| 53.66% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 3 | | adverbTags | | 0 | "heterochromatic eyes glinted knowingly [knowingly]" | | 1 | "Lucien leaned back [back]" | | 2 | "Lucien said smoothly [smoothly]" |
| | dialogueSentences | 41 | | tagDensity | 0.39 | | leniency | 0.78 | | rawRatio | 0.188 | | effectiveRatio | 0.146 | |
| 72.94% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 924 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "knowingly" | | 1 | "lazily" | | 2 | "really" | | 3 | "very" | | 4 | "carefully" |
| |
| 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) | |
| 13.42% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 924 | | totalAiIsms | 16 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | word | "down her spine" | | count | 1 |
| | 13 | | | 14 | | | 15 | |
| | highlights | | 0 | "echoing" | | 1 | "absolutely" | | 2 | "scanned" | | 3 | "raced" | | 4 | "silence" | | 5 | "measured" | | 6 | "furrowed" | | 7 | "unwavering" | | 8 | "jaw clenched" | | 9 | "silk" | | 10 | "pounding" | | 11 | "racing" | | 12 | "down her spine" | | 13 | "familiar" | | 14 | "weight" | | 15 | "comforting" |
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| 0.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 4 | | maxInWindow | 4 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "knuckles turned white" | | count | 1 |
| | 2 | | label | "jaw/fists clenched" | | count | 1 |
| | 3 | | label | "sent a shiver through" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "knuckles turned white" | | 2 | "jaw clenched" | | 3 | "sent a shiver down" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 67 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 67 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 90 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 923 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 649 | | uniqueNames | 7 | | maxNameDensity | 2.77 | | worstName | "Rory" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Rory" | | discoveredNames | | Moreau | 1 | | Carter | 1 | | Rory | 18 | | Lucien | 14 | | Frenchman | 1 | | Evan | 4 | | Ptolemy | 3 |
| | persons | | 0 | "Moreau" | | 1 | "Carter" | | 2 | "Rory" | | 3 | "Lucien" | | 4 | "Frenchman" | | 5 | "Evan" | | 6 | "Ptolemy" |
| | places | (empty) | | globalScore | 0.113 | | windowScore | 0 | |
| 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 | 923 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 90 | | matches | (empty) | |
| 93.89% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 21.47 | | std | 10.27 | | cv | 0.479 | | sampleLengths | | 0 | 23 | | 1 | 23 | | 2 | 8 | | 3 | 18 | | 4 | 16 | | 5 | 16 | | 6 | 17 | | 7 | 45 | | 8 | 1 | | 9 | 27 | | 10 | 16 | | 11 | 22 | | 12 | 16 | | 13 | 8 | | 14 | 33 | | 15 | 16 | | 16 | 37 | | 17 | 12 | | 18 | 16 | | 19 | 9 | | 20 | 15 | | 21 | 37 | | 22 | 11 | | 23 | 26 | | 24 | 11 | | 25 | 22 | | 26 | 16 | | 27 | 15 | | 28 | 23 | | 29 | 18 | | 30 | 15 | | 31 | 23 | | 32 | 24 | | 33 | 15 | | 34 | 31 | | 35 | 31 | | 36 | 38 | | 37 | 29 | | 38 | 34 | | 39 | 28 | | 40 | 50 | | 41 | 21 | | 42 | 11 |
| |
| 94.79% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 67 | | matches | | 0 | "get caught" | | 1 | "get caught" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 118 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 90 | | ratio | 0.011 | | matches | | 0 | "But Lucien was right - if Evan was involved with those \"unsavoury people,\" it was only a matter of time before they came knocking." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 650 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.03538461538461538 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.010769230769230769 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 90 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 90 | | mean | 10.26 | | std | 5.55 | | cv | 0.542 | | sampleLengths | | 0 | 16 | | 1 | 2 | | 2 | 5 | | 3 | 13 | | 4 | 10 | | 5 | 8 | | 6 | 14 | | 7 | 4 | | 8 | 16 | | 9 | 16 | | 10 | 17 | | 11 | 17 | | 12 | 10 | | 13 | 18 | | 14 | 1 | | 15 | 18 | | 16 | 9 | | 17 | 8 | | 18 | 8 | | 19 | 8 | | 20 | 14 | | 21 | 4 | | 22 | 12 | | 23 | 7 | | 24 | 1 | | 25 | 22 | | 26 | 11 | | 27 | 16 | | 28 | 28 | | 29 | 9 | | 30 | 8 | | 31 | 4 | | 32 | 6 | | 33 | 10 | | 34 | 3 | | 35 | 6 | | 36 | 7 | | 37 | 8 | | 38 | 12 | | 39 | 14 | | 40 | 11 | | 41 | 7 | | 42 | 4 | | 43 | 7 | | 44 | 19 | | 45 | 3 | | 46 | 8 | | 47 | 22 | | 48 | 11 | | 49 | 5 |
| |
| 71.48% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.45555555555555555 | | totalSentences | 90 | | uniqueOpeners | 41 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 64 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 64 | | matches | | 0 | "Her gaze narrowed at the" | | 1 | "She started to close the" | | 2 | "His heterochromatic eyes glinted knowingly" | | 3 | "She let out a slow," | | 4 | "She lifted her chin, eyes" | | 5 | "His eyes gleamed with amusement" | | 6 | "She let the book slip" | | 7 | "She shook her head, running" | | 8 | "She couldn't afford to get" | | 9 | "She let out a heavy" | | 10 | "She had to do something." | | 11 | "She couldn't just sit back" | | 12 | "She had to find Evan." | | 13 | "She pulled it on, the" |
| | ratio | 0.219 | |
| 38.13% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 64 | | matches | | 0 | "Lucien Moreau's knuckles stilled on" | | 1 | "Someone didn't want unwelcome guests." | | 2 | "Rory Carter opened it a" | | 3 | "Her gaze narrowed at the" | | 4 | "The corners of his mouth" | | 5 | "She started to close the" | | 6 | "His heterochromatic eyes glinted knowingly" | | 7 | "Rory stared him down for" | | 8 | "The flat was a maze" | | 9 | "Ptolemy lifted his head and" | | 10 | "Lucien strode in, the ivory" | | 11 | "Rory closed the door with" | | 12 | "Lucien turned to face her," | | 13 | "Rory let out a sharp," | | 14 | "The Frenchman's expression darkened." | | 15 | "Rory's fingers tightened around the" | | 16 | "Lucien crossed the room to" | | 17 | "Rory asked, her voice carefully" | | 18 | "Lucien's eyes narrowed" | | 19 | "Rory felt the blood drain" |
| | ratio | 0.844 | |
| 78.13% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 64 | | matches | | 0 | "Whether she liked it or" |
| | ratio | 0.016 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 5 | | matches | | 0 | "She started, but his cane shot out, wedging it open" | | 1 | "Rory closed, the locks clicking back into place" | | 2 | "Rory asked, her voice carefully even" | | 3 | "She lifted, eyes narrowing" | | 4 | "His eyes gleamed, the scent of expensive cologne lingering in his wake" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "Rory murmured (murmur)" |
| | dialogueSentences | 41 | | tagDensity | 0.073 | | leniency | 0.146 | | rawRatio | 0.333 | | effectiveRatio | 0.049 | |