| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1057 | | 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) | |
| 81.08% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1057 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "familiar" | | 1 | "sense of" | | 2 | "stomach" | | 3 | "predator" |
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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 | 91 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 91 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 38 | | totalWords | 1057 | | ratio | 0.036 | | matches | | 0 | "small drawing of finger bone, possibly occult, possibly nothing, possibly the thing that took my partner." | | 1 | "If you ever find yourself at one of those doors, Detective, don't go through without a token. And don't go through alone." |
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| 97.22% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 1 | | matches | | 0 | "Her radio crackled against her collarbone, Dispatch asking for her twenty." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 988 | | uniqueNames | 19 | | maxNameDensity | 0.61 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Regulations" | | discoveredNames | | Camden | 1 | | High | 1 | | Street | 1 | | Raven | 1 | | Nest | 1 | | Quinn | 6 | | Tuesday | 1 | | Dispatch | 1 | | Hackney | 1 | | Marshes | 1 | | Met | 2 | | Three | 1 | | Morris | 4 | | Whitechapel | 1 | | Bethnal | 1 | | Green | 1 | | Herrera | 1 | | Detective | 1 | | Regulations | 4 |
| | persons | | 0 | "Quinn" | | 1 | "Dispatch" | | 2 | "Met" | | 3 | "Three" | | 4 | "Morris" | | 5 | "Herrera" | | 6 | "Detective" | | 7 | "Regulations" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Raven" | | 4 | "Hackney" | | 5 | "Marshes" | | 6 | "Whitechapel" | | 7 | "Bethnal" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 1 | | matches | | 0 | "quite match any rhythm she knew" |
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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 | 1057 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 98 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 25.17 | | std | 23.54 | | cv | 0.935 | | sampleLengths | | 0 | 16 | | 1 | 71 | | 2 | 4 | | 3 | 5 | | 4 | 5 | | 5 | 21 | | 6 | 18 | | 7 | 7 | | 8 | 10 | | 9 | 61 | | 10 | 19 | | 11 | 4 | | 12 | 11 | | 13 | 2 | | 14 | 50 | | 15 | 32 | | 16 | 2 | | 17 | 50 | | 18 | 50 | | 19 | 3 | | 20 | 45 | | 21 | 9 | | 22 | 42 | | 23 | 5 | | 24 | 26 | | 25 | 1 | | 26 | 4 | | 27 | 23 | | 28 | 1 | | 29 | 38 | | 30 | 7 | | 31 | 84 | | 32 | 46 | | 33 | 71 | | 34 | 47 | | 35 | 8 | | 36 | 63 | | 37 | 3 | | 38 | 28 | | 39 | 5 | | 40 | 54 | | 41 | 6 |
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| 93.70% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 91 | | matches | | 0 | "was gone" | | 1 | "was supposed" | | 2 | "been found" |
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| 76.54% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 162 | | matches | | 0 | "was walking" | | 1 | "was running" | | 2 | "wasn't laughing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 98 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 894 | | adjectiveStacks | 1 | | stackExamples | | 0 | "bouncing hard against his" |
| | adverbCount | 24 | | adverbRatio | 0.026845637583892617 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0044742729306487695 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 10.79 | | std | 8.84 | | cv | 0.819 | | sampleLengths | | 0 | 13 | | 1 | 3 | | 2 | 27 | | 3 | 22 | | 4 | 22 | | 5 | 4 | | 6 | 5 | | 7 | 2 | | 8 | 3 | | 9 | 11 | | 10 | 10 | | 11 | 18 | | 12 | 7 | | 13 | 2 | | 14 | 8 | | 15 | 9 | | 16 | 10 | | 17 | 18 | | 18 | 5 | | 19 | 19 | | 20 | 17 | | 21 | 2 | | 22 | 4 | | 23 | 11 | | 24 | 2 | | 25 | 20 | | 26 | 20 | | 27 | 4 | | 28 | 3 | | 29 | 3 | | 30 | 32 | | 31 | 2 | | 32 | 5 | | 33 | 22 | | 34 | 1 | | 35 | 2 | | 36 | 20 | | 37 | 8 | | 38 | 20 | | 39 | 5 | | 40 | 4 | | 41 | 6 | | 42 | 7 | | 43 | 3 | | 44 | 8 | | 45 | 12 | | 46 | 25 | | 47 | 8 | | 48 | 1 | | 49 | 8 |
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| 72.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.4897959183673469 | | totalSentences | 98 | | uniqueOpeners | 48 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 77 | | matches | | 0 | "Right before he'd gone down" | | 1 | "Right before she'd come back" | | 2 | "Somewhere above her, on the" | | 3 | "Somewhere in the dark, that" |
| | ratio | 0.052 | |
| 74.55% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 77 | | matches | | 0 | "She didn't slow." | | 1 | "She'd clocked him outside the" | | 2 | "They never did." | | 3 | "Her radio crackled against her" | | 4 | "She pressed the button with" | | 5 | "She could lose three suspects" | | 6 | "Her boots hit something soft" | | 7 | "She took the wall anyway." | | 8 | "Her lungs began to burn," | | 9 | "She always followed." | | 10 | "He went left at the" | | 11 | "She wiped it with the" | | 12 | "She knew this stretch." | | 13 | "She'd walked it a hundred" | | 14 | "She crouched at the top" | | 15 | "She keyed the radio again." | | 16 | "She tapped it." | | 17 | "She drew her torch instead." | | 18 | "Her stomach did a slow," | | 19 | "She'd seen that mark before." |
| | ratio | 0.364 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 77 | | matches | | 0 | "Quinn's boot hit a puddle" | | 1 | "She didn't slow." | | 2 | "She'd clocked him outside the" | | 3 | "They never did." | | 4 | "Her radio crackled against her" | | 5 | "She pressed the button with" | | 6 | "She could lose three suspects" | | 7 | "The alley stank of bin" | | 8 | "Her boots hit something soft" | | 9 | "She took the wall anyway." | | 10 | "The leather watch on her" | | 11 | "A vendor packing up a" | | 12 | "The vendor jerked a thumb" | | 13 | "Rain came harder now, sheets" | | 14 | "Her lungs began to burn," | | 15 | "Some things didn't change." | | 16 | "She always followed." | | 17 | "He went left at the" | | 18 | "Water ran off her nose." | | 19 | "She wiped it with the" |
| | ratio | 0.714 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 77 | | matches | | 0 | "By the time Quinn had" | | 1 | "Now he was running." | | 2 | "And, tucked behind the lining" | | 3 | "*If you ever find yourself" |
| | ratio | 0.052 | |
| 86.47% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 3 | | matches | | 0 | "She'd clocked him outside the Raven's Nest an hour ago, passing something to a woman with teeth that caught the streetlight wrong." | | 1 | "The static thickened, curdled, became something that sounded almost like breathing before snapping clean off." | | 2 | "Regulations said don't enter unfamiliar premises alone, especially ones that weren't on any map the Met had ever drawn." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "Quinn shouted (shout)" | | 1 | "she muttered (mutter)" |
| | dialogueSentences | 10 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 1 | | effectiveRatio | 0.4 | |