| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 49 | | tagDensity | 0.347 | | leniency | 0.694 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 82.41% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1137 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | | 2 | | adverb | "barely above a whisper" | | count | 1 |
| | 3 | |
| | highlights | | 0 | "tightly" | | 1 | "precisely" | | 2 | "barely above a whisper" | | 3 | "slowly" |
| |
| 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) | |
| 29.64% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1137 | | totalAiIsms | 16 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | word | "scratched his head" | | count | 1 |
| | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | |
| | highlights | | 0 | "echoing" | | 1 | "enigmatic" | | 2 | "flicked" | | 3 | "eyebrow" | | 4 | "scanning" | | 5 | "scratched his head" | | 6 | "glinting" | | 7 | "raced" | | 8 | "reminder" | | 9 | "whisper" | | 10 | "racing" | | 11 | "determined" | | 12 | "scanned" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "The air was thick with" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 68 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 68 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 100 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1135 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 1 | | matches | | 0 | "As they moved away from the stall, Markham spoke up." |
| |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 58 | | wordCount | 731 | | uniqueNames | 12 | | maxNameDensity | 3.01 | | worstName | "Harlow" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 22 | | Quinn | 1 | | Tube | 1 | | Camden | 1 | | Veil | 2 | | Market | 6 | | Detective | 2 | | Inspector | 1 | | Markham | 9 | | Granger | 2 | | Kowalski | 1 | | Eva | 10 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Markham" | | 3 | "Kowalski" | | 4 | "Eva" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 1 | | matches | | 0 | "gate that seemed to hum with an energy she couldn't quite place" | | 1 | "quite place" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1135 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 100 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 25.22 | | std | 14.51 | | cv | 0.575 | | sampleLengths | | 0 | 83 | | 1 | 43 | | 2 | 48 | | 3 | 19 | | 4 | 55 | | 5 | 18 | | 6 | 40 | | 7 | 15 | | 8 | 41 | | 9 | 8 | | 10 | 40 | | 11 | 10 | | 12 | 4 | | 13 | 19 | | 14 | 15 | | 15 | 16 | | 16 | 49 | | 17 | 6 | | 18 | 30 | | 19 | 25 | | 20 | 29 | | 21 | 19 | | 22 | 22 | | 23 | 17 | | 24 | 26 | | 25 | 23 | | 26 | 24 | | 27 | 37 | | 28 | 11 | | 29 | 19 | | 30 | 26 | | 31 | 15 | | 32 | 21 | | 33 | 21 | | 34 | 25 | | 35 | 33 | | 36 | 15 | | 37 | 31 | | 38 | 12 | | 39 | 17 | | 40 | 25 | | 41 | 13 | | 42 | 29 | | 43 | 15 | | 44 | 26 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 68 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 123 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 100 | | ratio | 0.01 | | matches | | 0 | "It wasn't random; it was deliberate, almost ritualistic." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 733 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.021828103683492497 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.01227830832196453 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 100 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 100 | | mean | 11.35 | | std | 5.2 | | cv | 0.458 | | sampleLengths | | 0 | 22 | | 1 | 15 | | 2 | 13 | | 3 | 33 | | 4 | 10 | | 5 | 16 | | 6 | 17 | | 7 | 8 | | 8 | 9 | | 9 | 16 | | 10 | 15 | | 11 | 11 | | 12 | 8 | | 13 | 11 | | 14 | 19 | | 15 | 17 | | 16 | 8 | | 17 | 18 | | 18 | 13 | | 19 | 6 | | 20 | 21 | | 21 | 6 | | 22 | 9 | | 23 | 10 | | 24 | 16 | | 25 | 15 | | 26 | 4 | | 27 | 4 | | 28 | 4 | | 29 | 13 | | 30 | 10 | | 31 | 13 | | 32 | 10 | | 33 | 4 | | 34 | 9 | | 35 | 10 | | 36 | 6 | | 37 | 9 | | 38 | 7 | | 39 | 9 | | 40 | 12 | | 41 | 23 | | 42 | 14 | | 43 | 6 | | 44 | 17 | | 45 | 13 | | 46 | 15 | | 47 | 10 | | 48 | 16 | | 49 | 13 |
| |
| 67.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.41 | | totalSentences | 100 | | uniqueOpeners | 41 | |
| 49.02% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 68 | | matches | | 0 | "Instead, she moved to Granger's" |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 68 | | matches | | 0 | "She adjusted the collar of" | | 1 | "It was Detective Inspector Markham," | | 2 | "He stood near the entrance," | | 3 | "she acknowledged, striding over with" | | 4 | "Her eyes, dark and probing," | | 5 | "It wasn't random; it was" | | 6 | "She gestured to the blood" | | 7 | "Her eyes flicked to the" | | 8 | "she murmured, more to herself" | | 9 | "She clutched her worn leather" | | 10 | "They approached a stall manned" | | 11 | "He watched them with a" | | 12 | "he greeted, his voice smooth" | | 13 | "he admitted, his voice barely" | | 14 | "she said, her tone curt" |
| | ratio | 0.221 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 68 | | matches | | 0 | "Detective Harlow Quinn stepped out" | | 1 | "The air was thick with" | | 2 | "She adjusted the collar of" | | 3 | "The Veil Market, a place" | | 4 | "a voice called out, echoing" | | 5 | "It was Detective Inspector Markham," | | 6 | "He stood near the entrance," | | 7 | "she acknowledged, striding over with" | | 8 | "Her eyes, dark and probing," | | 9 | "The Market was a labyrinth" | | 10 | "Markham began, flipping through his" | | 11 | "Harlow crouched beside the body," | | 12 | "Granger lay sprawled on the" | | 13 | "A pool of blood had" | | 14 | "It wasn't random; it was" | | 15 | "Markham suggested, his tone casual," | | 16 | "Harlow's voice was sharp, cutting" | | 17 | "She gestured to the blood" | | 18 | "Markham frowned, glancing at the" | | 19 | "Harlow replied, standing up and" |
| | ratio | 0.926 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 7 | | matches | | 0 | "she murmured, more to herself than to Markham" | | 1 | "Harlow replied, her voice firm" | | 2 | "Harlow replied, a hint of a smile playing on her lips" | | 3 | "Harlow replied, her eyes narrowing as she surveyed the Market" | | 4 | "Eva asked, her voice low" | | 5 | "he greeted, his voice smooth and unctuous" | | 6 | "he admitted, his voice barely above a whisper" |
| |
| 47.96% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 5 | | fancyTags | | 0 | "a voice called out (call out)" | | 1 | "she acknowledged (acknowledge)" | | 2 | "Markham suggested (suggest)" | | 3 | "she murmured (murmur)" | | 4 | "he admitted (admit)" |
| | dialogueSentences | 49 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0.357 | | effectiveRatio | 0.204 | |