| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 21 | | tagDensity | 0.381 | | leniency | 0.762 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1112 | | 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) | |
| 86.51% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1112 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoed" | | 2 | "flickered" |
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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 | 92 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 92 | | filterMatches | | | 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 | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1112 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 889 | | uniqueNames | 12 | | maxNameDensity | 0.9 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Inverness | 1 | | Street | 1 | | Quinn | 8 | | Morris | 3 | | Camden | 1 | | Tube | 1 | | Spanish | 1 | | English | 1 | | Tomás | 1 | | Cold | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Tomás" |
| | places | | 0 | "Inverness" | | 1 | "Street" | | 2 | "Veil" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.899 | | wordCount | 1112 | | matches | | 0 | "not the blue-white of working bulbs but something warmer, redder" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 105 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 25.27 | | std | 21.25 | | cv | 0.841 | | sampleLengths | | 0 | 19 | | 1 | 65 | | 2 | 14 | | 3 | 56 | | 4 | 2 | | 5 | 7 | | 6 | 46 | | 7 | 2 | | 8 | 39 | | 9 | 1 | | 10 | 49 | | 11 | 20 | | 12 | 9 | | 13 | 7 | | 14 | 60 | | 15 | 7 | | 16 | 39 | | 17 | 7 | | 18 | 73 | | 19 | 13 | | 20 | 6 | | 21 | 4 | | 22 | 36 | | 23 | 4 | | 24 | 28 | | 25 | 4 | | 26 | 36 | | 27 | 26 | | 28 | 5 | | 29 | 43 | | 30 | 15 | | 31 | 14 | | 32 | 2 | | 33 | 66 | | 34 | 30 | | 35 | 29 | | 36 | 12 | | 37 | 50 | | 38 | 67 | | 39 | 7 | | 40 | 3 | | 41 | 43 | | 42 | 19 | | 43 | 28 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 92 | | matches | | |
| 65.77% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 149 | | matches | | 0 | "wasn't losing" | | 1 | "was heading" | | 2 | "was singing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 105 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 892 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.023542600896860985 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0033632286995515697 | |
| 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 | 10.59 | | std | 8.47 | | cv | 0.8 | | sampleLengths | | 0 | 19 | | 1 | 9 | | 2 | 35 | | 3 | 11 | | 4 | 10 | | 5 | 6 | | 6 | 3 | | 7 | 2 | | 8 | 3 | | 9 | 10 | | 10 | 13 | | 11 | 13 | | 12 | 5 | | 13 | 4 | | 14 | 6 | | 15 | 5 | | 16 | 2 | | 17 | 4 | | 18 | 3 | | 19 | 26 | | 20 | 20 | | 21 | 2 | | 22 | 4 | | 23 | 15 | | 24 | 13 | | 25 | 7 | | 26 | 1 | | 27 | 17 | | 28 | 12 | | 29 | 6 | | 30 | 14 | | 31 | 3 | | 32 | 5 | | 33 | 12 | | 34 | 9 | | 35 | 7 | | 36 | 17 | | 37 | 20 | | 38 | 3 | | 39 | 20 | | 40 | 7 | | 41 | 5 | | 42 | 10 | | 43 | 10 | | 44 | 14 | | 45 | 7 | | 46 | 22 | | 47 | 7 | | 48 | 16 | | 49 | 14 |
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| 69.21% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.4666666666666667 | | totalSentences | 105 | | uniqueOpeners | 49 | |
| 79.37% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 84 | | matches | | 0 | "Somewhere a voice was singing" | | 1 | "Almost as though he wanted" |
| | ratio | 0.024 | |
| 67.62% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 84 | | matches | | 0 | "She'd lost sight of his" | | 1 | "She wasn't losing him to" | | 2 | "Her radio crackled against her" | | 3 | "She killed it." | | 4 | "He vaulted a stack of" | | 5 | "He didn't glance back." | | 6 | "He didn't waste a single" | | 7 | "He was heading somewhere specific." | | 8 | "They never stopped." | | 9 | "He skidded past a flower" | | 10 | "Her watch snagged on a" | | 11 | "She hit them too quick" | | 12 | "She heard voices." | | 13 | "She nudged the door with" | | 14 | "She'd stepped into something that" | | 15 | "She spun, baton up." | | 16 | "His eyes weren't hostile." | | 17 | "They were afraid, but not" | | 18 | "His accent rolled the words" | | 19 | "His grip tightened, urgent now" |
| | ratio | 0.381 | |
| 79.05% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 84 | | matches | | 0 | "The suspect cut left at" | | 1 | "She'd lost sight of his" | | 2 | "She wasn't losing him to" | | 3 | "Her radio crackled against her" | | 4 | "She killed it." | | 5 | "He vaulted a stack of" | | 6 | "Quinn went around them, lungs" | | 7 | "This one knew the streets." | | 8 | "He didn't glance back." | | 9 | "He didn't waste a single" | | 10 | "He was heading somewhere specific." | | 11 | "A waste of breath." | | 12 | "They never stopped." | | 13 | "The market stalls were down" | | 14 | "He skidded past a flower" | | 15 | "The alley narrowed fast." | | 16 | "Brick on both sides, slick" | | 17 | "Her watch snagged on a" | | 18 | "She hit them too quick" | | 19 | "The rain noise faded above" |
| | ratio | 0.762 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 4 | | matches | | 0 | "Faint light leaked through the gap, not the blue-white of working bulbs but something warmer, redder, that flickered like firelight." | | 1 | "Many of them, low and overlapping, the murmur of a crowd that had no business existing beneath a derelict platform." | | 2 | "Lanterns hung from the curved tile ceiling, throwing light that moved wrong, too slow, as though the air itself were thicker here." | | 3 | "Quinn tightened her grip on the baton, the bone token biting into her other palm, and walked into the Veil Market after the man who'd killed her partner." |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, eyes fixed on the green coat" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 21 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0 | | effectiveRatio | 0 | |