| 88.89% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn's voice cracked like [like]" | | 1 | "Tomás spun around [around]" |
| | dialogueSentences | 36 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0.125 | | effectiveRatio | 0.111 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1452 | | 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) | |
| 24.24% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1452 | | totalAiIsms | 22 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "familiar" | | 1 | "glint" | | 2 | "lilt" | | 3 | "intricate" | | 4 | "charged" | | 5 | "flicked" | | 6 | "pulse" | | 7 | "gloom" | | 8 | "resolved" | | 9 | "stomach" | | 10 | "echoes" | | 11 | "crystal" | | 12 | "vibrated" | | 13 | "velvet" | | 14 | "porcelain" | | 15 | "scanned" | | 16 | "dancing" | | 17 | "trembled" |
| |
| 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) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 169 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 189 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 10 | | totalWords | 1453 | | ratio | 0.007 | | matches | | 0 | "Camdon Station - Closed" | | 1 | "The Raven's Nest" | | 2 | "Detective... Detective... Llice..." |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 64 | | wordCount | 1244 | | uniqueNames | 15 | | maxNameDensity | 2.41 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Saint | 1 | | Christopher | 1 | | Seville | 1 | | Metropolitan | 1 | | Police | 1 | | Quinn | 30 | | Morris | 2 | | Tomás | 11 | | Station | 1 | | Soho | 1 | | Raven | 1 | | Tube | 1 | | Vex | 7 | | Spanish | 1 | | Vendors | 4 |
| | persons | | 0 | "Saint" | | 1 | "Christopher" | | 2 | "Police" | | 3 | "Quinn" | | 4 | "Morris" | | 5 | "Tomás" | | 6 | "Station" | | 7 | "Raven" | | 8 | "Vex" | | 9 | "Vendors" |
| | places | | 0 | "Seville" | | 1 | "Metropolitan" | | 2 | "Soho" | | 3 | "Spanish" |
| | globalScore | 0.294 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 95 | | glossingSentenceCount | 1 | | matches | | 0 | "sigils that seemed to shift under the sickly yellow glow of the streetlamp" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1453 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 189 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 29.06 | | std | 20.69 | | cv | 0.712 | | sampleLengths | | 0 | 53 | | 1 | 33 | | 2 | 96 | | 3 | 6 | | 4 | 61 | | 5 | 5 | | 6 | 47 | | 7 | 29 | | 8 | 51 | | 9 | 25 | | 10 | 64 | | 11 | 19 | | 12 | 73 | | 13 | 11 | | 14 | 19 | | 15 | 47 | | 16 | 61 | | 17 | 6 | | 18 | 34 | | 19 | 45 | | 20 | 16 | | 21 | 18 | | 22 | 69 | | 23 | 25 | | 24 | 32 | | 25 | 18 | | 26 | 47 | | 27 | 15 | | 28 | 11 | | 29 | 18 | | 30 | 36 | | 31 | 14 | | 32 | 12 | | 33 | 26 | | 34 | 11 | | 35 | 20 | | 36 | 37 | | 37 | 23 | | 38 | 8 | | 39 | 31 | | 40 | 37 | | 41 | 18 | | 42 | 14 | | 43 | 35 | | 44 | 2 | | 45 | 23 | | 46 | 37 | | 47 | 7 | | 48 | 4 | | 49 | 4 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 169 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 243 | | matches | | 0 | "wasn't looking" | | 1 | "was looking" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 189 | | ratio | 0.005 | | matches | | 0 | "A rusted sign hung askew: *Camdon Station - Closed*." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1246 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.016853932584269662 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.0072231139646869984 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 189 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 189 | | mean | 7.69 | | std | 4.82 | | cv | 0.627 | | sampleLengths | | 0 | 7 | | 1 | 16 | | 2 | 3 | | 3 | 14 | | 4 | 13 | | 5 | 11 | | 6 | 16 | | 7 | 6 | | 8 | 3 | | 9 | 18 | | 10 | 13 | | 11 | 5 | | 12 | 20 | | 13 | 18 | | 14 | 10 | | 15 | 9 | | 16 | 6 | | 17 | 13 | | 18 | 8 | | 19 | 4 | | 20 | 9 | | 21 | 4 | | 22 | 17 | | 23 | 6 | | 24 | 5 | | 25 | 3 | | 26 | 3 | | 27 | 22 | | 28 | 19 | | 29 | 9 | | 30 | 7 | | 31 | 8 | | 32 | 5 | | 33 | 5 | | 34 | 17 | | 35 | 12 | | 36 | 5 | | 37 | 3 | | 38 | 9 | | 39 | 13 | | 40 | 5 | | 41 | 7 | | 42 | 12 | | 43 | 6 | | 44 | 9 | | 45 | 6 | | 46 | 8 | | 47 | 23 | | 48 | 6 | | 49 | 13 |
| |
| 49.21% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.3492063492063492 | | totalSentences | 189 | | uniqueOpeners | 66 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 155 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 155 | | matches | | 0 | "She didn't slow." | | 1 | "She flowed through the narrowing" | | 2 | "She drew her service pistol" | | 3 | "His curly dark hair plastered" | | 4 | "He favored his right leg." | | 5 | "His eyes held no fear," | | 6 | "His accent carried the lilt" | | 7 | "She had the training." | | 8 | "He pulled out a bone." | | 9 | "Her breath fogged in the" | | 10 | "She kept the gun centered" | | 11 | "He reached past the peeling" | | 12 | "He raised his palms, empty." | | 13 | "He had come back silent," | | 14 | "He died in his flat" | | 15 | "She checked her pulse." | | 16 | "She would not hesitate." | | 17 | "She needed both hands for" | | 18 | "She drew her torch instead," | | 19 | "Her stomach turned." |
| | ratio | 0.239 | |
| 27.74% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 134 | | totalSentences | 155 | | matches | | 0 | "Quinn's shoulder drove into the" | | 1 | "Metal shrieked against the damp" | | 2 | "She didn't slow." | | 3 | "She flowed through the narrowing" | | 4 | "The suspect's silhouette blurred ahead," | | 5 | "Quinn's voice cracked like a" | | 6 | "She drew her service pistol" | | 7 | "Tomás kept moving." | | 8 | "His curly dark hair plastered" | | 9 | "Posters for gigs dead twenty" | | 10 | "He favored his right leg." | | 11 | "An old injury, possibly the" | | 12 | "Quinn saw the glint of" | | 13 | "Sweat and rain mingled in" | | 14 | "His eyes held no fear," | | 15 | "His accent carried the lilt" | | 16 | "Tomás slid a hand into" | | 17 | "Quinn tensed, muscles coiling." | | 18 | "She had the training." | | 19 | "He pulled out a bone." |
| | ratio | 0.865 | |
| 32.26% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 155 | | matches | | 0 | "If he pulled a weapon," |
| | ratio | 0.006 | |
| 73.17% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 4 | | matches | | 0 | "Metal shrieked against the damp brickwork, a sound that tore through the rhythm of her breathing." | | 1 | "A finger bone, stripped clean and carved with intricate sigils that seemed to shift under the sickly yellow glow of the streetlamp." | | 2 | "The runes made Quinn's teeth ache, a dull thrumming pressure behind her eyes that tasted of copper and ozone." | | 3 | "Tomás shouted in Spanish, his medallion flaring with a blinding white light that pushed the shadows back for a heartbeat." |
| |
| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 2 | | matches | | 0 | "Tomás spun around, his back against the kiosk" | | 1 | "The figure laughed, a sound like grinding stones" |
| |
| 66.67% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 3 | | fancyTags | | 0 | "Quinn ordered (order)" | | 1 | "The figure laughed (laugh)" | | 2 | "Quinn repeated (repeat)" |
| | dialogueSentences | 36 | | tagDensity | 0.083 | | leniency | 0.167 | | rawRatio | 1 | | effectiveRatio | 0.167 | |