| 75.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 2 | | adverbTags | | 0 | "His accent curled around [around]" | | 1 | "he finished quietly [quietly]" |
| | dialogueSentences | 32 | | tagDensity | 0.375 | | leniency | 0.75 | | rawRatio | 0.167 | | effectiveRatio | 0.125 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1238 | | 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) | |
| 83.84% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1238 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "quickened" | | 1 | "silence" | | 2 | "flicked" | | 3 | "streaming" |
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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 | 86 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 86 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 105 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 75 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1230 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 823 | | uniqueNames | 18 | | maxNameDensity | 0.36 | | worstName | "Street" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Street" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Frith | 1 | | Street | 3 | | Harlow | 1 | | Quinn | 3 | | Morris | 3 | | Herrera | 3 | | Old | 1 | | Compton | 1 | | Monmouth | 1 | | Camden | 1 | | Saint | 1 | | Christopher | 1 | | Seville | 1 | | Didn | 1 | | Tube | 1 | | Rain | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Rain" |
| | places | | 0 | "Raven" | | 1 | "Frith" | | 2 | "Street" | | 3 | "Old" | | 4 | "Compton" | | 5 | "Monmouth" | | 6 | "Camden" | | 7 | "Seville" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 50 | | 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 | 1230 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 105 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 25.63 | | std | 23.52 | | cv | 0.918 | | sampleLengths | | 0 | 42 | | 1 | 18 | | 2 | 40 | | 3 | 20 | | 4 | 9 | | 5 | 56 | | 6 | 2 | | 7 | 43 | | 8 | 2 | | 9 | 9 | | 10 | 53 | | 11 | 23 | | 12 | 26 | | 13 | 32 | | 14 | 8 | | 15 | 31 | | 16 | 4 | | 17 | 35 | | 18 | 8 | | 19 | 91 | | 20 | 5 | | 21 | 10 | | 22 | 13 | | 23 | 39 | | 24 | 8 | | 25 | 18 | | 26 | 3 | | 27 | 6 | | 28 | 55 | | 29 | 3 | | 30 | 6 | | 31 | 101 | | 32 | 23 | | 33 | 39 | | 34 | 2 | | 35 | 44 | | 36 | 27 | | 37 | 20 | | 38 | 5 | | 39 | 36 | | 40 | 11 | | 41 | 22 | | 42 | 93 | | 43 | 12 | | 44 | 9 | | 45 | 34 | | 46 | 18 | | 47 | 16 |
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| 93.02% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 86 | | matches | | 0 | "being brushed" | | 1 | "was, hidden" | | 2 | "being counted" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 144 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 1 | | flaggedSentences | 6 | | totalSentences | 105 | | ratio | 0.057 | | matches | | 0 | "Olive skin, sharp jaw, the particular way he checked the street before moving—left, right, then over his shoulder without turning his head." | | 1 | "Her radio crackled against her shoulder—dispatch checking in, she ignored it." | | 2 | "Some did, it was true—office clothes, sensible shoes." | | 3 | "Of the word the coroner had used in the final report—unexplained—and the way he'd refused to meet her eyes." | | 4 | "Rain had stopped dripping; the lantern light caught the scar on his forearm where his sleeve had ridden up." | | 5 | "The market breathed around them—haggling voices, lantern hiss, the clink of bone tokens being counted." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 832 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.027644230769230768 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.007211538461538462 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 105 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 105 | | mean | 11.71 | | std | 10.4 | | cv | 0.888 | | sampleLengths | | 0 | 17 | | 1 | 25 | | 2 | 2 | | 3 | 16 | | 4 | 4 | | 5 | 11 | | 6 | 22 | | 7 | 1 | | 8 | 2 | | 9 | 2 | | 10 | 2 | | 11 | 2 | | 12 | 14 | | 13 | 9 | | 14 | 23 | | 15 | 6 | | 16 | 2 | | 17 | 2 | | 18 | 23 | | 19 | 2 | | 20 | 14 | | 21 | 14 | | 22 | 15 | | 23 | 2 | | 24 | 2 | | 25 | 4 | | 26 | 3 | | 27 | 15 | | 28 | 5 | | 29 | 12 | | 30 | 21 | | 31 | 18 | | 32 | 5 | | 33 | 16 | | 34 | 10 | | 35 | 32 | | 36 | 5 | | 37 | 2 | | 38 | 1 | | 39 | 12 | | 40 | 2 | | 41 | 17 | | 42 | 4 | | 43 | 14 | | 44 | 21 | | 45 | 8 | | 46 | 17 | | 47 | 21 | | 48 | 15 | | 49 | 38 |
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| 87.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.5523809523809524 | | totalSentences | 105 | | uniqueOpeners | 58 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 69 | | matches | | 0 | "Currently supplying medical care to" | | 1 | "Of course he didn't." | | 2 | "Perhaps two hundred people milled" |
| | ratio | 0.043 | |
| 57.68% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 69 | | matches | | 0 | "She let him get twenty" | | 1 | "He cut west on Old" | | 2 | "His pace quickened past the" | | 3 | "She tore after him, lungs" | | 4 | "He shoulder-checked a woman out" | | 5 | "They never did." | | 6 | "He ducked beneath a railway" | | 7 | "His white breath came fast." | | 8 | "She fanned her stance, one" | | 9 | "His accent curled around the" | | 10 | "His hand found the door" | | 11 | "He didn't open the door" | | 12 | "His eyes flicked past her" | | 13 | "He pulled the door open" | | 14 | "He stepped backward into the" | | 15 | "Her radio crackled against her" | | 16 | "She keyed her radio." | | 17 | "She thumbed it off and" | | 18 | "Her rain-soaked coat steamed faintly." | | 19 | "She stopped breathing for a" |
| | ratio | 0.406 | |
| 75.94% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 53 | | totalSentences | 69 | | matches | | 0 | "Detective Harlow Quinn stood beneath" | | 1 | "The door swung open." | | 2 | "A man stepped out, hood" | | 3 | "Olive skin, sharp jaw, the" | | 4 | "She let him get twenty" | | 5 | "He cut west on Old" | | 6 | "His pace quickened past the" | | 7 | "Boots slapping wet stone, he" | | 8 | "She tore after him, lungs" | | 9 | "He shoulder-checked a woman out" | | 10 | "They never did." | | 11 | "He ducked beneath a railway" | | 12 | "His white breath came fast." | | 13 | "Rain dripped from his sleeves," | | 14 | "The Saint Christopher medallion swung" | | 15 | "She fanned her stance, one" | | 16 | "His accent curled around the" | | 17 | "His hand found the door" | | 18 | "Something shifted in his face." | | 19 | "He didn't open the door" |
| | ratio | 0.768 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 69 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 1 | | matches | | 0 | "Beyond it, stairs descended into yellow-orange dark, the kind of light that came from old sodium bulbs and never touched daylight." |
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| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 2 | | matches | | 0 | "His accent curled around, Seville bleeding through" | | 1 | "He started, and the crowd parted around him like water around a stone" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 32 | | tagDensity | 0.094 | | leniency | 0.188 | | rawRatio | 0.333 | | effectiveRatio | 0.063 | |