| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 40 | | tagDensity | 0.325 | | leniency | 0.65 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1392 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 89.22% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1392 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "silence" | | 1 | "trembled" | | 2 | "etched" |
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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 | 89 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 89 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 116 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1392 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 57.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 914 | | uniqueNames | 8 | | maxNameDensity | 1.86 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 17 | | Camden | 1 | | High | 1 | | Street | 1 | | Veil | 1 | | Market | 1 | | Kowalski | 1 | | Eva | 15 |
| | persons | | 0 | "Harlow" | | 1 | "Market" | | 2 | "Kowalski" | | 3 | "Eva" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" |
| | globalScore | 0.57 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1392 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 116 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 30.93 | | std | 23.8 | | cv | 0.769 | | sampleLengths | | 0 | 92 | | 1 | 61 | | 2 | 2 | | 3 | 15 | | 4 | 77 | | 5 | 97 | | 6 | 49 | | 7 | 10 | | 8 | 26 | | 9 | 48 | | 10 | 16 | | 11 | 47 | | 12 | 27 | | 13 | 4 | | 14 | 5 | | 15 | 45 | | 16 | 4 | | 17 | 10 | | 18 | 35 | | 19 | 35 | | 20 | 30 | | 21 | 44 | | 22 | 3 | | 23 | 6 | | 24 | 51 | | 25 | 7 | | 26 | 56 | | 27 | 42 | | 28 | 25 | | 29 | 9 | | 30 | 4 | | 31 | 50 | | 32 | 29 | | 33 | 16 | | 34 | 65 | | 35 | 5 | | 36 | 39 | | 37 | 31 | | 38 | 32 | | 39 | 28 | | 40 | 54 | | 41 | 4 | | 42 | 14 | | 43 | 30 | | 44 | 13 |
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| 89.49% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 89 | | matches | | 0 | "been etched" | | 1 | "been scraped" | | 2 | "been forced" | | 3 | "been smeared" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 154 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 116 | | ratio | 0.009 | | matches | | 0 | "The neck bent; there was a small depression behind his left ear, hidden by the collar." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 916 | | adjectiveStacks | 1 | | stackExamples | | 0 | "cloying honey-sweet smell" |
| | adverbCount | 21 | | adverbRatio | 0.02292576419213974 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.001091703056768559 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 116 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 116 | | mean | 12 | | std | 8.36 | | cv | 0.697 | | sampleLengths | | 0 | 20 | | 1 | 7 | | 2 | 11 | | 3 | 18 | | 4 | 6 | | 5 | 30 | | 6 | 6 | | 7 | 13 | | 8 | 20 | | 9 | 14 | | 10 | 8 | | 11 | 2 | | 12 | 15 | | 13 | 5 | | 14 | 13 | | 15 | 6 | | 16 | 19 | | 17 | 10 | | 18 | 7 | | 19 | 17 | | 20 | 13 | | 21 | 9 | | 22 | 4 | | 23 | 15 | | 24 | 23 | | 25 | 4 | | 26 | 4 | | 27 | 25 | | 28 | 16 | | 29 | 18 | | 30 | 15 | | 31 | 10 | | 32 | 24 | | 33 | 2 | | 34 | 28 | | 35 | 20 | | 36 | 16 | | 37 | 47 | | 38 | 5 | | 39 | 6 | | 40 | 7 | | 41 | 9 | | 42 | 4 | | 43 | 5 | | 44 | 4 | | 45 | 8 | | 46 | 23 | | 47 | 6 | | 48 | 4 | | 49 | 4 |
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| 52.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.35344827586206895 | | totalSentences | 116 | | uniqueOpeners | 41 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 87 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 87 | | matches | | 0 | "She pocketed the sliver and" | | 1 | "Her torch cut through the" | | 2 | "He checked her identification with" | | 3 | "Her shoe caught on the" | | 4 | "She checked the worn leather" | | 5 | "His head drooped forward." | | 6 | "She ran a gloved finger" | | 7 | "She lifted one of his" | | 8 | "She let go and watched" | | 9 | "She pulled the lamp close" | | 10 | "They stopped at the back" | | 11 | "She followed them backward." | | 12 | "She moved the lamp." | | 13 | "She picked it up by" | | 14 | "She set it down and" | | 15 | "She straightened and looked around." | | 16 | "She lifted the bottom corner" | | 17 | "She lifted his head." | | 18 | "She held the lamp close." | | 19 | "She pulled off her glasses" |
| | ratio | 0.253 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 87 | | matches | | 0 | "The bone token warmed in" | | 1 | "The lock ticked open without" | | 2 | "She pocketed the sliver and" | | 3 | "A stairwell dropped into a" | | 4 | "Her torch cut through the" | | 5 | "The steps ended at a" | | 6 | "Stalls stood between rusted columns," | | 7 | "The Veil Market had a" | | 8 | "A uniformed constable waited at" | | 9 | "He checked her identification with" | | 10 | "Harlow ducked under the tape." | | 11 | "Her shoe caught on the" | | 12 | "The platform had no straight" | | 13 | "Everything tilted a half degree" | | 14 | "She checked the worn leather" | | 15 | "The full moon was two" | | 16 | "The market would fold itself" | | 17 | "The stall had a green" | | 18 | "A beaded curtain hung across" | | 19 | "Harlow pushed it aside." |
| | ratio | 0.943 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 87 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |