| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 29 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn said aloud [aloud]" | | 1 | "Quinn stood again [again]" |
| | dialogueSentences | 52 | | tagDensity | 0.558 | | leniency | 1 | | rawRatio | 0.069 | | effectiveRatio | 0.069 | |
| 92.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1378 | | totalAiIsmAdverbs | 2 | | found | | 0 | | adverb | "ever so slightly" | | count | 1 |
| | 1 | |
| | highlights | | 0 | "ever so slightly" | | 1 | "slightly" |
| |
| 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) | |
| 56.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1378 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "gloom" | | 1 | "footsteps" | | 2 | "standard" | | 3 | "stomach" | | 4 | "traced" | | 5 | "complex" | | 6 | "porcelain" | | 7 | "resonance" | | 8 | "familiar" | | 9 | "silence" | | 10 | "pulse" |
| |
| 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 | 132 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 132 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 155 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 15 | | totalWords | 1370 | | ratio | 0.011 | | matches | | 0 | "DS Morris" | | 1 | "The Veil Market moves locations every full moon. Entry requires a bone token." |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 68.11% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 48 | | wordCount | 1099 | | uniqueNames | 15 | | maxNameDensity | 1.64 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 18 | | London | 3 | | Davies | 13 | | Tube | 1 | | Camden | 2 | | Victorian | 1 | | Celtic | 1 | | Polaroid | 1 | | Morris | 2 | | Codex | 1 | | Eva | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Davies" | | 3 | "Tube" | | 4 | "Victorian" | | 5 | "Morris" | | 6 | "Eva" | | 7 | "Market" |
| | places | | | globalScore | 0.681 | | windowScore | 0.833 | |
| 90.48% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 84 | | glossingSentenceCount | 2 | | matches | | 0 | "not quite" | | 1 | "sounded like a slow, patient pulse" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.73 | | wordCount | 1370 | | matches | | 0 | "not the wall, but drawn in what the lab had confirmed was DS Morris's blood, m" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 155 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 57 | | mean | 24.04 | | std | 17.33 | | cv | 0.721 | | sampleLengths | | 0 | 43 | | 1 | 8 | | 2 | 27 | | 3 | 27 | | 4 | 46 | | 5 | 34 | | 6 | 6 | | 7 | 51 | | 8 | 13 | | 9 | 14 | | 10 | 48 | | 11 | 8 | | 12 | 25 | | 13 | 44 | | 14 | 43 | | 15 | 4 | | 16 | 60 | | 17 | 9 | | 18 | 10 | | 19 | 14 | | 20 | 49 | | 21 | 6 | | 22 | 20 | | 23 | 22 | | 24 | 35 | | 25 | 47 | | 26 | 22 | | 27 | 18 | | 28 | 52 | | 29 | 24 | | 30 | 5 | | 31 | 4 | | 32 | 43 | | 33 | 10 | | 34 | 43 | | 35 | 15 | | 36 | 38 | | 37 | 4 | | 38 | 12 | | 39 | 39 | | 40 | 21 | | 41 | 48 | | 42 | 3 | | 43 | 34 | | 44 | 17 | | 45 | 5 | | 46 | 33 | | 47 | 21 | | 48 | 13 | | 49 | 2 |
| |
| 91.97% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 132 | | matches | | 0 | "was turned" | | 1 | "were focused" | | 2 | "were tied" | | 3 | "been dragged" | | 4 | "was plastered" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 182 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 155 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1107 | | adjectiveStacks | 1 | | stackExamples | | 0 | "faint, hair-thin lines" |
| | adverbCount | 30 | | adverbRatio | 0.02710027100271003 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004516711833785004 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 155 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 155 | | mean | 8.84 | | std | 5.96 | | cv | 0.675 | | sampleLengths | | 0 | 16 | | 1 | 11 | | 2 | 16 | | 3 | 8 | | 4 | 27 | | 5 | 5 | | 6 | 17 | | 7 | 5 | | 8 | 9 | | 9 | 18 | | 10 | 2 | | 11 | 17 | | 12 | 5 | | 13 | 13 | | 14 | 16 | | 15 | 6 | | 16 | 4 | | 17 | 6 | | 18 | 6 | | 19 | 9 | | 20 | 7 | | 21 | 7 | | 22 | 6 | | 23 | 6 | | 24 | 13 | | 25 | 4 | | 26 | 1 | | 27 | 9 | | 28 | 14 | | 29 | 8 | | 30 | 3 | | 31 | 8 | | 32 | 15 | | 33 | 7 | | 34 | 1 | | 35 | 6 | | 36 | 18 | | 37 | 1 | | 38 | 3 | | 39 | 12 | | 40 | 12 | | 41 | 17 | | 42 | 4 | | 43 | 10 | | 44 | 11 | | 45 | 18 | | 46 | 4 | | 47 | 13 | | 48 | 8 | | 49 | 7 |
| |
| 60.65% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.4064516129032258 | | totalSentences | 155 | | uniqueOpeners | 63 | |
| 58.48% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 114 | | matches | | 0 | "Just the single set coming" | | 1 | "Then, directly beside the symbol," |
| | ratio | 0.018 | |
| 69.12% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 43 | | totalSentences | 114 | | matches | | 0 | "She straightened her shoulders, ignoring" | | 1 | "she said as she approached" | | 2 | "Her colleague, Davies, stood under" | | 3 | "He gestured inside" | | 4 | "He shook his head" | | 5 | "Her military-trained posture didn't falter," | | 6 | "Her torchlight splashed against curved" | | 7 | "Her head was turned to" | | 8 | "Her eyes were open." | | 9 | "She shone her light along" | | 10 | "He gestured at the silent," | | 11 | "Her beam traced the victim's" | | 12 | "She stood and walked over" | | 13 | "It wasn't a smudge." | | 14 | "It was a symbol drawn" | | 15 | "It looked almost like a" | | 16 | "Her worn leather watch felt" | | 17 | "she said, the name heavy" | | 18 | "It was one of..." | | 19 | "Her eyes weren't glazed in" |
| | ratio | 0.377 | |
| 78.42% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 87 | | totalSentences | 114 | | matches | | 0 | "The metal gate groaned shut" | | 1 | "She straightened her shoulders, ignoring" | | 2 | "she said as she approached" | | 3 | "Her colleague, Davies, stood under" | | 4 | "He gestured inside" | | 5 | "He shook his head" | | 6 | "Quinn ducked under the tape" | | 7 | "Her military-trained posture didn't falter," | | 8 | "The tunnel swallowed her footsteps." | | 9 | "The air tasted of iron" | | 10 | "Her torchlight splashed against curved" | | 11 | "The silhouette lay ten metres" | | 12 | "Quinn slowed her approach." | | 13 | "A woman, slight build, dressed" | | 14 | "Her head was turned to" | | 15 | "Her eyes were open." | | 16 | "Quinn crouched, careful not to" | | 17 | "She shone her light along" | | 18 | "Quinn said aloud" | | 19 | "Davies supplied from behind her" |
| | ratio | 0.763 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 114 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 2 | | matches | | 0 | "Long, shallow grooves arced across it, as if something heavy had been dragged from the wall to the spot where the woman now lay." | | 1 | "The fingers were slightly curled, as if she'd been holding something small and cylindrical." |
| |
| 56.03% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 29 | | uselessAdditionCount | 4 | | matches | | 0 | "Davies said, his professional mask slipping into concern" | | 1 | "She traced, not touching, just following its path" | | 2 | "she told, her voice low and tight" | | 3 | "Quinn stood, turning to face the false panel in the wall" |
| |
| 92.31% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 3 | | fancyTags | | 0 | "Quinn murmured (murmur)" | | 1 | "he conceded (concede)" | | 2 | "she breathed (breathe)" |
| | dialogueSentences | 52 | | tagDensity | 0.212 | | leniency | 0.423 | | rawRatio | 0.273 | | effectiveRatio | 0.115 | |