| 91.89% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn advanced slowly [slowly]" | | 1 | "Tomás stepped backward [backward]" |
| | dialogueSentences | 37 | | tagDensity | 0.324 | | leniency | 0.649 | | rawRatio | 0.167 | | effectiveRatio | 0.108 | |
| 95.47% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1103 | | totalAiIsmAdverbs | 1 | | 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) | |
| 36.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1103 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "jaw clenched" | | 1 | "efficient" | | 2 | "encounter" | | 3 | "wavered" | | 4 | "standard" | | 5 | "determined" | | 6 | "intricate" | | 7 | "footsteps" | | 8 | "echoed" | | 9 | "silence" | | 10 | "depths" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | 0 | "blood went cold" | | 1 | "jaw clenched" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 105 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 105 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 130 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1098 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 25.16% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 66 | | wordCount | 801 | | uniqueNames | 19 | | maxNameDensity | 2.5 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Tomás | 14 | | Herrera | 2 | | Harlow | 2 | | Quinn | 20 | | Raven | 1 | | Nest | 1 | | Saint | 1 | | Christopher | 1 | | Camden | 2 | | Heard | 1 | | Three | 3 | | Morris | 5 | | London | 5 | | Transport | 1 | | Veil | 1 | | Market | 2 | | Thunder | 1 | | Small | 1 | | Detective | 2 |
| | persons | | 0 | "Tomás" | | 1 | "Herrera" | | 2 | "Harlow" | | 3 | "Quinn" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Camden" | | 7 | "Morris" | | 8 | "Thunder" |
| | places | | | globalScore | 0.252 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | 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 | 1098 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 130 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 22.88 | | std | 13.91 | | cv | 0.608 | | sampleLengths | | 0 | 25 | | 1 | 47 | | 2 | 2 | | 3 | 43 | | 4 | 53 | | 5 | 5 | | 6 | 41 | | 7 | 34 | | 8 | 36 | | 9 | 25 | | 10 | 7 | | 11 | 2 | | 12 | 19 | | 13 | 27 | | 14 | 14 | | 15 | 11 | | 16 | 22 | | 17 | 21 | | 18 | 12 | | 19 | 6 | | 20 | 10 | | 21 | 37 | | 22 | 25 | | 23 | 15 | | 24 | 40 | | 25 | 6 | | 26 | 27 | | 27 | 19 | | 28 | 6 | | 29 | 27 | | 30 | 29 | | 31 | 3 | | 32 | 20 | | 33 | 24 | | 34 | 6 | | 35 | 24 | | 36 | 31 | | 37 | 35 | | 38 | 26 | | 39 | 13 | | 40 | 8 | | 41 | 61 | | 42 | 41 | | 43 | 28 | | 44 | 20 | | 45 | 10 | | 46 | 31 | | 47 | 24 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 105 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 148 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 130 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 806 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.019851116625310174 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.007444168734491315 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 130 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 130 | | mean | 8.45 | | std | 6 | | cv | 0.71 | | sampleLengths | | 0 | 16 | | 1 | 9 | | 2 | 18 | | 3 | 19 | | 4 | 10 | | 5 | 2 | | 6 | 10 | | 7 | 19 | | 8 | 14 | | 9 | 9 | | 10 | 13 | | 11 | 12 | | 12 | 14 | | 13 | 5 | | 14 | 5 | | 15 | 11 | | 16 | 3 | | 17 | 2 | | 18 | 1 | | 19 | 15 | | 20 | 9 | | 21 | 17 | | 22 | 17 | | 23 | 11 | | 24 | 13 | | 25 | 12 | | 26 | 17 | | 27 | 8 | | 28 | 7 | | 29 | 2 | | 30 | 6 | | 31 | 13 | | 32 | 7 | | 33 | 6 | | 34 | 5 | | 35 | 3 | | 36 | 6 | | 37 | 6 | | 38 | 8 | | 39 | 11 | | 40 | 9 | | 41 | 13 | | 42 | 3 | | 43 | 5 | | 44 | 2 | | 45 | 11 | | 46 | 6 | | 47 | 4 | | 48 | 2 | | 49 | 6 |
| |
| 90.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.5538461538461539 | | totalSentences | 130 | | uniqueOpeners | 72 | |
| 73.26% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 91 | | matches | | 0 | "Unofficially haunting her dreams." | | 1 | "Still warm to the touch" |
| | ratio | 0.022 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 91 | | matches | | 0 | "Her sharp jaw clenched as" | | 1 | "He stumbled again, leaving a" | | 2 | "She could hear his laboured" | | 3 | "He spun around, his warm" | | 4 | "His fingers twitched toward the" | | 5 | "She needed answers now, before" | | 6 | "He smiled, the expression grim." | | 7 | "He laughed, the sound harsh" | | 8 | "He tossed the object at" | | 9 | "She crouched to examine it" | | 10 | "He winced as fresh blood" | | 11 | "Her radio crackled again." | | 12 | "His footsteps echoed on stone" | | 13 | "Her radio buzzed." |
| | ratio | 0.154 | |
| 97.36% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 91 | | matches | | 0 | "The knife clattered across wet" | | 1 | "Blood seeped through the fingers" | | 2 | "Detective Harlow Quinn rounded the" | | 3 | "Her sharp jaw clenched as" | | 4 | "The distinctive green neon sign" | | 5 | "Tomás glanced back, his olive" | | 6 | "The Saint Christopher medallion around" | | 7 | "Quinn cursed and followed, her" | | 8 | "The alley led to Camden's" | | 9 | "Quinn's breathing stayed controlled, eighteen" | | 10 | "The scar running along Tomás's" | | 11 | "He stumbled again, leaving a" | | 12 | "Quinn gained ground." | | 13 | "She could hear his laboured" | | 14 | "The rain intensified, drumming against" | | 15 | "Quinn's salt-and-pepper hair stayed plastered" | | 16 | "Tomás reached a dead end" | | 17 | "He spun around, his warm" | | 18 | "The knife wound in his" | | 19 | "Quinn advanced slowly, her left" |
| | ratio | 0.725 | |
| 54.95% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 91 | | matches | | 0 | "Now it looked months old." |
| | ratio | 0.011 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 1 | | matches | | 0 | "Quinn drew her torch, its beam cutting through the rain to illuminate worn steps disappearing into black." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 95.95% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "He laughed (laugh)" | | 1 | "Tomás pressed (press)" |
| | dialogueSentences | 37 | | tagDensity | 0.081 | | leniency | 0.162 | | rawRatio | 0.667 | | effectiveRatio | 0.108 | |