| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 2 | | adverbTags | | 0 | "I stepped aside [aside]" | | 1 | "I stepped back [back]" |
| | dialogueSentences | 51 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.118 | | effectiveRatio | 0.078 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1233 | | 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) | |
| 55.39% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1233 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "measured" | | 1 | "mosaic" | | 2 | "lilt" | | 3 | "intensity" | | 4 | "flicked" | | 5 | "weight" | | 6 | "flickered" | | 7 | "trembled" |
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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 | 1 | | narrationSentences | 93 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 93 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 127 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 17 | | totalWords | 1231 | | ratio | 0.014 | | matches | | 0 | "Don't be paranoid. London's full of people who knock at odd hours." | | 1 | "Lucien." | | 2 | "Bastard." | | 3 | "Liar." | | 4 | "Two years." |
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| 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 | 27 | | wordCount | 946 | | uniqueNames | 15 | | maxNameDensity | 0.74 | | worstName | "Eva" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Eva" | | discoveredNames | | London | 2 | | French | 1 | | English | 1 | | Eva | 7 | | Cardiff | 1 | | Two | 2 | | British | 1 | | Library | 1 | | Ptolemy | 2 | | Spitalfields | 1 | | Market | 1 | | Brick | 1 | | Lane | 1 | | Lucien | 4 | | Evan | 1 |
| | persons | | 0 | "French" | | 1 | "Eva" | | 2 | "Ptolemy" | | 3 | "Lucien" | | 4 | "Evan" |
| | places | | 0 | "London" | | 1 | "Cardiff" | | 2 | "Two" | | 3 | "British" | | 4 | "Library" | | 5 | "Spitalfields" | | 6 | "Brick" | | 7 | "Lane" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like I'd been dragged through thre" |
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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 | 1231 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 127 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 64 | | mean | 19.23 | | std | 14.88 | | cv | 0.774 | | sampleLengths | | 0 | 8 | | 1 | 32 | | 2 | 21 | | 3 | 28 | | 4 | 12 | | 5 | 44 | | 6 | 5 | | 7 | 3 | | 8 | 6 | | 9 | 30 | | 10 | 1 | | 11 | 36 | | 12 | 49 | | 13 | 20 | | 14 | 5 | | 15 | 20 | | 16 | 6 | | 17 | 25 | | 18 | 12 | | 19 | 12 | | 20 | 52 | | 21 | 5 | | 22 | 3 | | 23 | 26 | | 24 | 25 | | 25 | 2 | | 26 | 34 | | 27 | 16 | | 28 | 28 | | 29 | 5 | | 30 | 4 | | 31 | 50 | | 32 | 4 | | 33 | 2 | | 34 | 26 | | 35 | 40 | | 36 | 25 | | 37 | 13 | | 38 | 37 | | 39 | 3 | | 40 | 32 | | 41 | 3 | | 42 | 8 | | 43 | 30 | | 44 | 5 | | 45 | 8 | | 46 | 20 | | 47 | 6 | | 48 | 32 | | 49 | 41 |
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| 93.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 93 | | matches | | 0 | "were slid" | | 1 | "been dragged" | | 2 | "was worn" |
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| 43.14% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 170 | | matches | | 0 | "was looking" | | 1 | "wasn't running" | | 2 | "was standing" | | 3 | "was happening" |
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| 75.37% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 127 | | ratio | 0.024 | | matches | | 0 | "Eva's research notes covered the coffee table like a paper mosaic, and if anyone from the wrong side of town saw what she'd been digging into—" | | 1 | "And those eyes—one amber, one black—fixed on me with an intensity that made me want to slam the door and slide every bolt back into place." | | 2 | "The third—" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 951 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.026288117770767613 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.002103049421661409 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 127 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 127 | | mean | 9.69 | | std | 7.23 | | cv | 0.746 | | sampleLengths | | 0 | 8 | | 1 | 15 | | 2 | 3 | | 3 | 1 | | 4 | 1 | | 5 | 12 | | 6 | 8 | | 7 | 13 | | 8 | 10 | | 9 | 18 | | 10 | 3 | | 11 | 9 | | 12 | 18 | | 13 | 26 | | 14 | 4 | | 15 | 1 | | 16 | 3 | | 17 | 6 | | 18 | 2 | | 19 | 10 | | 20 | 18 | | 21 | 1 | | 22 | 5 | | 23 | 6 | | 24 | 25 | | 25 | 7 | | 26 | 6 | | 27 | 10 | | 28 | 26 | | 29 | 12 | | 30 | 8 | | 31 | 5 | | 32 | 9 | | 33 | 11 | | 34 | 6 | | 35 | 15 | | 36 | 10 | | 37 | 12 | | 38 | 9 | | 39 | 3 | | 40 | 5 | | 41 | 29 | | 42 | 18 | | 43 | 5 | | 44 | 3 | | 45 | 20 | | 46 | 3 | | 47 | 3 | | 48 | 13 | | 49 | 12 |
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| 48.56% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.3858267716535433 | | totalSentences | 127 | | uniqueOpeners | 49 | |
| 39.68% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 84 | | matches | | 0 | "Just noodles and deliveries and" |
| | ratio | 0.012 | |
| 77.14% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 84 | | matches | | 0 | "I set down my takeaway" | | 1 | "My blood turned to ice" | | 2 | "I hadn't heard it in" | | 3 | "I pulled back the bolts." | | 4 | "His gaze flicked past me" | | 5 | "He leaned on his cane," | | 6 | "He nodded toward the open" | | 7 | "I stepped aside, just enough" | | 8 | "He moved past me, close" | | 9 | "He surveyed Eva's cluttered living" | | 10 | "He settled into the armchair" | | 11 | "He didn't wince." | | 12 | "I looked like I'd been" | | 13 | "He reached into his jacket," | | 14 | "He tossed the envelope onto" | | 15 | "It landed against a stack" | | 16 | "I didn't move." | | 17 | "My life had been quiet" | | 18 | "He settled deeper into the" | | 19 | "I wasn't scared of what" |
| | ratio | 0.357 | |
| 49.29% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 84 | | matches | | 0 | "The knock came at a" | | 1 | "The kind of knock that" | | 2 | "Ptolemy hissed from his perch" | | 3 | "The tabby's ears flattened against" | | 4 | "I set down my takeaway" | | 5 | "The deadbolts were slid home," | | 6 | "London's full of people who" | | 7 | "London was also full of" | | 8 | "Eva's research notes covered the" | | 9 | "The knock came again." | | 10 | "My blood turned to ice" | | 11 | "That particular lilt of French" | | 12 | "I hadn't heard it in" | | 13 | "I pulled back the bolts." | | 14 | "The chain rattled against the" | | 15 | "Charcoal suit immaculate despite the" | | 16 | "The ivory-handled cane gripped in" | | 17 | "His gaze flicked past me" | | 18 | "He leaned on his cane," | | 19 | "He nodded toward the open" |
| | ratio | 0.821 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 2 | | matches | | 0 | "He moved past me, close enough that I caught the scent of expensive cologne and something smokier beneath it, something that clung to his clothes like a second …" | | 1 | "It landed against a stack of Eva's research, sending a few pages skittering." |
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| 95.59% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 1 | | matches | | 0 | "Lucien leaned, the cane's tip tapping the floor once" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 51 | | tagDensity | 0.039 | | leniency | 0.078 | | rawRatio | 0 | | effectiveRatio | 0 | |