| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 25 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 156 | | tagDensity | 0.16 | | leniency | 0.321 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.41% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2329 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "quickly" | | 1 | "slowly" | | 2 | "very" | | 3 | "suddenly" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 82.83% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2329 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "familiar" | | 1 | "flickered" | | 2 | "tracing" | | 3 | "affection" | | 4 | "vibrated" | | 5 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 177 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 177 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 307 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2329 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 36 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 117 | | wordCount | 1558 | | uniqueNames | 13 | | maxNameDensity | 3.15 | | worstName | "Nia" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Rory" | | discoveredNames | | Aurora | 1 | | Golden | 2 | | Empress | 2 | | Carter | 3 | | Yu-Fei | 1 | | Miss | 1 | | Rory | 48 | | Nia | 49 | | London | 2 | | Mum | 1 | | Evan | 1 | | Thursday | 2 | | Silas | 4 |
| | persons | | 0 | "Carter" | | 1 | "Rory" | | 2 | "Nia" | | 3 | "Mum" | | 4 | "Evan" | | 5 | "Silas" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 110 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like an excuse people made when th" |
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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 | 2329 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 307 | | matches | | 0 | "confessed that she" | | 1 | "disliked that explanation" | | 2 | "used that word" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 216 | | mean | 10.78 | | std | 13.45 | | cv | 1.248 | | sampleLengths | | 0 | 26 | | 1 | 1 | | 2 | 19 | | 3 | 49 | | 4 | 46 | | 5 | 1 | | 6 | 33 | | 7 | 6 | | 8 | 19 | | 9 | 4 | | 10 | 3 | | 11 | 5 | | 12 | 60 | | 13 | 36 | | 14 | 7 | | 15 | 3 | | 16 | 1 | | 17 | 9 | | 18 | 5 | | 19 | 34 | | 20 | 3 | | 21 | 2 | | 22 | 3 | | 23 | 13 | | 24 | 8 | | 25 | 3 | | 26 | 20 | | 27 | 3 | | 28 | 7 | | 29 | 2 | | 30 | 1 | | 31 | 7 | | 32 | 13 | | 33 | 2 | | 34 | 26 | | 35 | 60 | | 36 | 4 | | 37 | 3 | | 38 | 10 | | 39 | 5 | | 40 | 2 | | 41 | 57 | | 42 | 6 | | 43 | 20 | | 44 | 40 | | 45 | 2 | | 46 | 5 | | 47 | 2 | | 48 | 3 | | 49 | 3 |
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| 99.32% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 177 | | matches | | 0 | "was annoyed" | | 1 | "being seen" | | 2 | "been forgiven" |
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| 93.84% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 314 | | matches | | 0 | "was carrying" | | 1 | "was polishing" | | 2 | "was reading" | | 3 | "was watching" | | 4 | "was wiping" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 307 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1563 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 51 | | adverbRatio | 0.03262955854126679 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.005758157389635317 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 307 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 307 | | mean | 7.59 | | std | 6.22 | | cv | 0.82 | | sampleLengths | | 0 | 26 | | 1 | 1 | | 2 | 7 | | 3 | 12 | | 4 | 6 | | 5 | 22 | | 6 | 14 | | 7 | 1 | | 8 | 6 | | 9 | 15 | | 10 | 5 | | 11 | 26 | | 12 | 1 | | 13 | 17 | | 14 | 5 | | 15 | 11 | | 16 | 3 | | 17 | 3 | | 18 | 7 | | 19 | 12 | | 20 | 4 | | 21 | 3 | | 22 | 5 | | 23 | 6 | | 24 | 33 | | 25 | 21 | | 26 | 10 | | 27 | 17 | | 28 | 9 | | 29 | 7 | | 30 | 3 | | 31 | 1 | | 32 | 9 | | 33 | 5 | | 34 | 7 | | 35 | 9 | | 36 | 18 | | 37 | 3 | | 38 | 2 | | 39 | 3 | | 40 | 13 | | 41 | 8 | | 42 | 3 | | 43 | 20 | | 44 | 3 | | 45 | 4 | | 46 | 3 | | 47 | 2 | | 48 | 1 | | 49 | 5 |
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| 45.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.2964169381107492 | | totalSentences | 307 | | uniqueOpeners | 91 | |
| 93.24% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 143 | | matches | | 0 | "Perhaps she had been." | | 1 | "Instead Rory said," | | 2 | "Then she went left, briskly," | | 3 | "Then she put the phone" |
| | ratio | 0.028 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 143 | | matches | | 0 | "She stopped beside the last" | | 1 | "Her hair had been cut" | | 2 | "She picked it up again." | | 3 | "They had once slept in" | | 4 | "His gaze passed from her" | | 5 | "His silver signet ring clicked" | | 6 | "They smiled at each other." | | 7 | "He moved away with his" | | 8 | "They took the table beneath" | | 9 | "Her nails were short and" | | 10 | "She had worn them bitten" | | 11 | "It had flickered steadily until" | | 12 | "She had owned one pair" | | 13 | "She had disliked that explanation" | | 14 | "It had sounded like an" | | 15 | "She had read the message" | | 16 | "She had typed I’m so" | | 17 | "He did not look at" | | 18 | "It was a small kindness." | | 19 | "She touched the small crescent" |
| | ratio | 0.217 | |
| 78.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 109 | | totalSentences | 143 | | matches | | 0 | "Rory was carrying a bowl" | | 1 | "She stopped beside the last" | | 2 | "Juice slipped over the rim" | | 3 | "The woman by the door" | | 4 | "Her hair had been cut" | | 5 | "The woman smiled, and there" | | 6 | "Rory had forgotten the smile." | | 7 | "Rory set the bowl on" | | 8 | "The man sitting there looked" | | 9 | "She picked it up again." | | 10 | "Rory was conscious of her" | | 11 | "Nia stepped forward and kissed" | | 12 | "They had once slept in" | | 13 | "This careful contact felt more" | | 14 | "Nia laughed a second late." | | 15 | "Rory took the limes to" | | 16 | "Silas looked up from the" | | 17 | "His gaze passed from her" | | 18 | "His silver signet ring clicked" | | 19 | "Rory asked Nia" |
| | ratio | 0.762 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 143 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 66 | | technicalSentenceCount | 1 | | matches | | 0 | "Rory had been in Evan’s kitchen, waiting for him to finish telling her why she had embarrassed him in front of his friends." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 25 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 23 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 156 | | tagDensity | 0.147 | | leniency | 0.295 | | rawRatio | 0 | | effectiveRatio | 0 | |