| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 101 | | tagDensity | 0.02 | | leniency | 0.04 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2324 | | totalAiIsmAdverbs | 1 | | 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) | |
| 65.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2324 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "flicker" | | 1 | "weight" | | 2 | "comforting" | | 3 | "warmth" | | 4 | "silk" | | 5 | "charm" | | 6 | "pulse" | | 7 | "perfect" | | 8 | "unsettled" | | 9 | "charged" | | 10 | "traced" | | 11 | "tenderness" |
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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 | 171 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 171 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 271 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2324 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 96.40% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 1679 | | uniqueNames | 6 | | maxNameDensity | 1.07 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Lucien | 13 | | Moreau | 1 | | Eva | 6 | | Ptolemy | 6 | | Thames | 1 | | Aurora | 18 |
| | persons | | 0 | "Lucien" | | 1 | "Moreau" | | 2 | "Eva" | | 3 | "Ptolemy" | | 4 | "Aurora" |
| | places | | | globalScore | 0.964 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 115 | | 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 | 2324 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 271 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 185 | | mean | 12.56 | | std | 15.04 | | cv | 1.198 | | sampleLengths | | 0 | 37 | | 1 | 47 | | 2 | 5 | | 3 | 6 | | 4 | 13 | | 5 | 3 | | 6 | 10 | | 7 | 31 | | 8 | 28 | | 9 | 3 | | 10 | 5 | | 11 | 16 | | 12 | 13 | | 13 | 6 | | 14 | 10 | | 15 | 62 | | 16 | 6 | | 17 | 15 | | 18 | 4 | | 19 | 4 | | 20 | 10 | | 21 | 5 | | 22 | 53 | | 23 | 42 | | 24 | 4 | | 25 | 8 | | 26 | 4 | | 27 | 59 | | 28 | 3 | | 29 | 9 | | 30 | 16 | | 31 | 3 | | 32 | 12 | | 33 | 49 | | 34 | 23 | | 35 | 3 | | 36 | 9 | | 37 | 6 | | 38 | 5 | | 39 | 5 | | 40 | 4 | | 41 | 31 | | 42 | 3 | | 43 | 38 | | 44 | 6 | | 45 | 4 | | 46 | 3 | | 47 | 10 | | 48 | 14 | | 49 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 171 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 267 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 271 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1138 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.029876977152899824 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0017574692442882249 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 271 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 271 | | mean | 8.58 | | std | 7.26 | | cv | 0.846 | | sampleLengths | | 0 | 37 | | 1 | 6 | | 2 | 27 | | 3 | 9 | | 4 | 5 | | 5 | 5 | | 6 | 6 | | 7 | 13 | | 8 | 3 | | 9 | 10 | | 10 | 14 | | 11 | 17 | | 12 | 28 | | 13 | 3 | | 14 | 5 | | 15 | 7 | | 16 | 5 | | 17 | 4 | | 18 | 13 | | 19 | 6 | | 20 | 10 | | 21 | 6 | | 22 | 8 | | 23 | 8 | | 24 | 40 | | 25 | 6 | | 26 | 15 | | 27 | 4 | | 28 | 4 | | 29 | 10 | | 30 | 5 | | 31 | 22 | | 32 | 13 | | 33 | 10 | | 34 | 8 | | 35 | 31 | | 36 | 11 | | 37 | 4 | | 38 | 8 | | 39 | 4 | | 40 | 27 | | 41 | 9 | | 42 | 8 | | 43 | 15 | | 44 | 3 | | 45 | 9 | | 46 | 16 | | 47 | 3 | | 48 | 5 | | 49 | 5 |
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| 45.57% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.26199261992619927 | | totalSentences | 271 | | uniqueOpeners | 71 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 156 | | matches | | 0 | "Then he swayed." | | 1 | "Of course he did." | | 2 | "Then morning had come, and" | | 3 | "Just warmth around the scar." | | 4 | "Somewhere in the flat a" | | 5 | "Then his other hand came" |
| | ratio | 0.038 | |
| 40.51% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 70 | | totalSentences | 156 | | matches | | 0 | "It darkened the shoulders of" | | 1 | "His mouth twitched, though the" | | 2 | "His gloved hand tightened on" | | 3 | "She should have shut the" | | 4 | "She knew the exact weight" | | 5 | "She looked at the blood" | | 6 | "He lifted his chin." | | 7 | "She slid the chain free" | | 8 | "He crossed the threshold with" | | 9 | "She shut the door fast" | | 10 | "His face had lost none" | | 11 | "His cheekbones still looked cut" | | 12 | "His mouth still carried that" | | 13 | "His jacket felt soaked through." | | 14 | "She shoved him towards the" | | 15 | "She snapped the tin open." | | 16 | "His hand moved to his" | | 17 | "She stepped in, slapped his" | | 18 | "He watched her with that" | | 19 | "His mouth almost curved." |
| | ratio | 0.449 | |
| 30.51% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 134 | | totalSentences | 156 | | matches | | 0 | "The door opened on the" | | 1 | "Rain clung to his slicked-back" | | 2 | "It darkened the shoulders of" | | 3 | "The other drank it whole." | | 4 | "Aurora kept the chain hooked." | | 5 | "His mouth twitched, though the" | | 6 | "Lucien dipped his head, gaze" | | 7 | "His gloved hand tightened on" | | 8 | "Rain slid from his cuff." | | 9 | "Something darker followed it." | | 10 | "Aurora dropped her gaze to" | | 11 | "She should have shut the" | | 12 | "She knew the exact weight" | | 13 | "She looked at the blood" | | 14 | "He lifted his chin." | | 15 | "She slid the chain free" | | 16 | "He crossed the threshold with" | | 17 | "Lucien never showed damage unless" | | 18 | "She shut the door fast" | | 19 | "Metal knocked into place, one" |
| | ratio | 0.859 | |
| 32.05% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 156 | | matches | | 0 | "To the small crescent scar" |
| | ratio | 0.006 | |
| 76.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 65 | | technicalSentenceCount | 6 | | matches | | 0 | "The door opened on the chain first, a narrow slice of dim hallway and wet brick and Lucien Moreau standing under the flicker of the landing light as if the buil…" | | 1 | "His mouth still carried that hard, deliberate shape that had haunted her at inconvenient hours." | | 2 | "Lucien nudged a stack of notes aside with the tip of his cane and sat with care that cost him." | | 3 | "Evan’s face flashed up, then the uglier faces that had come after she slipped into Lucien’s world: creatures with human smiles and butcher’s appetites, men who …" | | 4 | "Ptolemy jumped from the microwave to the windowsill and began washing one paw with deep concentration, as if the room had finally grown interesting." | | 5 | "Lucien rested his forehead against hers, eyes shut, one hand still spread at her waist as if he had found something solid in a city built on bargains." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 101 | | tagDensity | 0.01 | | leniency | 0.02 | | rawRatio | 1 | | effectiveRatio | 0.02 | |