like an unholy flea market carved" |
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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 | 1197 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 23.02 | | std | 16.72 | | cv | 0.726 | | sampleLengths | | 0 | 32 | | 1 | 55 | | 2 | 1 | | 3 | 40 | | 4 | 49 | | 5 | 22 | | 6 | 12 | | 7 | 5 | | 8 | 39 | | 9 | 41 | | 10 | 28 | | 11 | 52 | | 12 | 18 | | 13 | 23 | | 14 | 43 | | 15 | 14 | | 16 | 54 | | 17 | 22 | | 18 | 43 | | 19 | 43 | | 20 | 21 | | 21 | 29 | | 22 | 2 | | 23 | 10 | | 24 | 2 | | 25 | 7 | | 26 | 10 | | 27 | 11 | | 28 | 36 | | 29 | 61 | | 30 | 3 | | 31 | 36 | | 32 | 7 | | 33 | 20 | | 34 | 8 | | 35 | 9 | | 36 | 37 | | 37 | 6 | | 38 | 28 | | 39 | 16 | | 40 | 10 | | 41 | 2 | | 42 | 9 | | 43 | 19 | | 44 | 4 | | 45 | 32 | | 46 | 12 | | 47 | 31 | | 48 | 7 | | 49 | 49 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 83 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 188 | | matches | (empty) | |
| 84.55% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 98 | | ratio | 0.02 | | matches | | 0 | "One carried an ancient sawed-off Purdey shotgun; the other held an iron cane topped with a carved crow skull." | | 1 | "The man with the shotgun did not raise the barrels; he merely tilted his head, revealing a throat crisscrossed with pale ritual scars that puckered when he spoke." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1098 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 15 | | adverbRatio | 0.01366120218579235 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.00819672131147541 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 12.21 | | std | 6.35 | | cv | 0.52 | | sampleLengths | | 0 | 13 | | 1 | 19 | | 2 | 10 | | 3 | 24 | | 4 | 9 | | 5 | 12 | | 6 | 1 | | 7 | 4 | | 8 | 23 | | 9 | 13 | | 10 | 14 | | 11 | 13 | | 12 | 22 | | 13 | 17 | | 14 | 5 | | 15 | 12 | | 16 | 5 | | 17 | 14 | | 18 | 14 | | 19 | 11 | | 20 | 5 | | 21 | 15 | | 22 | 19 | | 23 | 2 | | 24 | 7 | | 25 | 9 | | 26 | 12 | | 27 | 6 | | 28 | 12 | | 29 | 24 | | 30 | 10 | | 31 | 18 | | 32 | 4 | | 33 | 19 | | 34 | 8 | | 35 | 15 | | 36 | 20 | | 37 | 14 | | 38 | 17 | | 39 | 14 | | 40 | 9 | | 41 | 14 | | 42 | 10 | | 43 | 12 | | 44 | 14 | | 45 | 18 | | 46 | 11 | | 47 | 8 | | 48 | 16 | | 49 | 19 |
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| 68.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.4387755102040816 | | totalSentences | 98 | | uniqueOpeners | 43 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 81 | | matches | | 0 | "He rounded a brick corner," | | 1 | "He did not turn." | | 2 | "He shoved through a metal" | | 3 | "Her worn leather watch scraped" | | 4 | "He carried stolen hospital supplies," | | 5 | "He did not slow down." | | 6 | "He hauled the door open" | | 7 | "Her torch beam speared down" | | 8 | "She flicked the beam across" | | 9 | "She secured her torch to" | | 10 | "Her boots found metal." | | 11 | "She descended with military precision," | | 12 | "She moved along the sleeper" | | 13 | "Her sharp jaw tightened as" | | 14 | "His hand clutched his left" | | 15 | "They wore long oilskin duster" | | 16 | "He did not pull a" | | 17 | "It looked like an unholy" | | 18 | "His warm brown eyes looked" | | 19 | "His hand tightened over the" |
| | ratio | 0.284 | |
| 58.77% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 81 | | matches | | 0 | "Quinn tackled the wooden pallet" | | 1 | "Tomás Herrera bolted down the" | | 2 | "Water kicked up from Quinn's" | | 3 | "He rounded a brick corner," | | 4 | "The canvas satchel slung across" | | 5 | "He did not turn." | | 6 | "He shoved through a metal" | | 7 | "Quinn cleared the barrier in" | | 8 | "Her worn leather watch scraped" | | 9 | "He carried stolen hospital supplies," | | 10 | "Herrera darted toward the rear" | | 11 | "He did not slow down." | | 12 | "Quinn reached into her coat," | | 13 | "Herrera slammed both hands into" | | 14 | "The heavy padlock hung in" | | 15 | "He hauled the door open" | | 16 | "Quinn arrived three seconds later." | | 17 | "Her torch beam speared down" | | 18 | "She flicked the beam across" | | 19 | "A smear of dark crimson" |
| | ratio | 0.802 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 94.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 59 | | technicalSentenceCount | 4 | | matches | | 0 | "He carried stolen hospital supplies, illicit sedatives, and answers about the Morris file that had kept Quinn awake for three bloody years." | | 1 | "Water ran along the disused tracks in a sluggish trickle, vanishing into an arched passage that curved toward the south." | | 2 | "They wore long oilskin duster coats and wide-brimmed hats that cast deep shadows over their features." | | 3 | "The scent of bitter almond and burnt copper flooded her nostrils from a hand that clamped over her mouth from behind, pinning her against a chest of solid muscl…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |