| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1519 | | 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) | |
| 24.29% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1519 | | totalAiIsms | 23 | | found | | | highlights | | 0 | "measured" | | 1 | "shattered" | | 2 | "footsteps" | | 3 | "weight" | | 4 | "glint" | | 5 | "charm" | | 6 | "fractured" | | 7 | "echoed" | | 8 | "mechanical" | | 9 | "silence" | | 10 | "etched" | | 11 | "aligned" | | 12 | "pulsed" | | 13 | "traced" | | 14 | "flicked" | | 15 | "velvet" |
| |
| 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 | 224 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 224 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 224 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1519 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 1510 | | uniqueNames | 16 | | maxNameDensity | 0.93 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 3 | | Met | 3 | | Police | 1 | | Christopher | 1 | | Tomás | 1 | | Herrera | 2 | | Raven | 1 | | Nest | 1 | | Morris | 4 | | Brixton | 1 | | Quinn | 14 | | Veil | 1 | | Market | 2 | | Shoreditch | 1 | | Water | 3 | | You | 4 |
| | persons | | 0 | "Met" | | 1 | "Christopher" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Raven" | | 5 | "Morris" | | 6 | "Quinn" | | 7 | "Water" | | 8 | "You" |
| | places | | 0 | "Camden" | | 1 | "Brixton" | | 2 | "Market" | | 3 | "Shoreditch" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 116 | | 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 | 1519 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 224 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 32.32 | | std | 25.49 | | cv | 0.789 | | sampleLengths | | 0 | 64 | | 1 | 66 | | 2 | 74 | | 3 | 5 | | 4 | 86 | | 5 | 65 | | 6 | 60 | | 7 | 58 | | 8 | 66 | | 9 | 7 | | 10 | 1 | | 11 | 10 | | 12 | 5 | | 13 | 54 | | 14 | 11 | | 15 | 18 | | 16 | 10 | | 17 | 20 | | 18 | 32 | | 19 | 37 | | 20 | 81 | | 21 | 8 | | 22 | 8 | | 23 | 5 | | 24 | 8 | | 25 | 12 | | 26 | 59 | | 27 | 58 | | 28 | 30 | | 29 | 20 | | 30 | 42 | | 31 | 88 | | 32 | 22 | | 33 | 11 | | 34 | 48 | | 35 | 18 | | 36 | 29 | | 37 | 6 | | 38 | 8 | | 39 | 13 | | 40 | 39 | | 41 | 55 | | 42 | 41 | | 43 | 11 | | 44 | 21 | | 45 | 24 | | 46 | 5 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 224 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 292 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 224 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 809 | | adjectiveStacks | 1 | | stackExamples | | 0 | "ceramic shut behind him." |
| | adverbCount | 15 | | adverbRatio | 0.018541409147095178 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.002472187886279357 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 224 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 224 | | mean | 6.78 | | std | 4.42 | | cv | 0.652 | | sampleLengths | | 0 | 14 | | 1 | 10 | | 2 | 11 | | 3 | 20 | | 4 | 5 | | 5 | 4 | | 6 | 7 | | 7 | 9 | | 8 | 7 | | 9 | 12 | | 10 | 20 | | 11 | 5 | | 12 | 3 | | 13 | 3 | | 14 | 11 | | 15 | 2 | | 16 | 4 | | 17 | 11 | | 18 | 6 | | 19 | 9 | | 20 | 4 | | 21 | 11 | | 22 | 5 | | 23 | 11 | | 24 | 2 | | 25 | 3 | | 26 | 10 | | 27 | 12 | | 28 | 3 | | 29 | 14 | | 30 | 5 | | 31 | 11 | | 32 | 6 | | 33 | 7 | | 34 | 4 | | 35 | 14 | | 36 | 4 | | 37 | 18 | | 38 | 2 | | 39 | 30 | | 40 | 5 | | 41 | 6 | | 42 | 2 | | 43 | 5 | | 44 | 3 | | 45 | 7 | | 46 | 16 | | 47 | 11 | | 48 | 3 | | 49 | 5 |
| |
| 55.06% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.3705357142857143 | | totalSentences | 224 | | uniqueOpeners | 83 | |
| 33.84% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 197 | | matches | | 0 | "More than one pair." | | 1 | "Then the gatekeeper resets the" |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 59 | | totalSentences | 197 | | matches | | 0 | "She kept the distance at" | | 1 | "She wiped it away with" | | 2 | "Her lungs burned." | | 3 | "She ignored it." | | 4 | "His footsteps splashed through pooled" | | 5 | "He vaulted a rusted bike" | | 6 | "He caught it before it" | | 7 | "His only answer came as" | | 8 | "He reached the alley’s end" | | 9 | "He took the concrete steps" | | 10 | "She’d seen that same charm" | | 11 | "Her breath plumed white in" | | 12 | "Her boots found purchase on" | | 13 | "He dropped to one knee," | | 14 | "He slid through the gap" | | 15 | "She ran her fingers along" | | 16 | "She shifted her weight and" | | 17 | "They pulled his badge from" | | 18 | "They left silence." | | 19 | "She unclipped her radio." |
| | ratio | 0.299 | |
| 38.68% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 166 | | totalSentences | 197 | | matches | | 0 | "Rain lashed the Camden pavement" | | 1 | "Quinn’s boots struck the wet" | | 2 | "The figure ahead bolted past" | | 3 | "Puddles shattered under his soles." | | 4 | "Spray coated the brickwork." | | 5 | "She kept the distance at" | | 6 | "Water dripped from the brim" | | 7 | "She wiped it away with" | | 8 | "The chase clocked four minutes." | | 9 | "Her lungs burned." | | 10 | "She ignored it." | | 11 | "The suspect cut left down" | | 12 | "Brick walls closed in." | | 13 | "The smell of wet cardboard" | | 14 | "His footsteps splashed through pooled" | | 15 | "He vaulted a rusted bike" | | 16 | "The satchel strap slipped." | | 17 | "He caught it before it" | | 18 | "Metal groaned under his weight." | | 19 | "A plastic crate toppled and" |
| | ratio | 0.843 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 197 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | |