| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.571 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 61.18% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 644 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "quickly" | | 2 | "suddenly" | | 3 | "truly" |
| |
| 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) | |
| 22.36% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 644 | | totalAiIsms | 10 | | found | | 0 | | word | "practiced ease" | | count | 1 |
| | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | |
| | highlights | | 0 | "practiced ease" | | 1 | "disrupted" | | 2 | "scanned" | | 3 | "flickered" | | 4 | "methodical" | | 5 | "traced" | | 6 | "echoes" | | 7 | "flicker" |
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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 | 56 | | matches | (empty) | |
| 91.84% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 56 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 62 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 19 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 639 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 61.35% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 564 | | uniqueNames | 9 | | maxNameDensity | 1.77 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 10 | | Soho | 1 | | Morris | 2 | | Raven | 1 | | Nest | 1 | | London | 1 | | Underground | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Raven" | | 3 | "Market" |
| | places | | | globalScore | 0.613 | | windowScore | 1 | |
| 95.65% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed slightly misaligned" |
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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 | 639 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 62 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 22 | | mean | 29.05 | | std | 15.73 | | cv | 0.542 | | sampleLengths | | 0 | 51 | | 1 | 9 | | 2 | 57 | | 3 | 35 | | 4 | 47 | | 5 | 16 | | 6 | 8 | | 7 | 20 | | 8 | 41 | | 9 | 17 | | 10 | 11 | | 11 | 11 | | 12 | 28 | | 13 | 12 | | 14 | 47 | | 15 | 37 | | 16 | 36 | | 17 | 46 | | 18 | 48 | | 19 | 22 | | 20 | 30 | | 21 | 10 |
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| 99.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 56 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 103 | | matches | (empty) | |
| 96.77% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 62 | | ratio | 0.016 | | matches | | 0 | "Her target—a wiry man in a hoodie—ducked into an alley between two brick buildings." |
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| 93.48% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 569 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.04745166959578207 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.019332161687170474 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 62 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 62 | | mean | 10.31 | | std | 4.54 | | cv | 0.44 | | sampleLengths | | 0 | 19 | | 1 | 14 | | 2 | 18 | | 3 | 9 | | 4 | 13 | | 5 | 16 | | 6 | 13 | | 7 | 15 | | 8 | 7 | | 9 | 1 | | 10 | 16 | | 11 | 11 | | 12 | 10 | | 13 | 16 | | 14 | 11 | | 15 | 1 | | 16 | 9 | | 17 | 16 | | 18 | 8 | | 19 | 15 | | 20 | 5 | | 21 | 9 | | 22 | 17 | | 23 | 15 | | 24 | 11 | | 25 | 6 | | 26 | 7 | | 27 | 4 | | 28 | 8 | | 29 | 3 | | 30 | 10 | | 31 | 10 | | 32 | 8 | | 33 | 6 | | 34 | 6 | | 35 | 3 | | 36 | 15 | | 37 | 13 | | 38 | 16 | | 39 | 8 | | 40 | 12 | | 41 | 14 | | 42 | 3 | | 43 | 12 | | 44 | 15 | | 45 | 9 | | 46 | 14 | | 47 | 16 | | 48 | 4 | | 49 | 8 |
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| 74.19% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.4838709677419355 | | totalSentences | 62 | | uniqueOpeners | 30 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 53 | | matches | | 0 | "Just for a second." | | 1 | "Once she left the relative" |
| | ratio | 0.038 | |
| 99.25% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 53 | | matches | | 0 | "Her target—a wiry man in" | | 1 | "she shouted, knowing it was" | | 2 | "She swore under her breath," | | 3 | "She pushed the door open," | | 4 | "He set the glass down" | | 5 | "She scanned the room again," | | 6 | "She turned to leave, then" | | 7 | "She moved toward the bookshelf," | | 8 | "Her fingers traced the edges" | | 9 | "She stepped into the darkness," | | 10 | "Her suspect moved through the" | | 11 | "She hesitated at the entrance," | | 12 | "she whispered to herself" | | 13 | "Her suspect had paused at" | | 14 | "Their eyes met across the" | | 15 | "He smiled, then disappeared around" |
| | ratio | 0.302 | |
| 26.04% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 46 | | totalSentences | 53 | | matches | | 0 | "Harlow Quinn's feet pounded against" | | 1 | "Her target—a wiry man in" | | 2 | "The rain had turned his" | | 3 | "she shouted, knowing it was" | | 4 | "The suspect vaulted over a" | | 5 | "Quinn followed, her worn leather" | | 6 | "She swore under her breath," | | 7 | "The alley opened into a" | | 8 | "Quinn scanned the area, her" | | 9 | "A distinctive green neon sign" | | 10 | "She pushed the door open," | | 11 | "The walls were covered with" | | 12 | "The bartender dried a glass" | | 13 | "He set the glass down" | | 14 | "Quinn's hand instinctively went to" | | 15 | "The subtle emphasis on rather" | | 16 | "She scanned the room again," | | 17 | "She turned to leave, then" | | 18 | "The bartender's eyes flickered toward" | | 19 | "She moved toward the bookshelf," |
| | ratio | 0.868 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 53 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 1 | | matches | | 0 | "She scanned the room again, noting the bookshelf behind the bar that seemed slightly misaligned." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 4 | | fancyTags | | 0 | "she shouted (shout)" | | 1 | "he knew (know)" | | 2 | "Quinn added (add)" | | 3 | "she whispered (whisper)" |
| | dialogueSentences | 14 | | tagDensity | 0.357 | | leniency | 0.714 | | rawRatio | 0.8 | | effectiveRatio | 0.571 | |