| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 30 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1086 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 53.96% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1086 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "tracing" | | 1 | "wavered" | | 2 | "traced" | | 3 | "churned" | | 4 | "pristine" | | 5 | "stomach" | | 6 | "trembled" | | 7 | "magnetic" | | 8 | "perfect" | | 9 | "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 | 96 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 96 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 116 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 8 | | totalWords | 1086 | | ratio | 0.007 | | matches | | 0 | "Read the floor before you read the body." |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 17 | | wordCount | 869 | | uniqueNames | 7 | | maxNameDensity | 0.69 | | worstName | "Patel" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Patel" | | discoveredNames | | Patel | 6 | | Morris | 3 | | Charing | 1 | | Cross | 1 | | Road | 1 | | Cold | 2 | | Quinn | 3 |
| | persons | | 0 | "Patel" | | 1 | "Morris" | | 2 | "Quinn" |
| | places | | 0 | "Charing" | | 1 | "Cross" | | 2 | "Road" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 1086 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 116 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 23.11 | | std | 22.44 | | cv | 0.971 | | sampleLengths | | 0 | 12 | | 1 | 75 | | 2 | 22 | | 3 | 10 | | 4 | 10 | | 5 | 62 | | 6 | 4 | | 7 | 11 | | 8 | 68 | | 9 | 4 | | 10 | 2 | | 11 | 12 | | 12 | 7 | | 13 | 69 | | 14 | 11 | | 15 | 6 | | 16 | 61 | | 17 | 44 | | 18 | 8 | | 19 | 11 | | 20 | 8 | | 21 | 4 | | 22 | 5 | | 23 | 53 | | 24 | 6 | | 25 | 63 | | 26 | 19 | | 27 | 4 | | 28 | 40 | | 29 | 10 | | 30 | 12 | | 31 | 5 | | 32 | 43 | | 33 | 66 | | 34 | 6 | | 35 | 40 | | 36 | 11 | | 37 | 19 | | 38 | 7 | | 39 | 2 | | 40 | 11 | | 41 | 58 | | 42 | 24 | | 43 | 13 | | 44 | 23 | | 45 | 5 | | 46 | 20 |
| |
| 94.30% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 96 | | matches | | 0 | "been scorched" | | 1 | "been sealed" | | 2 | "were stained" |
| |
| 97.44% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 130 | | matches | | 0 | "was rising" | | 1 | "were breathing" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 116 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 871 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.021814006888633754 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 116 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 116 | | mean | 9.36 | | std | 6.77 | | cv | 0.724 | | sampleLengths | | 0 | 12 | | 1 | 16 | | 2 | 28 | | 3 | 6 | | 4 | 2 | | 5 | 23 | | 6 | 7 | | 7 | 15 | | 8 | 10 | | 9 | 3 | | 10 | 7 | | 11 | 5 | | 12 | 20 | | 13 | 2 | | 14 | 9 | | 15 | 26 | | 16 | 4 | | 17 | 11 | | 18 | 19 | | 19 | 23 | | 20 | 11 | | 21 | 2 | | 22 | 13 | | 23 | 4 | | 24 | 2 | | 25 | 12 | | 26 | 7 | | 27 | 34 | | 28 | 18 | | 29 | 17 | | 30 | 4 | | 31 | 7 | | 32 | 6 | | 33 | 16 | | 34 | 5 | | 35 | 12 | | 36 | 4 | | 37 | 4 | | 38 | 7 | | 39 | 13 | | 40 | 7 | | 41 | 6 | | 42 | 4 | | 43 | 16 | | 44 | 6 | | 45 | 3 | | 46 | 2 | | 47 | 3 | | 48 | 5 | | 49 | 8 |
| |
| 79.02% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.5 | | totalSentences | 116 | | uniqueOpeners | 58 | |
| 83.33% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 80 | | matches | | 0 | "Instead the dead man's face" | | 1 | "Instead a ring of marks" |
| | ratio | 0.025 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 80 | | matches | | 0 | "She straightened and walked the" | | 1 | "She pointed at the tiles" | | 2 | "She swept the torch toward" | | 3 | "She descended the short ladder" | | 4 | "His shoes were polished." | | 5 | "She crouched and lifted his" | | 6 | "She turned it over." | | 7 | "She'd seen that stain once" | | 8 | "Her stomach clenched." | | 9 | "She let the hand down." | | 10 | "She went through the coat" | | 11 | "She drew it into the" | | 12 | "She turned the thing in" | | 13 | "She watched the needle quiver," | | 14 | "She'd smelled it once before" | | 15 | "She slipped the compass into" | | 16 | "She didn't care." | | 17 | "She climbed back to the" | | 18 | "He flipped his notebook, angled" | | 19 | "She stepped down onto the" |
| | ratio | 0.25 | |
| 97.50% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 80 | | matches | | 0 | "The body lay across the" | | 1 | "Quinn crouched at the edge" | | 2 | "The skin should have been" | | 3 | "DC Patel said behind her" | | 4 | "Patel said nothing." | | 5 | "The torch beam wavered in" | | 6 | "This wasn't a working station." | | 7 | "The signs still read MORNINGTON" | | 8 | "Quinn knew it the moment" | | 9 | "She straightened and walked the" | | 10 | "A track of footprints led" | | 11 | "She pointed at the tiles" | | 12 | "She swept the torch toward" | | 13 | "Patel's mouth opened, closed." | | 14 | "She descended the short ladder" | | 15 | "The man was perhaps fifty," | | 16 | "His shoes were polished." | | 17 | "A man who had not" | | 18 | "She crouched and lifted his" | | 19 | "She turned it over." |
| | ratio | 0.725 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 80 | | matches | (empty) | | ratio | 0 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 3 | | matches | | 0 | "The fingertips were stained a faint grey-blue, the colour of a bruise that had given up." | | 1 | "A man who had walked twenty feet across filth and left perfect prints, yet whose own shoes were clean as a shop window." | | 2 | "The sweet smell had grown stronger, and now she understood it was rising, not drifting, seeping up from the tunnel as though the dark below were breathing." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 30 | | tagDensity | 0.1 | | leniency | 0.2 | | rawRatio | 0 | | effectiveRatio | 0 | |