| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.13% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1292 | | 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) | |
| 45.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1292 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "flicked" | | 1 | "marble" | | 2 | "porcelain" | | 3 | "echoed" | | 4 | "echoing" | | 5 | "silence" | | 6 | "pulse" | | 7 | "trembled" | | 8 | "race" | | 9 | "footsteps" | | 10 | "warmth" | | 11 | "tension" |
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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 | 187 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 1 | | narrationSentences | 187 | | filterMatches | | 0 | "look" | | 1 | "know" | | 2 | "think" | | 3 | "hear" |
| | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 187 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1292 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 8 | | matches | | 0 | "You look like you swallowed a hornet, he said." | | 1 | "I saw you coming, Aurora replied." | | 2 | "You always brace for impact, he murmured." | | 3 | "Three months, he said." | | 4 | "The case is closed, she said." | | 5 | "You were right, she whispered." | | 6 | "If I come with you, she said quietly, the deal stays off the table." | | 7 | "Fetch your coat, he said." |
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| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 56 | | wordCount | 1292 | | uniqueNames | 19 | | maxNameDensity | 1.01 | | worstName | "You" | | maxWindowNameDensity | 2.5 | | worstWindowName | "You" | | discoveredNames | | Marseille | 2 | | East | 1 | | London | 1 | | Aurora | 8 | | Lucien | 8 | | Lane | 2 | | Soho | 1 | | Eva | 2 | | Deptford | 1 | | Cardiff | 1 | | England | 1 | | Yu-Fei | 1 | | Evan | 3 | | Southwark | 1 | | Birmingham | 1 | | Brick | 2 | | Ptolemy | 4 | | You | 13 | | Safe | 3 |
| | persons | | 0 | "Aurora" | | 1 | "Lucien" | | 2 | "Eva" | | 3 | "Evan" | | 4 | "Ptolemy" | | 5 | "You" | | 6 | "Safe" |
| | places | | 0 | "Marseille" | | 1 | "East" | | 2 | "London" | | 3 | "Lane" | | 4 | "Soho" | | 5 | "Deptford" | | 6 | "Cardiff" | | 7 | "England" | | 8 | "Southwark" | | 9 | "Birmingham" | | 10 | "Brick" |
| | globalScore | 0.997 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 94 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like I was stealing sunlight I did" |
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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 | 1292 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 187 | | matches | | 0 | "carried that Marseille" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 30.76 | | std | 17.6 | | cv | 0.572 | | sampleLengths | | 0 | 17 | | 1 | 62 | | 2 | 41 | | 3 | 28 | | 4 | 27 | | 5 | 22 | | 6 | 62 | | 7 | 7 | | 8 | 17 | | 9 | 20 | | 10 | 70 | | 11 | 26 | | 12 | 47 | | 13 | 14 | | 14 | 16 | | 15 | 49 | | 16 | 12 | | 17 | 30 | | 18 | 35 | | 19 | 6 | | 20 | 27 | | 21 | 35 | | 22 | 36 | | 23 | 43 | | 24 | 19 | | 25 | 41 | | 26 | 23 | | 27 | 40 | | 28 | 4 | | 29 | 32 | | 30 | 50 | | 31 | 79 | | 32 | 36 | | 33 | 10 | | 34 | 54 | | 35 | 22 | | 36 | 28 | | 37 | 7 | | 38 | 32 | | 39 | 11 | | 40 | 34 | | 41 | 21 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 187 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 274 | | matches | | 0 | "weren't asking" | | 1 | "was stealing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 187 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1295 | | adjectiveStacks | 1 | | stackExamples | | 0 | "under leather-bound journals." |
| | adverbCount | 43 | | adverbRatio | 0.033204633204633204 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.003088803088803089 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 187 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 187 | | mean | 6.91 | | std | 4.73 | | cv | 0.685 | | sampleLengths | | 0 | 9 | | 1 | 8 | | 2 | 6 | | 3 | 13 | | 4 | 8 | | 5 | 17 | | 6 | 18 | | 7 | 6 | | 8 | 11 | | 9 | 14 | | 10 | 10 | | 11 | 9 | | 12 | 19 | | 13 | 6 | | 14 | 8 | | 15 | 13 | | 16 | 3 | | 17 | 3 | | 18 | 2 | | 19 | 10 | | 20 | 4 | | 21 | 6 | | 22 | 11 | | 23 | 6 | | 24 | 13 | | 25 | 26 | | 26 | 3 | | 27 | 4 | | 28 | 11 | | 29 | 6 | | 30 | 8 | | 31 | 4 | | 32 | 5 | | 33 | 3 | | 34 | 12 | | 35 | 26 | | 36 | 2 | | 37 | 22 | | 38 | 5 | | 39 | 3 | | 40 | 6 | | 41 | 15 | | 42 | 5 | | 43 | 7 | | 44 | 5 | | 45 | 13 | | 46 | 9 | | 47 | 8 | | 48 | 5 | | 49 | 1 |
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| 53.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.37433155080213903 | | totalSentences | 187 | | uniqueOpeners | 70 | |
| 80.81% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 165 | | matches | | 0 | "Then the third." | | 1 | "Then be tired of safe." | | 2 | "Just you and me and" | | 3 | "Somewhere downstairs, a customer slammed" |
| | ratio | 0.024 | |
| 47.88% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 71 | | totalSentences | 165 | | matches | | 0 | "He held himself upright despite" | | 1 | "His heterochromatic eyes caught the" | | 2 | "She should have closed the" | | 3 | "Her hand stayed wrapped around" | | 4 | "You look like you swallowed" | | 5 | "His voice carried that Marseille" | | 6 | "I saw you coming, Aurora" | | 7 | "She kept her stance planted," | | 8 | "I just haven't decided whether" | | 9 | "His lips quirked." | | 10 | "He stepped forward anyway, forcing" | | 11 | "He smelled of wet wool," | | 12 | "She stepped aside." | | 13 | "He crossed the threshold." | | 14 | "She shut the door." | | 15 | "His gaze swept the room," | | 16 | "You still live among debris." | | 17 | "You prefer marble floors and" | | 18 | "She filled the kettle, watching" | | 19 | "She flipped the switch." |
| | ratio | 0.43 | |
| 63.03% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 131 | | totalSentences | 165 | | matches | | 0 | "The deadbolts clacked back, metal" | | 1 | "Aurora pulled the door wide" | | 2 | "Lucien stood in the stairwell" | | 3 | "Rain darkened his charcoal suit," | | 4 | "Water droplets tracked the line" | | 5 | "He held himself upright despite" | | 6 | "His heterochromatic eyes caught the" | | 7 | "She should have closed the" | | 8 | "Her hand stayed wrapped around" | | 9 | "The smell of cumin and" | | 10 | "Ptolemy yowled from somewhere inside" | | 11 | "You look like you swallowed" | | 12 | "His voice carried that Marseille" | | 13 | "I saw you coming, Aurora" | | 14 | "She kept her stance planted," | | 15 | "I just haven't decided whether" | | 16 | "His lips quirked." | | 17 | "The police would arrest me" | | 18 | "The floorboards groaned under unfamiliar" | | 19 | "He stepped forward anyway, forcing" |
| | ratio | 0.794 | |
| 90.91% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 165 | | matches | | 0 | "Even when nothing touches you." | | 1 | "Because every time you smiled," | | 2 | "If I come with you," |
| | ratio | 0.018 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 1 | | matches | | 0 | "The same syndicate that bought Evan's debts resurfaced in Southwark." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |