| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.059 | | leniency | 0.118 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 786 | | 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) | |
| 80.92% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 786 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "scanned" | | 1 | "silence" | | 2 | "glint" |
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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 | 86 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 86 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 102 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 786 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 53.18% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 723 | | uniqueNames | 17 | | maxNameDensity | 1.94 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Soho | 1 | | Harlow | 1 | | Quinn | 14 | | Herrera | 10 | | Saint | 1 | | Christopher | 1 | | Chinatown | 1 | | Wardour | 1 | | Street | 1 | | Morris | 1 | | Tube | 1 | | Camden | 2 | | Veil | 1 | | Market | 1 | | Rain | 3 |
| | persons | | 0 | "Raven" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Morris" | | 7 | "Rain" |
| | places | | 0 | "Soho" | | 1 | "Chinatown" | | 2 | "Wardour" | | 3 | "Street" | | 4 | "Market" |
| | globalScore | 0.532 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed stitched from shadow stood guard, hand outstretched" |
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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 | 786 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 102 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 17.09 | | std | 17.31 | | cv | 1.013 | | sampleLengths | | 0 | 59 | | 1 | 44 | | 2 | 2 | | 3 | 1 | | 4 | 47 | | 5 | 26 | | 6 | 40 | | 7 | 20 | | 8 | 4 | | 9 | 4 | | 10 | 3 | | 11 | 18 | | 12 | 34 | | 13 | 52 | | 14 | 25 | | 15 | 15 | | 16 | 3 | | 17 | 10 | | 18 | 4 | | 19 | 3 | | 20 | 4 | | 21 | 4 | | 22 | 57 | | 23 | 5 | | 24 | 8 | | 25 | 6 | | 26 | 10 | | 27 | 9 | | 28 | 4 | | 29 | 4 | | 30 | 24 | | 31 | 18 | | 32 | 1 | | 33 | 57 | | 34 | 3 | | 35 | 23 | | 36 | 14 | | 37 | 37 | | 38 | 8 | | 39 | 4 | | 40 | 31 | | 41 | 4 | | 42 | 3 | | 43 | 27 | | 44 | 4 | | 45 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 86 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 127 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 102 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 729 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.01783264746227709 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.00411522633744856 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 102 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 102 | | mean | 7.71 | | std | 5.05 | | cv | 0.655 | | sampleLengths | | 0 | 16 | | 1 | 9 | | 2 | 21 | | 3 | 6 | | 4 | 7 | | 5 | 18 | | 6 | 5 | | 7 | 9 | | 8 | 12 | | 9 | 2 | | 10 | 1 | | 11 | 5 | | 12 | 20 | | 13 | 13 | | 14 | 9 | | 15 | 7 | | 16 | 10 | | 17 | 9 | | 18 | 17 | | 19 | 23 | | 20 | 9 | | 21 | 7 | | 22 | 4 | | 23 | 4 | | 24 | 4 | | 25 | 3 | | 26 | 7 | | 27 | 2 | | 28 | 3 | | 29 | 6 | | 30 | 3 | | 31 | 12 | | 32 | 13 | | 33 | 6 | | 34 | 6 | | 35 | 5 | | 36 | 9 | | 37 | 9 | | 38 | 5 | | 39 | 18 | | 40 | 7 | | 41 | 4 | | 42 | 10 | | 43 | 4 | | 44 | 8 | | 45 | 7 | | 46 | 3 | | 47 | 6 | | 48 | 4 | | 49 | 4 |
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| 53.59% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3627450980392157 | | totalSentences | 102 | | uniqueOpeners | 37 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 82 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 82 | | matches | | 0 | "She scanned the street and" | | 1 | "He did not look back." | | 2 | "He knew the alley behind" | | 3 | "Her breathing stayed even, military" | | 4 | "He was fast, lighter than" | | 5 | "He laughed without slowing." | | 6 | "He sprinted through." | | 7 | "She followed, shoulder checking a" | | 8 | "He lifted his left forearm," | | 9 | "His voice carried back." | | 10 | "He shook his head." | | 11 | "She thought of DS Morris" | | 12 | "She thought of eighteen years" | | 13 | "He stepped further into the" | | 14 | "She had been on this" | | 15 | "Her coat weighed heavy." | | 16 | "She followed the sound." | | 17 | "He did not offer her" | | 18 | "She could pull back, call" | | 19 | "She could wait for the" |
| | ratio | 0.256 | |
| 8.78% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 82 | | matches | | 0 | "The sign buzzed, threw sick" | | 1 | "Detective Harlow Quinn stepped out" | | 2 | "Salt-and-pepper hair stuck to her" | | 3 | "She scanned the street and" | | 4 | "Tomás Herrera broke from the" | | 5 | "Olive skin darkened by rain." | | 6 | "The scar ran along his" | | 7 | "He did not look back." | | 8 | "He knew the alley behind" | | 9 | "Quinn kept three lengths behind," | | 10 | "Her breathing stayed even, military" | | 11 | "A bus hissed past, sprayed" | | 12 | "Herrera vaulted a stack of" | | 13 | "Quinn ducked under the bus’s" | | 14 | "The chase carried them past" | | 15 | "The walls of The Raven’s" | | 16 | "Herrera turned down a side" | | 17 | "He was fast, lighter than" | | 18 | "Quinn’s sharp jaw tightened." | | 19 | "He laughed without slowing." |
| | ratio | 0.902 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 82 | | matches | (empty) | | ratio | 0 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 4 | | matches | | 0 | "He knew the alley behind the bar, the service doors, the narrow cut through Chinatown that spilled onto Wardour Street." | | 1 | "She thought of eighteen years of decorated service and the file on the clique that kept thickening." | | 2 | "The tunnel opened into a cavernous space that could only be an abandoned Tube station beneath Camden." | | 3 | "Quinn stared at the gate, at the market, at the man who ran from her into an unfamiliar and potentially dangerous territory." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.059 | | leniency | 0.118 | | rawRatio | 0 | | effectiveRatio | 0 | |