| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.125 | | leniency | 0.25 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1402 | | 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) | |
| 82.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1402 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "wavering" | | 1 | "scanned" | | 2 | "structure" | | 3 | "footsteps" | | 4 | "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 | 1 | | narrationSentences | 139 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 139 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 153 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1401 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 60.31% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 1338 | | uniqueNames | 8 | | maxNameDensity | 1.79 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Dallow | 15 | | Quinn | 24 | | Camden | 1 | | Several | 1 | | Rain | 3 |
| | persons | | 0 | "Raven" | | 1 | "Dallow" | | 2 | "Quinn" | | 3 | "Rain" |
| | places | | | globalScore | 0.603 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 107 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1401 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 153 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 24.16 | | std | 21.93 | | cv | 0.908 | | sampleLengths | | 0 | 74 | | 1 | 5 | | 2 | 61 | | 3 | 5 | | 4 | 24 | | 5 | 2 | | 6 | 2 | | 7 | 53 | | 8 | 24 | | 9 | 3 | | 10 | 37 | | 11 | 37 | | 12 | 50 | | 13 | 37 | | 14 | 1 | | 15 | 40 | | 16 | 6 | | 17 | 2 | | 18 | 6 | | 19 | 4 | | 20 | 4 | | 21 | 33 | | 22 | 14 | | 23 | 39 | | 24 | 30 | | 25 | 55 | | 26 | 4 | | 27 | 4 | | 28 | 10 | | 29 | 8 | | 30 | 39 | | 31 | 5 | | 32 | 6 | | 33 | 69 | | 34 | 27 | | 35 | 12 | | 36 | 42 | | 37 | 8 | | 38 | 27 | | 39 | 45 | | 40 | 6 | | 41 | 35 | | 42 | 19 | | 43 | 9 | | 44 | 93 | | 45 | 30 | | 46 | 48 | | 47 | 5 | | 48 | 16 | | 49 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 139 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 232 | | matches | (empty) | |
| 68.16% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 3 | | flaggedSentences | 4 | | totalSentences | 153 | | ratio | 0.026 | | matches | | 0 | "A cyclist swore as she cut across the road; a bus blared its horn and dragged a fan of water over the pavement." | | 1 | "Dallow waited for no gap; he darted between two cars and reached the opposite kerb as brakes screamed behind him." | | 2 | "A rusted sign hung from one bolt: CAMDEN TOWN—CLOSED." | | 3 | "A woman laughed once; a man answered in a language she didn’t recognise." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1344 | | adjectiveStacks | 1 | | stackExamples | | 0 | "grating shut above him." |
| | adverbCount | 22 | | adverbRatio | 0.01636904761904762 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.001488095238095238 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 153 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 153 | | mean | 9.16 | | std | 5.06 | | cv | 0.553 | | sampleLengths | | 0 | 17 | | 1 | 21 | | 2 | 14 | | 3 | 15 | | 4 | 7 | | 5 | 5 | | 6 | 12 | | 7 | 4 | | 8 | 15 | | 9 | 19 | | 10 | 11 | | 11 | 5 | | 12 | 11 | | 13 | 6 | | 14 | 7 | | 15 | 2 | | 16 | 2 | | 17 | 8 | | 18 | 23 | | 19 | 22 | | 20 | 7 | | 21 | 7 | | 22 | 10 | | 23 | 3 | | 24 | 5 | | 25 | 5 | | 26 | 18 | | 27 | 5 | | 28 | 4 | | 29 | 12 | | 30 | 5 | | 31 | 20 | | 32 | 17 | | 33 | 8 | | 34 | 7 | | 35 | 18 | | 36 | 3 | | 37 | 12 | | 38 | 9 | | 39 | 13 | | 40 | 1 | | 41 | 8 | | 42 | 10 | | 43 | 6 | | 44 | 16 | | 45 | 6 | | 46 | 2 | | 47 | 6 | | 48 | 4 | | 49 | 4 |
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| 46.08% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.28104575163398693 | | totalSentences | 153 | | uniqueOpeners | 43 | |
| 98.04% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 136 | | matches | | 0 | "Then Quinn spotted the charcoal" | | 1 | "Then came the clatter of" | | 2 | "Only static answered." | | 3 | "Then he shoved the woman" |
| | ratio | 0.029 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 136 | | matches | | 0 | "He carried no umbrella." | | 1 | "She stepped off the kerb." | | 2 | "His gaze caught on her" | | 3 | "His stride broke for half" | | 4 | "Her left wrist struck the" | | 5 | "He raised the leather case" | | 6 | "She took the crossing on" | | 7 | "She scanned faces." | | 8 | "He shouldered through people and" | | 9 | "Her radio crackled against her" | | 10 | "She switched off the channel" | | 11 | "She heard a metal clang" | | 12 | "He dropped down the steps" | | 13 | "It shifted an inch, then" | | 14 | "She crouched and looked through" | | 15 | "Her radio spat static." | | 16 | "Her boots rang against the" | | 17 | "She took a photograph, then" | | 18 | "It did not move." | | 19 | "She reached for her radio." |
| | ratio | 0.221 | |
| 44.56% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 113 | | totalSentences | 136 | | matches | | 0 | "Rain sheeted across Soho and" | | 1 | "Quinn stood beneath a shop" | | 2 | "A man near the bar" | | 3 | "The customer tucked it inside" | | 4 | "Quinn watched the man leave." | | 5 | "Rafe Dallow wore a charcoal" | | 6 | "He carried no umbrella." | | 7 | "A black leather case swung" | | 8 | "Quinn had seen his name" | | 9 | "Each time, someone had handed" | | 10 | "She stepped off the kerb." | | 11 | "Dallow reached the mouth of" | | 12 | "His gaze caught on her" | | 13 | "His stride broke for half" | | 14 | "Quinn pushed through a knot" | | 15 | "A cyclist swore as she" | | 16 | "Dallow hurdled a stack of" | | 17 | "Quinn cleared the crates without" | | 18 | "Her left wrist struck the" | | 19 | "Pain flashed beneath the worn" |
| | ratio | 0.831 | |
| 36.76% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 136 | | matches | | 0 | "By the time she reached" |
| | ratio | 0.007 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 64 | | technicalSentenceCount | 1 | | matches | | 0 | "She could draw her weapon in a crowd that watched her with hands tucked beneath coats." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 87.50% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 16 | | tagDensity | 0.125 | | leniency | 0.25 | | rawRatio | 0.5 | | effectiveRatio | 0.125 | |