| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 62 | | tagDensity | 0.097 | | leniency | 0.194 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1587 | | 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) | |
| 87.40% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1587 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "flickered" | | 1 | "scanned" | | 2 | "footsteps" | | 3 | "weight" |
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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 | 142 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 142 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 197 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1587 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1270 | | uniqueNames | 9 | | maxNameDensity | 2.36 | | worstName | "Quinn" | | maxWindowNameDensity | 5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 30 | | Dean | 1 | | Street | 2 | | Berwick | 1 | | Raven | 1 | | Nest | 1 | | Tube | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" |
| | places | | 0 | "Dean" | | 1 | "Street" | | 2 | "Berwick" |
| | globalScore | 0.319 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 101 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared beyond the green neon sign of the Raven’s Nest" |
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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 | 1587 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 197 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 115 | | mean | 13.8 | | std | 15.42 | | cv | 1.118 | | sampleLengths | | 0 | 46 | | 1 | 2 | | 2 | 68 | | 3 | 4 | | 4 | 8 | | 5 | 43 | | 6 | 7 | | 7 | 16 | | 8 | 38 | | 9 | 8 | | 10 | 59 | | 11 | 4 | | 12 | 6 | | 13 | 4 | | 14 | 5 | | 15 | 6 | | 16 | 25 | | 17 | 7 | | 18 | 3 | | 19 | 45 | | 20 | 6 | | 21 | 10 | | 22 | 43 | | 23 | 3 | | 24 | 24 | | 25 | 5 | | 26 | 2 | | 27 | 1 | | 28 | 8 | | 29 | 20 | | 30 | 6 | | 31 | 4 | | 32 | 8 | | 33 | 51 | | 34 | 11 | | 35 | 5 | | 36 | 65 | | 37 | 4 | | 38 | 54 | | 39 | 6 | | 40 | 5 | | 41 | 13 | | 42 | 4 | | 43 | 1 | | 44 | 6 | | 45 | 10 | | 46 | 17 | | 47 | 3 | | 48 | 2 | | 49 | 25 |
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| 95.38% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 142 | | matches | | 0 | "been chained" | | 1 | "been drilled" | | 2 | "was gone" | | 3 | "been explained" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 217 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 197 | | ratio | 0.01 | | matches | | 0 | "The suspect had gone through it; the casework had shifted a fraction from the wall, leaving a black seam." | | 1 | "His sleeves were too long; something beneath one cuff clicked against the stall’s counter." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1274 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.015698587127158554 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 197 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 197 | | mean | 8.06 | | std | 5.34 | | cv | 0.663 | | sampleLengths | | 0 | 14 | | 1 | 32 | | 2 | 2 | | 3 | 9 | | 4 | 11 | | 5 | 16 | | 6 | 6 | | 7 | 26 | | 8 | 3 | | 9 | 1 | | 10 | 8 | | 11 | 8 | | 12 | 9 | | 13 | 5 | | 14 | 21 | | 15 | 7 | | 16 | 16 | | 17 | 5 | | 18 | 3 | | 19 | 15 | | 20 | 15 | | 21 | 8 | | 22 | 13 | | 23 | 6 | | 24 | 20 | | 25 | 7 | | 26 | 13 | | 27 | 4 | | 28 | 6 | | 29 | 4 | | 30 | 5 | | 31 | 6 | | 32 | 2 | | 33 | 14 | | 34 | 9 | | 35 | 7 | | 36 | 3 | | 37 | 8 | | 38 | 14 | | 39 | 15 | | 40 | 8 | | 41 | 6 | | 42 | 4 | | 43 | 6 | | 44 | 5 | | 45 | 19 | | 46 | 9 | | 47 | 10 | | 48 | 3 | | 49 | 11 |
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| 53.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.3350253807106599 | | totalSentences | 197 | | uniqueOpeners | 66 | |
| 72.99% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 137 | | matches | | 0 | "Then a flash of dark" | | 1 | "Somewhere in the walls, pipes" | | 2 | "Then a shout, cut short." |
| | ratio | 0.022 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 137 | | matches | | 0 | "Her boots struck the pavement" | | 1 | "She had run through worse" | | 2 | "He had blood on his" | | 3 | "He looked back, saw her," | | 4 | "She kept her eyes on" | | 5 | "She reached the doorway and" | | 6 | "She heard a crash below," | | 7 | "she called over her shoulder" | | 8 | "She took the stairs two" | | 9 | "She moved to the bookshelf." | | 10 | "It gave with a wooden" | | 11 | "Her radio crackled." | | 12 | "Her sergeant’s voice clipped through" | | 13 | "She stared down the passage." | | 14 | "She heard voices below, layered" | | 15 | "Their cords ran over the" | | 16 | "His smile showed a gold" | | 17 | "He held his hands out," | | 18 | "His sleeves were too long;" | | 19 | "Her radio broke into a" |
| | ratio | 0.248 | |
| 47.59% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 113 | | totalSentences | 137 | | matches | | 0 | "The suspect cut across Dean" | | 1 | "Her boots struck the pavement" | | 2 | "She had run through worse" | | 3 | "The man ahead wore a" | | 4 | "He had blood on his" | | 5 | "The trail had started in" | | 6 | "He looked back, saw her," | | 7 | "The passage spat them onto" | | 8 | "A bus hissed past, throwing" | | 9 | "The suspect darted behind it." | | 10 | "Quinn cut the other way," | | 11 | "Quinn crossed against the traffic." | | 12 | "A horn blared." | | 13 | "She kept her eyes on" | | 14 | "The sign above the door" | | 15 | "She reached the doorway and" | | 16 | "The bar fell quiet around" | | 17 | "Faces turned from the counter," | | 18 | "Maps and black-and-white photographs covered" | | 19 | "The bartender set down the" |
| | ratio | 0.825 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 137 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 1 | | matches | | 0 | "Near a dead ticket machine, a pair of teenagers watched a cage that rattled though nothing inside could be seen." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | 0 | "Quinn demanded (demand)" |
| | dialogueSentences | 62 | | tagDensity | 0.065 | | leniency | 0.129 | | rawRatio | 0.25 | | effectiveRatio | 0.032 | |