| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.462 | | leniency | 0.923 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 77.78% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 900 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "tightly" | | 1 | "suddenly" | | 2 | "really" |
| |
| 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) | |
| 66.67% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 900 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoing" | | 2 | "gloom" | | 3 | "glinting" | | 4 | "looming" |
| |
| 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 | 1 | | narrationSentences | 48 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 48 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 55 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 896 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 61.50% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 791 | | uniqueNames | 9 | | maxNameDensity | 1.77 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 14 | | Tomás | 2 | | Herrera | 12 | | Tube | 1 | | Veil | 1 | | Market | 1 | | Spanish | 1 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Morris" |
| | places | (empty) | | globalScore | 0.615 | | windowScore | 0.667 | |
| 96.81% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like an abandoned Tube station ent" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 896 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 55 | | matches | (empty) | |
| 75.09% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 17 | | mean | 52.71 | | std | 21.76 | | cv | 0.413 | | sampleLengths | | 0 | 67 | | 1 | 76 | | 2 | 81 | | 3 | 79 | | 4 | 80 | | 5 | 81 | | 6 | 49 | | 7 | 30 | | 8 | 20 | | 9 | 26 | | 10 | 40 | | 11 | 25 | | 12 | 57 | | 13 | 22 | | 14 | 53 | | 15 | 60 | | 16 | 50 |
| |
| 90.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 48 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 137 | | matches | | 0 | "was heading" | | 1 | "was like stepping" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 55 | | ratio | 0.055 | | matches | | 0 | "The Veil Market, if the rumors were true—a place where the dregs of the supernatural world came to peddle their wares." | | 1 | "It was like stepping into another world—one she'd spent her entire career denying existed." | | 2 | "And she thought of the look in Herrera's eyes—that terrible mix of fear and resignation—as he'd turned and run." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 797 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.030112923462986198 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.006273525721455458 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 55 | | echoCount | 0 | | echoWords | (empty) | |
| 68.97% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 55 | | mean | 16.29 | | std | 5.25 | | cv | 0.322 | | sampleLengths | | 0 | 27 | | 1 | 16 | | 2 | 18 | | 3 | 6 | | 4 | 15 | | 5 | 13 | | 6 | 18 | | 7 | 9 | | 8 | 21 | | 9 | 17 | | 10 | 7 | | 11 | 15 | | 12 | 17 | | 13 | 25 | | 14 | 12 | | 15 | 20 | | 16 | 23 | | 17 | 24 | | 18 | 20 | | 19 | 20 | | 20 | 19 | | 21 | 21 | | 22 | 20 | | 23 | 21 | | 24 | 26 | | 25 | 14 | | 26 | 21 | | 27 | 19 | | 28 | 9 | | 29 | 15 | | 30 | 15 | | 31 | 18 | | 32 | 2 | | 33 | 12 | | 34 | 14 | | 35 | 17 | | 36 | 10 | | 37 | 13 | | 38 | 13 | | 39 | 12 | | 40 | 9 | | 41 | 18 | | 42 | 15 | | 43 | 15 | | 44 | 14 | | 45 | 8 | | 46 | 22 | | 47 | 17 | | 48 | 14 | | 49 | 27 |
| |
| 75.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.4727272727272727 | | totalSentences | 55 | | uniqueOpeners | 26 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 48 | | matches | | 0 | "Suddenly, a hand clamped down" | | 1 | "Then his shadow was gone," | | 2 | "Maybe it wasn't something to" |
| | ratio | 0.063 | |
| 61.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 48 | | matches | | 0 | "She'd been tailing Tomás Herrera" | | 1 | "She watched as Herrera took" | | 2 | "she muttered, slamming her fist" | | 3 | "She knew the area was" | | 4 | "She reached for her radio," | | 5 | "She ducked into the stairwell," | | 6 | "She made short work of" | | 7 | "She fished a flashlight from" | | 8 | "She caught glimpses of things" | | 9 | "It was like stepping into" | | 10 | "he replied with a smirk," | | 11 | "She reached for her cuffs," | | 12 | "He lunged at her, knocking" | | 13 | "he said, his voice thick" | | 14 | "She reached for her radio" | | 15 | "Her vision began to tunnel," | | 16 | "She thought of her partner," | | 17 | "Her last thought, before the" | | 18 | "She'd spent so long chasing" |
| | ratio | 0.396 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 34 | | totalSentences | 48 | | matches | | 0 | "Detective Harlow Quinn gripped the" | | 1 | "The wipers slapped a steady" | | 2 | "She'd been tailing Tomás Herrera" | | 3 | "She watched as Herrera took" | | 4 | "Quinn followed suit, the tires" | | 5 | "she muttered, slamming her fist" | | 6 | "She knew the area was" | | 7 | "Quinn pulled over and killed" | | 8 | "She reached for her radio," | | 9 | "She ducked into the stairwell," | | 10 | "The sound of Herrera's bike" | | 11 | "She made short work of" | | 12 | "The air turned heavy and" | | 13 | "She fished a flashlight from" | | 14 | "The tunnel stretched out before" | | 15 | "The Veil Market, if the" | | 16 | "Quinn's heart hammered against her" | | 17 | "The market was alive with" | | 18 | "She caught glimpses of things" | | 19 | "It was like stepping into" |
| | ratio | 0.708 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 48 | | matches | | 0 | "If she called this in," | | 1 | "If there was one thing" |
| | ratio | 0.042 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 1 | | matches | | 0 | "She caught glimpses of things that made her blood run cold: vials of shimmering liquid, fetishes carved from bone, the occasional flash of fangs or claw." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "he replied, his Spanish accent thickening as he spoke" | | 1 | "he said, his voice thick with regret" |
| |
| 73.08% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 13 | | tagDensity | 0.308 | | leniency | 0.615 | | rawRatio | 0.25 | | effectiveRatio | 0.154 | |