| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 20 | | tagDensity | 0.45 | | leniency | 0.9 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.72% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1208 | | 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) | |
| 42.05% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1208 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "glint" | | 1 | "profound" | | 2 | "silence" | | 3 | "gloom" | | 4 | "chaotic" | | 5 | "tapestry" | | 6 | "pulsed" | | 7 | "mosaic" | | 8 | "weight" | | 9 | "familiar" | | 10 | "pulse" | | 11 | "disrupt" | | 12 | "raced" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 127 | | matches | (empty) | |
| 75.37% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 5 | | narrationSentences | 127 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 139 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1207 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 99.49% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 1089 | | uniqueNames | 13 | | maxNameDensity | 1.01 | | worstName | "Herrera" | | maxWindowNameDensity | 2 | | worstWindowName | "Herrera" | | discoveredNames | | Herrera | 11 | | Harlow | 1 | | Quinn | 11 | | Camden | 2 | | Morris | 3 | | Saint | 1 | | Christopher | 1 | | Victorian | 1 | | Tube | 1 | | Town | 1 | | Veil | 1 | | Market | 1 | | Spanish | 1 |
| | persons | | 0 | "Herrera" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Morris" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Market" |
| | places | | | globalScore | 0.995 | | windowScore | 1 | |
| 2.94% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 85 | | glossingSentenceCount | 5 | | matches | | 0 | "felt like a cold cap" | | 1 | "blades that seemed to twist if you looked at them too long" | | 2 | "looked like teeth" | | 3 | "felt like paper and air" | | 4 | "seemed more prisoner than suspect" |
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| 34.30% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.657 | | wordCount | 1207 | | matches | | 0 | "Not just shadow, but a profound absence of light" | | 1 | "not fear, but a terrible, dawning understanding" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 139 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 36 | | mean | 33.53 | | std | 23.67 | | cv | 0.706 | | sampleLengths | | 0 | 21 | | 1 | 75 | | 2 | 68 | | 3 | 52 | | 4 | 52 | | 5 | 58 | | 6 | 18 | | 7 | 53 | | 8 | 10 | | 9 | 44 | | 10 | 123 | | 11 | 33 | | 12 | 42 | | 13 | 48 | | 14 | 39 | | 15 | 31 | | 16 | 37 | | 17 | 12 | | 18 | 6 | | 19 | 42 | | 20 | 21 | | 21 | 16 | | 22 | 4 | | 23 | 18 | | 24 | 35 | | 25 | 5 | | 26 | 27 | | 27 | 9 | | 28 | 42 | | 29 | 40 | | 30 | 27 | | 31 | 24 | | 32 | 41 | | 33 | 13 | | 34 | 4 | | 35 | 17 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 127 | | matches | | |
| 41.27% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 168 | | matches | | 0 | "was running" | | 1 | "was talking" | | 2 | "was forming" | | 3 | "was still smiling" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 139 | | ratio | 0.007 | | matches | | 0 | "The look in his eyes before the end—not fear, but a terrible, dawning understanding." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 466 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.017167381974248927 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 139 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 139 | | mean | 8.68 | | std | 5.16 | | cv | 0.594 | | sampleLengths | | 0 | 21 | | 1 | 6 | | 2 | 14 | | 3 | 13 | | 4 | 13 | | 5 | 12 | | 6 | 17 | | 7 | 10 | | 8 | 13 | | 9 | 3 | | 10 | 12 | | 11 | 11 | | 12 | 15 | | 13 | 4 | | 14 | 6 | | 15 | 15 | | 16 | 24 | | 17 | 7 | | 18 | 7 | | 19 | 18 | | 20 | 4 | | 21 | 9 | | 22 | 3 | | 23 | 8 | | 24 | 1 | | 25 | 1 | | 26 | 1 | | 27 | 5 | | 28 | 6 | | 29 | 10 | | 30 | 16 | | 31 | 10 | | 32 | 4 | | 33 | 3 | | 34 | 4 | | 35 | 17 | | 36 | 1 | | 37 | 14 | | 38 | 3 | | 39 | 14 | | 40 | 9 | | 41 | 13 | | 42 | 5 | | 43 | 5 | | 44 | 7 | | 45 | 8 | | 46 | 14 | | 47 | 11 | | 48 | 4 | | 49 | 13 |
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| 53.72% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.37410071942446044 | | totalSentences | 139 | | uniqueOpeners | 52 | |
| 56.02% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 119 | | matches | | 0 | "Then he was gone, around" | | 1 | "Maybe even get a shot" |
| | ratio | 0.017 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 119 | | matches | | 0 | "He was good, but he" | | 1 | "Her salt-and-pepper hair, plastered to" | | 2 | "He ducked into an alley" | | 3 | "She didn't slow." | | 4 | "She didn't hesitate anymore." | | 5 | "He glanced back, his face" | | 6 | "She cornered hard, her shoulder" | | 7 | "She pulled a small torch" | | 8 | "It illuminated a descending staircase," | | 9 | "Her radio crackled on her" | | 10 | "She thumbed the radio off." | | 11 | "She started down, each step" | | 12 | "It was a bazaar, but" | | 13 | "She’d heard the name in" | | 14 | "She stood at the edge," | | 15 | "Her hand drifted to the" | | 16 | "She spotted him." | | 17 | "He handed over a small" | | 18 | "She was a discordant note," | | 19 | "She was ten feet away" |
| | ratio | 0.294 | |
| 35.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 101 | | totalSentences | 119 | | matches | | 0 | "Tomás Herrera moved like a" | | 1 | "A splash in a left-hand" | | 2 | "The shift of a shadow" | | 3 | "He was good, but he" | | 4 | "Quinn matched his pace, her" | | 5 | "Her salt-and-pepper hair, plastered to" | | 6 | "The worn leather strap of" | | 7 | "He ducked into an alley" | | 8 | "The stink of rotting food" | | 9 | "She didn't slow." | | 10 | "A moment's doubt, a glance" | | 11 | "Quinn had replayed that fragment" | | 12 | "She didn't hesitate anymore." | | 13 | "The alley twisted, a concrete" | | 14 | "Herrera was a darker blur" | | 15 | "He glanced back, his face" | | 16 | "She cornered hard, her shoulder" | | 17 | "The narrow passage ended at" | | 18 | "The smell changed." | | 19 | "Quinn stopped at the threshold." |
| | ratio | 0.849 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 119 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 47 | | technicalSentenceCount | 1 | | matches | | 0 | "Her radio crackled on her belt, a burst of static that made her jump." |
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| 13.89% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 2 | | matches | | 0 | "he said, his Spanish accent thickening" | | 1 | "Quinn said, her voice cutting through the murmur" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | 0 | "the gaunt man corrected (correct)" |
| | dialogueSentences | 20 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0.167 | | effectiveRatio | 0.1 | |