| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 2 | | adverbTags | | 0 | "he said quietly [quietly]" | | 1 | "he said softly [softly]" |
| | dialogueSentences | 40 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.2 | | effectiveRatio | 0.1 | |
| 85.32% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1022 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "suddenly" | | 1 | "slowly" | | 2 | "softly" |
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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) | |
| 55.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1022 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "echoed" | | 1 | "tracing" | | 2 | "flickered" | | 3 | "silence" | | 4 | "weight" | | 5 | "raced" | | 6 | "calculating" | | 7 | "trembled" |
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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 | 67 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 67 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 97 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1022 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 99.32% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 592 | | uniqueNames | 10 | | maxNameDensity | 1.01 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 6 | | Moreau | 1 | | Yu-Fei | 1 | | Cheung | 1 | | Golden | 1 | | Empress | 1 | | Cardiff | 1 | | University | 1 | | Evan | 1 | | Lucien | 6 |
| | persons | | 0 | "Rory" | | 1 | "Moreau" | | 2 | "Yu-Fei" | | 3 | "Cheung" | | 4 | "University" | | 5 | "Evan" | | 6 | "Lucien" |
| | places | | | globalScore | 0.993 | | windowScore | 1 | |
| 25.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | glossingSentenceCount | 2 | | matches | | 0 | "as if remembering older, colder touches" | | 1 | "felt like thin armour against something" |
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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 | 1022 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 97 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 19.28 | | std | 16.92 | | cv | 0.877 | | sampleLengths | | 0 | 11 | | 1 | 64 | | 2 | 11 | | 3 | 79 | | 4 | 9 | | 5 | 6 | | 6 | 71 | | 7 | 21 | | 8 | 6 | | 9 | 8 | | 10 | 20 | | 11 | 5 | | 12 | 32 | | 13 | 13 | | 14 | 37 | | 15 | 44 | | 16 | 5 | | 17 | 15 | | 18 | 17 | | 19 | 48 | | 20 | 4 | | 21 | 19 | | 22 | 9 | | 23 | 18 | | 24 | 22 | | 25 | 36 | | 26 | 11 | | 27 | 6 | | 28 | 13 | | 29 | 4 | | 30 | 23 | | 31 | 11 | | 32 | 5 | | 33 | 2 | | 34 | 21 | | 35 | 7 | | 36 | 6 | | 37 | 6 | | 38 | 35 | | 39 | 32 | | 40 | 2 | | 41 | 20 | | 42 | 29 | | 43 | 4 | | 44 | 18 | | 45 | 30 | | 46 | 10 | | 47 | 9 | | 48 | 25 | | 49 | 20 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 67 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 101 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 97 | | ratio | 0.01 | | matches | | 0 | "One amber eye caught the hallway light; the other, black as obsidian, swallowed it whole." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 479 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 14 | | adverbRatio | 0.029227557411273485 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.008350730688935281 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 97 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 97 | | mean | 10.54 | | std | 7.15 | | cv | 0.679 | | sampleLengths | | 0 | 11 | | 1 | 14 | | 2 | 25 | | 3 | 15 | | 4 | 10 | | 5 | 6 | | 6 | 5 | | 7 | 6 | | 8 | 6 | | 9 | 18 | | 10 | 30 | | 11 | 19 | | 12 | 5 | | 13 | 4 | | 14 | 6 | | 15 | 3 | | 16 | 3 | | 17 | 2 | | 18 | 14 | | 19 | 10 | | 20 | 19 | | 21 | 20 | | 22 | 6 | | 23 | 15 | | 24 | 6 | | 25 | 2 | | 26 | 6 | | 27 | 20 | | 28 | 5 | | 29 | 13 | | 30 | 19 | | 31 | 13 | | 32 | 9 | | 33 | 10 | | 34 | 18 | | 35 | 8 | | 36 | 36 | | 37 | 5 | | 38 | 15 | | 39 | 3 | | 40 | 14 | | 41 | 3 | | 42 | 19 | | 43 | 14 | | 44 | 12 | | 45 | 4 | | 46 | 19 | | 47 | 3 | | 48 | 6 | | 49 | 18 |
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| 50.17% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.35051546391752575 | | totalSentences | 97 | | uniqueOpeners | 34 | |
| 59.52% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 56 | | matches | | 0 | "Instead, she leaned against the" |
| | ratio | 0.018 | |
| 77.14% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 56 | | matches | | 0 | "He smiled, and the expression" | | 1 | "She should have slammed the" | | 2 | "Her delivery jacket still reeked" | | 3 | "She stepped back." | | 4 | "Her law books from Cardiff" | | 5 | "He crossed the threshold without" | | 6 | "He turned, his heterochromatic gaze" | | 7 | "He set the cane against" | | 8 | "he said quietly" | | 9 | "She laughed, brittle." | | 10 | "He moved closer." | | 11 | "His height, five feet eleven," | | 12 | "She tilted her chin up," | | 13 | "He reached out slowly, giving" | | 14 | "His fingers, long and precise," | | 15 | "His touch was cool, not" | | 16 | "he said softly" | | 17 | "Her eyes widened." | | 18 | "She pulled her wrist back," | | 19 | "She looked at him, hurt" |
| | ratio | 0.357 | |
| 40.36% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 56 | | matches | | 0 | "The door swung open before" | | 1 | "Lucien Moreau filled the corridor" | | 2 | "Platinum hair slicked back against" | | 3 | "He smiled, and the expression" | | 4 | "Rory's heart hammered against her" | | 5 | "She should have slammed the" | | 6 | "Her delivery jacket still reeked" | | 7 | "The small crescent-shaped scar on" | | 8 | "She stepped back." | | 9 | "The flat above" | | 10 | "A single bulb cast yellow" | | 11 | "Her law books from Cardiff" | | 12 | "The air smelled of cold" | | 13 | "He crossed the threshold without" | | 14 | "The cane clicked behind him," | | 15 | "He turned, his heterochromatic gaze" | | 16 | "The words hung between them," | | 17 | "Lucien's jaw tightened beneath the" | | 18 | "He set the cane against" | | 19 | "he said quietly" |
| | ratio | 0.839 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 44.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 4 | | matches | | 0 | "The small crescent-shaped scar on her left wrist, pale and old, itched suddenly, as if remembering older, colder touches." | | 1 | "The air smelled of cold chamomile tea and something darker, something that slipped inside with Lucien and refused to leave." | | 2 | "The charcoal suit smelled of cedar and old smoke, the kind that clung to supernatural bargains in back rooms." | | 3 | "The doorknob turned from the outside, slow and deliberate, testing the weight of the lock that wasn't there." |
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| 75.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 1 | | matches | | 0 | "He turned, his heterochromatic gaze pinning her to the spot" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 40 | | tagDensity | 0.225 | | leniency | 0.45 | | rawRatio | 0.111 | | effectiveRatio | 0.05 | |