| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 33 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 71 | | tagDensity | 0.465 | | leniency | 0.93 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.24% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2049 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "perfectly" | | 1 | "very" | | 2 | "really" | | 3 | "suddenly" |
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| 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) | |
| 48.76% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2049 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "unreadable" | | 1 | "stomach" | | 2 | "traced" | | 3 | "intensity" | | 4 | "pulse" | | 5 | "perfect" | | 6 | "thundered" | | 7 | "eyebrow" | | 8 | "whisper" | | 9 | "familiar" | | 10 | "depths" | | 11 | "tenderness" | | 12 | "could feel" | | 13 | "effortless" | | 14 | "vibrated" | | 15 | "silk" | | 16 | "navigated" |
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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 | 150 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 150 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 188 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2049 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1388 | | uniqueNames | 17 | | maxNameDensity | 0.72 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Moreau | 1 | | Marseille | 1 | | Rory | 10 | | Three | 2 | | Lucien | 10 | | Amusement | 1 | | Earl | 1 | | Grey | 1 | | Formica | 1 | | Close | 2 | | French | 1 | | English | 1 | | Silas | 1 | | Simple | 1 | | Brick | 1 | | Lane | 1 | | Ptolemy | 3 |
| | persons | | 0 | "Moreau" | | 1 | "Rory" | | 2 | "Lucien" | | 3 | "Amusement" | | 4 | "Earl" | | 5 | "Grey" | | 6 | "Silas" | | 7 | "Ptolemy" |
| | places | | 0 | "Marseille" | | 1 | "Three" | | 2 | "French" | | 3 | "Brick" | | 4 | "Lane" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 102 | | 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 | 2049 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 188 | | matches | | 0 | "chose that moment" | | 1 | "chose that moment" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 73 | | mean | 28.07 | | std | 18.54 | | cv | 0.661 | | sampleLengths | | 0 | 46 | | 1 | 4 | | 2 | 65 | | 3 | 6 | | 4 | 31 | | 5 | 1 | | 6 | 28 | | 7 | 30 | | 8 | 52 | | 9 | 7 | | 10 | 25 | | 11 | 37 | | 12 | 2 | | 13 | 16 | | 14 | 1 | | 15 | 31 | | 16 | 24 | | 17 | 25 | | 18 | 23 | | 19 | 60 | | 20 | 20 | | 21 | 32 | | 22 | 31 | | 23 | 27 | | 24 | 44 | | 25 | 6 | | 26 | 52 | | 27 | 59 | | 28 | 5 | | 29 | 25 | | 30 | 15 | | 31 | 19 | | 32 | 72 | | 33 | 26 | | 34 | 10 | | 35 | 22 | | 36 | 22 | | 37 | 74 | | 38 | 20 | | 39 | 69 | | 40 | 20 | | 41 | 34 | | 42 | 1 | | 43 | 37 | | 44 | 23 | | 45 | 29 | | 46 | 51 | | 47 | 61 | | 48 | 5 | | 49 | 34 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 150 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 236 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 188 | | ratio | 0 | | matches | (empty) | |
| 98.62% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1395 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 58 | | adverbRatio | 0.04157706093189964 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.008602150537634409 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 188 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 188 | | mean | 10.9 | | std | 8.53 | | cv | 0.782 | | sampleLengths | | 0 | 10 | | 1 | 8 | | 2 | 13 | | 3 | 15 | | 4 | 4 | | 5 | 21 | | 6 | 8 | | 7 | 6 | | 8 | 13 | | 9 | 17 | | 10 | 6 | | 11 | 15 | | 12 | 12 | | 13 | 4 | | 14 | 1 | | 15 | 21 | | 16 | 7 | | 17 | 17 | | 18 | 2 | | 19 | 11 | | 20 | 19 | | 21 | 5 | | 22 | 17 | | 23 | 11 | | 24 | 7 | | 25 | 10 | | 26 | 8 | | 27 | 7 | | 28 | 2 | | 29 | 8 | | 30 | 11 | | 31 | 16 | | 32 | 2 | | 33 | 15 | | 34 | 1 | | 35 | 1 | | 36 | 19 | | 37 | 12 | | 38 | 3 | | 39 | 13 | | 40 | 8 | | 41 | 25 | | 42 | 10 | | 43 | 8 | | 44 | 5 | | 45 | 27 | | 46 | 9 | | 47 | 24 | | 48 | 4 | | 49 | 16 |
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| 60.64% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.3829787234042553 | | totalSentences | 188 | | uniqueOpeners | 72 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 130 | | matches | | 0 | "Instead she turned, finding him" | | 1 | "Then his mouth crashed down" | | 2 | "Just pure, unfiltered need that" | | 3 | "Then his mouth found hers" |
| | ratio | 0.031 | |
| 63.08% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 51 | | totalSentences | 130 | | matches | | 0 | "She already knew who waited" | | 1 | "She opened the door." | | 2 | "His ivory-handled cane rested against" | | 3 | "She noticed the faint tremor" | | 4 | "His voice carried the faint" | | 5 | "He tilted his head, platinum" | | 6 | "He smiled anyway, that small," | | 7 | "She stepped aside before she" | | 8 | "He surveyed the chaos with" | | 9 | "His mismatched eyes traced the" | | 10 | "She folded her arms, creating" | | 11 | "He set his cane against" | | 12 | "She filled the kettle, slammed" | | 13 | "She kept her back to" | | 14 | "His voice came from directly" | | 15 | "She laughed, the sound brittle" | | 16 | "His fingers brushed her elbow." | | 17 | "She should have pulled away." | | 18 | "His fingers traced the line" | | 19 | "She caught his wrist" |
| | ratio | 0.392 | |
| 29.23% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 112 | | totalSentences | 130 | | matches | | 0 | "Rory yanked the deadbolt back" | | 1 | "The second and third followed" | | 2 | "She already knew who waited" | | 3 | "The particular rhythm of those" | | 4 | "She opened the door." | | 5 | "Lucien Moreau filled the narrow" | | 6 | "The black one remained shadowed," | | 7 | "His ivory-handled cane rested against" | | 8 | "She noticed the faint tremor" | | 9 | "His voice carried the faint" | | 10 | "He tilted his head, platinum" | | 11 | "He smiled anyway, that small," | | 12 | "The tabby chose that moment" | | 13 | "She stepped aside before she" | | 14 | "Lucien moved past her with" | | 15 | "The flat swallowed him immediately." | | 16 | "Books and scrolls covered every" | | 17 | "He surveyed the chaos with" | | 18 | "Rory shut the door harder" | | 19 | "The movement brought them closer" |
| | ratio | 0.862 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 130 | | matches | (empty) | | ratio | 0 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 56 | | technicalSentenceCount | 4 | | matches | | 0 | "Held it against his chest where his heart thundered with something that felt dangerously like hope." | | 1 | "The black one held depths that had always terrified and fascinated her in equal measure." | | 2 | "The man who'd once carried her home from Silas's bar after too much whisky and tended her wrist scar with surprising tenderness when it ached in the rain." | | 3 | "Just pure, unfiltered need that matched the ache she'd carried since waking up alone." |
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| 94.70% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 33 | | uselessAdditionCount | 2 | | matches | | 0 | "She laughed, the sound brittle enough to cut" | | 1 | "she said, voice fierce," |
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| 93.66% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 4 | | fancyTags | | 0 | "She laughed (laugh)" | | 1 | "she whispered (whisper)" | | 2 | "she demanded (demand)" | | 3 | "she gasped (gasp)" |
| | dialogueSentences | 71 | | tagDensity | 0.113 | | leniency | 0.225 | | rawRatio | 0.5 | | effectiveRatio | 0.113 | |