| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1012 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 50.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1012 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "footsteps" | | 1 | "rhythmic" | | 2 | "echoed" | | 3 | "glint" | | 4 | "weight" | | 5 | "flickered" | | 6 | "stomach" | | 7 | "lurch" |
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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 | 95 | | matches | (empty) | |
| 97.74% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 95 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 109 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1000 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 78.02% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 903 | | uniqueNames | 10 | | maxNameDensity | 1.44 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | London | 1 | | Quinn | 13 | | Chalk | 1 | | Farm | 1 | | Road | 1 | | Tube | 1 | | West | 1 | | End | 1 | | Water | 2 | | Morris | 4 |
| | persons | | 0 | "Quinn" | | 1 | "Water" | | 2 | "Morris" |
| | places | | 0 | "London" | | 1 | "Chalk" | | 2 | "Farm" | | 3 | "Road" | | 4 | "West" | | 5 | "End" |
| | globalScore | 0.78 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 1 | | matches | | 0 | "quite touching the ground" |
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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 | 1000 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 109 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 23.81 | | std | 17.09 | | cv | 0.718 | | sampleLengths | | 0 | 48 | | 1 | 36 | | 2 | 2 | | 3 | 26 | | 4 | 58 | | 5 | 45 | | 6 | 15 | | 7 | 4 | | 8 | 9 | | 9 | 48 | | 10 | 44 | | 11 | 6 | | 12 | 11 | | 13 | 43 | | 14 | 16 | | 15 | 37 | | 16 | 4 | | 17 | 15 | | 18 | 3 | | 19 | 13 | | 20 | 32 | | 21 | 5 | | 22 | 28 | | 23 | 2 | | 24 | 16 | | 25 | 3 | | 26 | 48 | | 27 | 2 | | 28 | 33 | | 29 | 17 | | 30 | 34 | | 31 | 34 | | 32 | 9 | | 33 | 33 | | 34 | 33 | | 35 | 45 | | 36 | 56 | | 37 | 28 | | 38 | 15 | | 39 | 35 | | 40 | 3 | | 41 | 6 |
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| 97.88% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 95 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 145 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 109 | | ratio | 0.055 | | matches | | 0 | "The suspect—dark jacket, hood pulled low—tore through a gap between two kebab shops, and Quinn followed without breaking stride." | | 1 | "They burst onto Chalk Farm Road together—her quarry first, then Quinn half a second later." | | 2 | "The air changed as she went deeper—warmer, thicker, carrying an undertone of something metallic and something else she couldn't name." | | 3 | "Footsteps, but wrong somehow—too light, too quick, like they weren't quite touching the ground." | | 4 | "Not with light—with something else." | | 5 | "Not gradually—instantly." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 771 | | adjectiveStacks | 1 | | stackExamples | | 0 | "deeper—warmer, thicker, carrying" |
| | adverbCount | 26 | | adverbRatio | 0.03372243839169909 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0038910505836575876 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 109 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 109 | | mean | 9.17 | | std | 6.1 | | cv | 0.665 | | sampleLengths | | 0 | 14 | | 1 | 15 | | 2 | 19 | | 3 | 13 | | 4 | 15 | | 5 | 8 | | 6 | 2 | | 7 | 6 | | 8 | 20 | | 9 | 3 | | 10 | 21 | | 11 | 19 | | 12 | 3 | | 13 | 12 | | 14 | 15 | | 15 | 4 | | 16 | 8 | | 17 | 18 | | 18 | 3 | | 19 | 5 | | 20 | 2 | | 21 | 5 | | 22 | 4 | | 23 | 9 | | 24 | 10 | | 25 | 14 | | 26 | 24 | | 27 | 13 | | 28 | 11 | | 29 | 20 | | 30 | 3 | | 31 | 1 | | 32 | 2 | | 33 | 9 | | 34 | 2 | | 35 | 8 | | 36 | 20 | | 37 | 15 | | 38 | 2 | | 39 | 14 | | 40 | 8 | | 41 | 14 | | 42 | 5 | | 43 | 10 | | 44 | 4 | | 45 | 7 | | 46 | 8 | | 47 | 3 | | 48 | 2 | | 49 | 3 |
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| 71.87% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.45871559633027525 | | totalSentences | 109 | | uniqueOpeners | 50 | |
| 81.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 82 | | matches | | 0 | "Just pushed harder, weaving between" | | 1 | "Just an expression of absolute" |
| | ratio | 0.024 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 82 | | matches | | 0 | "He'd anticipated her route before" | | 1 | "She ignored it." | | 2 | "They burst onto Chalk Farm" | | 3 | "She barrelled into the road." | | 4 | "Her radio crackled." | | 5 | "She pulled it from her" | | 6 | "Her torch swept left, right," | | 7 | "Her free hand rested on" | | 8 | "She hadn't drawn it yet." | | 9 | "He stood at the far" | | 10 | "He tilted his head" | | 11 | "He reached into his jacket," | | 12 | "He tucked the token away" | | 13 | "He stepped backward into the" | | 14 | "Her torch beam reached into" | | 15 | "Her heartbeat counted off the" | | 16 | "They'd found his body three" | | 17 | "Her quarry was gone." | | 18 | "She could climb back up" | | 19 | "She stepped forward." |
| | ratio | 0.244 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 82 | | matches | | 0 | "Harlow Quinn's boots struck the" | | 1 | "The suspect—dark jacket, hood pulled" | | 2 | "This one knew the terrain," | | 3 | "He'd anticipated her route before" | | 4 | "The figure didn't even glance" | | 5 | "Quinn's lungs burned." | | 6 | "The worn leather watch on" | | 7 | "She ignored it." | | 8 | "They burst onto Chalk Farm" | | 9 | "A black cab's headlights carved" | | 10 | "The suspect dodged between a" | | 11 | "Quinn didn't hesitate." | | 12 | "She barrelled into the road." | | 13 | "Tyres screeched against wet tarmac." | | 14 | "Someone's curse dissolved into the" | | 15 | "The station entrance gaped like" | | 16 | "The yellow signage had faded" | | 17 | "Quinn's torch beam cut through" | | 18 | "Water dripped somewhere ahead, a" | | 19 | "The air changed as she" |
| | ratio | 0.707 | |
| 60.98% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 82 | | matches | | | ratio | 0.012 | |
| 93.02% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 3 | | matches | | 0 | "Water dripped somewhere ahead, a rhythmic plink-plink-plink that echoed off tiles." | | 1 | "Advertising posters from another decade peeled from the walls, promoting concerts and West End shows that had long since closed." | | 2 | "All of them connected to people who'd vanished near abandoned stations, forgotten tunnels, places the city had tried to bury." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |