| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 1 | | adverbTags | | 0 | "Tomás shouted back [back]" |
| | dialogueSentences | 28 | | tagDensity | 0.786 | | leniency | 1 | | rawRatio | 0.045 | | effectiveRatio | 0.045 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1781 | | 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) | |
| 71.93% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1781 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "jaw clenched" | | 1 | "footsteps" | | 2 | "weight" | | 3 | "flickered" | | 4 | "echoing" | | 5 | "pulse" | | 6 | "velvet" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 168 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 168 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 174 | | 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 | 1781 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 80 | | wordCount | 1649 | | uniqueNames | 19 | | maxNameDensity | 1.7 | | worstName | "Quinn" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Tomás" | | discoveredNames | | Raven | 1 | | Nest | 3 | | Soho | 2 | | Quinn | 28 | | Herrera | 1 | | Tomás | 28 | | Saint | 1 | | Christopher | 1 | | Dean | 1 | | Street | 2 | | Tube | 1 | | Tottenham | 1 | | Court | 1 | | Road | 1 | | Camden | 2 | | High | 1 | | Static | 1 | | Morris | 1 | | Rain | 3 |
| | persons | | 0 | "Raven" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Tomás" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Static" | | 7 | "Morris" | | 8 | "Rain" |
| | places | | 0 | "Soho" | | 1 | "Dean" | | 2 | "Street" | | 3 | "Tottenham" | | 4 | "Court" | | 5 | "Road" | | 6 | "Camden" | | 7 | "High" |
| | globalScore | 0.651 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 134 | | 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 | 1781 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 174 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 41.42 | | std | 43.71 | | cv | 1.055 | | sampleLengths | | 0 | 121 | | 1 | 138 | | 2 | 7 | | 3 | 48 | | 4 | 8 | | 5 | 23 | | 6 | 3 | | 7 | 21 | | 8 | 4 | | 9 | 7 | | 10 | 9 | | 11 | 21 | | 12 | 61 | | 13 | 7 | | 14 | 5 | | 15 | 5 | | 16 | 6 | | 17 | 16 | | 18 | 32 | | 19 | 5 | | 20 | 9 | | 21 | 8 | | 22 | 77 | | 23 | 113 | | 24 | 4 | | 25 | 122 | | 26 | 86 | | 27 | 3 | | 28 | 95 | | 29 | 11 | | 30 | 12 | | 31 | 87 | | 32 | 77 | | 33 | 24 | | 34 | 83 | | 35 | 7 | | 36 | 6 | | 37 | 128 | | 38 | 103 | | 39 | 99 | | 40 | 4 | | 41 | 69 | | 42 | 7 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 168 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 249 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 174 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1654 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 12 | | adverbRatio | 0.007255139056831923 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0012091898428053204 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 174 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 174 | | mean | 10.24 | | std | 4.79 | | cv | 0.468 | | sampleLengths | | 0 | 14 | | 1 | 12 | | 2 | 19 | | 3 | 14 | | 4 | 7 | | 5 | 19 | | 6 | 5 | | 7 | 5 | | 8 | 8 | | 9 | 18 | | 10 | 20 | | 11 | 14 | | 12 | 10 | | 13 | 13 | | 14 | 8 | | 15 | 11 | | 16 | 16 | | 17 | 8 | | 18 | 13 | | 19 | 25 | | 20 | 7 | | 21 | 7 | | 22 | 8 | | 23 | 19 | | 24 | 14 | | 25 | 8 | | 26 | 5 | | 27 | 6 | | 28 | 12 | | 29 | 3 | | 30 | 8 | | 31 | 13 | | 32 | 4 | | 33 | 7 | | 34 | 6 | | 35 | 3 | | 36 | 10 | | 37 | 11 | | 38 | 12 | | 39 | 15 | | 40 | 6 | | 41 | 7 | | 42 | 12 | | 43 | 9 | | 44 | 7 | | 45 | 5 | | 46 | 5 | | 47 | 6 | | 48 | 8 | | 49 | 8 |
| |
| 39.08% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 19 | | diversityRatio | 0.25287356321839083 | | totalSentences | 174 | | uniqueOpeners | 44 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 150 | | matches | (empty) | | ratio | 0 | |
| 78.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 53 | | totalSentences | 150 | | matches | | 0 | "Her sharp jaw clenched against" | | 1 | "She lifted her left wrist" | | 2 | "He wore a plain dark" | | 3 | "His olive skin shone under" | | 4 | "He pressed a clean cloth" | | 5 | "He worked with the calm" | | 6 | "Her footsteps left wet prints" | | 7 | "She kept her hands loose" | | 8 | "Her coat dripped onto the" | | 9 | "Her broad shoulders filled the" | | 10 | "Her brown eyes did not" | | 11 | "His warm brown eyes held" | | 12 | "His short curly hair stuck" | | 13 | "Her boot squeaked on the" | | 14 | "She pushed through into the" | | 15 | "His bag thumped against his" | | 16 | "Her lungs burned with the" | | 17 | "Her boots struck puddles and" | | 18 | "She vaulted a stack of" | | 19 | "He glanced back over his" |
| | ratio | 0.353 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 139 | | totalSentences | 150 | | matches | | 0 | "The green neon sign above" | | 1 | "Harlow Quinn pressed her shoulder" | | 2 | "Water ran from her closely" | | 3 | "Her sharp jaw clenched against" | | 4 | "She lifted her left wrist" | | 5 | "The hands marked ten forty-seven." | | 6 | "A saxophone record hissed from" | | 7 | "The door swung open and" | | 8 | "A bartender polished a glass" | | 9 | "Tomás Herrera stood at the" | | 10 | "He wore a plain dark" | | 11 | "His olive skin shone under" | | 12 | "A scar ran along his" | | 13 | "He pressed a clean cloth" | | 14 | "Blood darkened the cloth in" | | 15 | "Tomás wrapped the hand with" | | 16 | "He worked with the calm" | | 17 | "Tomás said across the room" | | 18 | "Quinn crossed the floor in" | | 19 | "Her footsteps left wet prints" |
| | ratio | 0.927 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 150 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 78 | | technicalSentenceCount | 3 | | matches | | 0 | "He worked with the calm hands of a man who had done the same work in ambulances and doorways and places no hospital would record." | | 1 | "Quinn crossed behind them and stepped into a river of gutter water that reached her ankles." | | 2 | "Quinn ignored him and kept her eyes on Tomás and his bag and the medallion that bounced against his chest." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 36.36% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 22 | | fancyCount | 5 | | fancyTags | | 0 | "Quinn shouted (shout)" | | 1 | "Quinn shouted (shout)" | | 2 | "Quinn shouted (shout)" | | 3 | "Tomás shouted back (shout)" | | 4 | "Tomás shouted (shout)" |
| | dialogueSentences | 28 | | tagDensity | 0.786 | | leniency | 1 | | rawRatio | 0.227 | | effectiveRatio | 0.227 | |