| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.294 | | leniency | 0.588 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.81% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1615 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 72.14% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1615 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echo" | | 2 | "rhythmic" | | 3 | "silence" | | 4 | "flickered" | | 5 | "velvet" | | 6 | "shattered" | | 7 | "could feel" |
| |
| 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 | 169 | | matches | (empty) | |
| 92.14% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 4 | | narrationSentences | 169 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 181 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1611 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 61.76% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1530 | | uniqueNames | 13 | | maxNameDensity | 1.76 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 27 | | Metropolitan | 1 | | Police | 1 | | Raven | 2 | | Nest | 2 | | Waterloo | 1 | | Morris | 4 | | Underground | 1 | | Tube | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Police" | | 3 | "Raven" | | 4 | "Morris" | | 5 | "Veil" | | 6 | "Market" |
| | places | | | globalScore | 0.618 | | windowScore | 0.667 | |
| 81.82% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 110 | | glossingSentenceCount | 3 | | matches | | 0 | "spiral that seemed to shift when the rain struck it" | | 1 | "knives that seemed to bend away from the light" | | 2 | "appeared behind the suspect—too many limbs, a crown of pale horns, a face made from shifting human features" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1611 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 181 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 104 | | mean | 15.49 | | std | 15.34 | | cv | 0.99 | | sampleLengths | | 0 | 9 | | 1 | 47 | | 2 | 50 | | 3 | 3 | | 4 | 6 | | 5 | 59 | | 6 | 4 | | 7 | 21 | | 8 | 8 | | 9 | 35 | | 10 | 2 | | 11 | 30 | | 12 | 1 | | 13 | 4 | | 14 | 45 | | 15 | 6 | | 16 | 4 | | 17 | 27 | | 18 | 3 | | 19 | 8 | | 20 | 6 | | 21 | 37 | | 22 | 4 | | 23 | 36 | | 24 | 3 | | 25 | 8 | | 26 | 70 | | 27 | 6 | | 28 | 5 | | 29 | 53 | | 30 | 9 | | 31 | 16 | | 32 | 28 | | 33 | 5 | | 34 | 13 | | 35 | 2 | | 36 | 46 | | 37 | 13 | | 38 | 9 | | 39 | 6 | | 40 | 1 | | 41 | 31 | | 42 | 11 | | 43 | 9 | | 44 | 13 | | 45 | 54 | | 46 | 43 | | 47 | 3 | | 48 | 23 | | 49 | 7 |
| |
| 94.88% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 169 | | matches | | 0 | "been seen" | | 1 | "been buried" | | 2 | "been abandoned" | | 3 | "been written" | | 4 | "was lined" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 258 | | matches | | |
| 79.72% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 181 | | ratio | 0.022 | | matches | | 0 | "Eighteen years of Metropolitan Police work had taught her their rhythms—the drunken stumble outside the clubs, the sudden flare of violence in a doorway, the taxis nosing through red lights." | | 1 | "From below came the fading echo of footsteps and something else—a low, distant murmur, too deep to be voices and too rhythmic to be machinery." | | 2 | "Quinn felt the old cold open inside her—the same cold she had felt in the depot when Morris’s radio crackled once and a voice answered from beneath the floor." | | 3 | "For an instant, something enormous appeared behind the suspect—too many limbs, a crown of pale horns, a face made from shifting human features." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1539 | | adjectiveStacks | 1 | | stackExamples | | 0 | "old cold open inside her—" |
| | adverbCount | 43 | | adverbRatio | 0.02794022092267706 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.004548408057179987 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 181 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 181 | | mean | 8.9 | | std | 6.05 | | cv | 0.68 | | sampleLengths | | 0 | 9 | | 1 | 23 | | 2 | 24 | | 3 | 4 | | 4 | 30 | | 5 | 16 | | 6 | 3 | | 7 | 3 | | 8 | 3 | | 9 | 6 | | 10 | 16 | | 11 | 16 | | 12 | 21 | | 13 | 4 | | 14 | 6 | | 15 | 15 | | 16 | 8 | | 17 | 2 | | 18 | 3 | | 19 | 10 | | 20 | 20 | | 21 | 2 | | 22 | 10 | | 23 | 6 | | 24 | 14 | | 25 | 1 | | 26 | 3 | | 27 | 1 | | 28 | 24 | | 29 | 21 | | 30 | 6 | | 31 | 4 | | 32 | 27 | | 33 | 3 | | 34 | 8 | | 35 | 6 | | 36 | 7 | | 37 | 16 | | 38 | 5 | | 39 | 9 | | 40 | 4 | | 41 | 6 | | 42 | 5 | | 43 | 25 | | 44 | 3 | | 45 | 8 | | 46 | 14 | | 47 | 17 | | 48 | 13 | | 49 | 18 |
| |
| 46.59% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.3259668508287293 | | totalSentences | 181 | | uniqueOpeners | 59 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 154 | | matches | | 0 | "Then he shoved a cyclist" | | 1 | "Then he thrust the token" | | 2 | "Then he ran." | | 3 | "Somewhere behind Quinn, the tunnel" | | 4 | "Then the suspect stepped backward" |
| | ratio | 0.032 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 154 | | matches | | 0 | "He moved fast without looking" | | 1 | "Her boots struck the pavement" | | 2 | "Her left wrist flashed as" | | 3 | "She was forty-one, too old" | | 4 | "His face was pale and" | | 5 | "His eyes caught the green" | | 6 | "She rounded the corner and" | | 7 | "He looked at her." | | 8 | "Her fingers closed on the" | | 9 | "He slipped through the opening." | | 10 | "She hit it with her" | | 11 | "She had seen the suspect" | | 12 | "It should have been enough." | | 13 | "She holstered her pistol and" | | 14 | "They led down." | | 15 | "She stopped beneath a broken" | | 16 | "It had been written in" | | 17 | "She had thought it was" | | 18 | "He looked back at her," | | 19 | "She tore free and kept" |
| | ratio | 0.208 | |
| 50.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 126 | | totalSentences | 154 | | matches | | 0 | "Detective Harlow Quinn caught glimpses" | | 1 | "He moved fast without looking" | | 2 | "Quinn knew the streets." | | 3 | "The suspect knew them too," | | 4 | "A couple turned." | | 5 | "The suspect didn’t." | | 6 | "Her boots struck the pavement" | | 7 | "Rain slicked her closely cropped" | | 8 | "Her left wrist flashed as" | | 9 | "She was forty-one, too old" | | 10 | "The suspect glanced back." | | 11 | "His face was pale and" | | 12 | "His eyes caught the green" | | 13 | "The cyclist shouted." | | 14 | "A wheel skidded sideways, spraying" | | 15 | "The alley stank of wet" | | 16 | "A metal door banged somewhere" | | 17 | "Quinn drew her service pistol," | | 18 | "She rounded the corner and" | | 19 | "The green glow from the" |
| | ratio | 0.818 | |
| 32.47% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 154 | | matches | | 0 | "By the time she regained" |
| | ratio | 0.006 | |
| 97.51% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 63 | | technicalSentenceCount | 4 | | matches | | 0 | "This time she saw what he held: a small bone token, smooth and yellow-white, carved with a spiral that seemed to shift when the rain struck it." | | 1 | "The dead man had been a known fence, the kind who trafficked in stolen medicines and forged passports." | | 2 | "Copper cages held small, furred things that stared at Quinn with damp, intelligent eyes." | | 3 | "The tunnel beyond was lined with old posters, their paper rippling as if underwater." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 91.18% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 17 | | tagDensity | 0.235 | | leniency | 0.471 | | rawRatio | 0.25 | | effectiveRatio | 0.118 | |