| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.36% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1078 | | 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) | |
| 44.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1078 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "raced" | | 1 | "dancing" | | 2 | "footsteps" | | 3 | "echoing" | | 4 | "silence" | | 5 | "scanning" | | 6 | "perfect" | | 7 | "grave" | | 8 | "racing" | | 9 | "navigate" | | 10 | "sense of" |
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| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "sense of foreboding" | | count | 1 |
| | 1 | | label | "air was thick with" | | count | 1 |
| | 2 | | label | "couldn't help but" | | count | 1 |
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| | highlights | | 0 | "a sense of unease" | | 1 | "The air was thick with" | | 2 | "couldn't help but feel" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 87 | | matches | | 0 | "e with fear" | | 1 | "a sense of unease" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 87 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1078 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 30.46% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 962 | | uniqueNames | 7 | | maxNameDensity | 2.39 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 2 | | Quinn | 23 | | Soho | 1 | | Detective | 2 | | Raven | 2 | | Nest | 2 | | Herrera | 8 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Herrera" |
| | places | | | globalScore | 0.305 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared in front of them, his eyes wide with fear" |
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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 | 1078 | | matches | (empty) | |
| 61.40% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 95 | | matches | | 0 | "suspected that the" | | 1 | "let that stop" | | 2 | "feeling that this" |
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| 60.55% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 29.14 | | std | 10.55 | | cv | 0.362 | | sampleLengths | | 0 | 37 | | 1 | 37 | | 2 | 53 | | 3 | 44 | | 4 | 32 | | 5 | 31 | | 6 | 32 | | 7 | 37 | | 8 | 15 | | 9 | 32 | | 10 | 39 | | 11 | 19 | | 12 | 31 | | 13 | 26 | | 14 | 29 | | 15 | 36 | | 16 | 38 | | 17 | 20 | | 18 | 53 | | 19 | 30 | | 20 | 22 | | 21 | 29 | | 22 | 12 | | 23 | 31 | | 24 | 15 | | 25 | 19 | | 26 | 19 | | 27 | 32 | | 28 | 25 | | 29 | 18 | | 30 | 21 | | 31 | 18 | | 32 | 31 | | 33 | 41 | | 34 | 14 | | 35 | 15 | | 36 | 45 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 87 | | matches | (empty) | |
| 40.32% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 167 | | matches | | 0 | "was going" | | 1 | "was going" | | 2 | "was closing" | | 3 | "were making" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 95 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 964 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.02074688796680498 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.004149377593360996 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 11.35 | | std | 5.47 | | cv | 0.482 | | sampleLengths | | 0 | 15 | | 1 | 22 | | 2 | 10 | | 3 | 13 | | 4 | 14 | | 5 | 14 | | 6 | 24 | | 7 | 15 | | 8 | 14 | | 9 | 17 | | 10 | 3 | | 11 | 10 | | 12 | 7 | | 13 | 13 | | 14 | 12 | | 15 | 7 | | 16 | 13 | | 17 | 11 | | 18 | 9 | | 19 | 15 | | 20 | 8 | | 21 | 11 | | 22 | 14 | | 23 | 12 | | 24 | 4 | | 25 | 11 | | 26 | 19 | | 27 | 13 | | 28 | 14 | | 29 | 3 | | 30 | 22 | | 31 | 9 | | 32 | 10 | | 33 | 2 | | 34 | 17 | | 35 | 12 | | 36 | 5 | | 37 | 13 | | 38 | 8 | | 39 | 11 | | 40 | 18 | | 41 | 8 | | 42 | 18 | | 43 | 10 | | 44 | 8 | | 45 | 12 | | 46 | 18 | | 47 | 11 | | 48 | 9 | | 49 | 15 |
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| 40.53% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.2 | | totalSentences | 95 | | uniqueOpeners | 19 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 83 | | matches | (empty) | | ratio | 0 | |
| 75.42% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 83 | | matches | | 0 | "She couldn't let him escape," | | 1 | "Her name is Detective Harlow" | | 2 | "She suspected that the killer" | | 3 | "She'd been here before, but" | | 4 | "She had to get closer," | | 5 | "She edged forward, keeping to" | | 6 | "She elbowed her way through" | | 7 | "She had to hurry." | | 8 | "He stopped at a bookshelf," | | 9 | "She made up her mind." | | 10 | "She had to know where" | | 11 | "She'd come too far to" | | 12 | "She followed the corridor, her" | | 13 | "She had no idea where" | | 14 | "She was in a cavern," | | 15 | "She caught a glimpse of" | | 16 | "She was closing in on" | | 17 | "She spun around, her hand" | | 18 | "She'd met Herrera before, during" | | 19 | "He'd always struck her as" |
| | ratio | 0.361 | |
| 8.19% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 83 | | matches | | 0 | "Detective Harlow Quinn pounded the" | | 1 | "Quinn raced after him, her" | | 2 | "The suspect was quick, but" | | 3 | "She couldn't let him escape," | | 4 | "Her name is Detective Harlow" | | 5 | "The murder of a prominent" | | 6 | "She suspected that the killer" | | 7 | "The alley was narrow and" | | 8 | "A faint green glow emanated" | | 9 | "The Raven's Nest." | | 10 | "She'd been here before, but" | | 11 | "Quinn reached for her radio," | | 12 | "She had to get closer," | | 13 | "She edged forward, keeping to" | | 14 | "The suspect had stopped at" | | 15 | "Quinn held her breath, waiting" | | 16 | "The door swung open, spilling" | | 17 | "Quinn caught a glimpse of" | | 18 | "The suspect slipped inside, merging" | | 19 | "Quinn followed, her hand resting" |
| | ratio | 0.904 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 83 | | matches | | 0 | "If she called for backup" | | 1 | "If she lost him now," | | 2 | "If she followed him through" |
| | ratio | 0.036 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 1 | | matches | | 0 | "Stalls and booths crowded the floor, merchants hawking their wares to the crowds that thronged the aisles." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 3 | | matches | | 0 | "Tomás Herrera said, his face grave" | | 1 | "she said, her voice low" | | 2 | "she said, her voice harsh" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |