| 57.14% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said suddenly [suddenly]" | | 1 | "she said finally [finally]" |
| | dialogueSentences | 28 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.143 | | effectiveRatio | 0.143 | |
| 93.87% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 816 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 50.98% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 816 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "etched" | | 1 | "intricate" | | 2 | "tinged" | | 3 | "racing" | | 4 | "scanning" |
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| 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 | 54 | | matches | | |
| 89.95% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 54 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 67 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 810 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 65.25% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 590 | | uniqueNames | 9 | | maxNameDensity | 1.69 | | worstName | "Markham" | | maxWindowNameDensity | 3 | | worstWindowName | "Markham" | | discoveredNames | | Harlow | 1 | | Quinn | 7 | | Tube | 1 | | Camden | 1 | | Veil | 3 | | Market | 3 | | Detective | 2 | | Inspector | 1 | | Markham | 10 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Markham" |
| | places | (empty) | | globalScore | 0.653 | | windowScore | 0.667 | |
| 93.18% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | glossingSentenceCount | 1 | | matches | | 0 | "quite put her finger on" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 810 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 67 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 32.4 | | std | 17.05 | | cv | 0.526 | | sampleLengths | | 0 | 89 | | 1 | 44 | | 2 | 53 | | 3 | 44 | | 4 | 27 | | 5 | 22 | | 6 | 52 | | 7 | 32 | | 8 | 22 | | 9 | 46 | | 10 | 27 | | 11 | 10 | | 12 | 14 | | 13 | 35 | | 14 | 29 | | 15 | 46 | | 16 | 21 | | 17 | 7 | | 18 | 20 | | 19 | 29 | | 20 | 32 | | 21 | 18 | | 22 | 16 | | 23 | 35 | | 24 | 40 |
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| 85.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 54 | | matches | | 0 | "was supposed" | | 1 | "was littered" | | 2 | "was twisted" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 97 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 67 | | ratio | 0.06 | | matches | | 0 | "The platform was littered with debris—discarded crates, tattered tarps, and the remnants of what might have been a stall." | | 1 | "The compass, the token, the lack of evidence—it all pointed to something more than a simple escape gone wrong." | | 2 | "The compass, the token, the journal—it all pointed to something more than a simple accident." | | 3 | "The Veil Market, the rift, the shadows—it was all connected, she was sure of it." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 595 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, leather-bound book," |
| | adverbCount | 20 | | adverbRatio | 0.03361344537815126 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0033613445378151263 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 67 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 67 | | mean | 12.09 | | std | 6.39 | | cv | 0.529 | | sampleLengths | | 0 | 22 | | 1 | 23 | | 2 | 24 | | 3 | 20 | | 4 | 9 | | 5 | 15 | | 6 | 20 | | 7 | 8 | | 8 | 9 | | 9 | 19 | | 10 | 17 | | 11 | 9 | | 12 | 35 | | 13 | 12 | | 14 | 11 | | 15 | 4 | | 16 | 8 | | 17 | 14 | | 18 | 13 | | 19 | 16 | | 20 | 11 | | 21 | 12 | | 22 | 11 | | 23 | 21 | | 24 | 8 | | 25 | 14 | | 26 | 7 | | 27 | 11 | | 28 | 9 | | 29 | 11 | | 30 | 1 | | 31 | 7 | | 32 | 8 | | 33 | 19 | | 34 | 5 | | 35 | 5 | | 36 | 6 | | 37 | 8 | | 38 | 14 | | 39 | 19 | | 40 | 2 | | 41 | 9 | | 42 | 20 | | 43 | 10 | | 44 | 16 | | 45 | 20 | | 46 | 6 | | 47 | 15 | | 48 | 3 | | 49 | 4 |
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| 80.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.4925373134328358 | | totalSentences | 67 | | uniqueOpeners | 33 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 51 | | matches | | 0 | "Just the compass, and a" | | 1 | "Just the shadows, shifting and" |
| | ratio | 0.039 | |
| 70.98% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 51 | | matches | | 0 | "She adjusted the collar of" | | 1 | "It was just past midnight," | | 2 | "It was Detective Inspector Markham," | | 3 | "He stood near the entrance" | | 4 | "she acknowledged, striding over with" | | 5 | "Her eyes, sharp and discerning," | | 6 | "He handed her a small" | | 7 | "she murmured, more to herself" | | 8 | "she muttered, more to herself" | | 9 | "She stood, scanning the platform" | | 10 | "she said suddenly, pointing" | | 11 | "She turned her attention back" | | 12 | "He handed her a small," | | 13 | "It was a journal, filled" | | 14 | "she repeated, her mind racing" | | 15 | "She turned back to the" | | 16 | "she said finally, her voice" | | 17 | "she replied, her voice steady" | | 18 | "She turned away, her mind" |
| | ratio | 0.373 | |
| 58.04% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 41 | | totalSentences | 51 | | matches | | 0 | "Detective Harlow Quinn stepped out" | | 1 | "The air was thick with" | | 2 | "She adjusted the collar of" | | 3 | "It was just past midnight," | | 4 | "It was Detective Inspector Markham," | | 5 | "He stood near the entrance" | | 6 | "she acknowledged, striding over with" | | 7 | "Her eyes, sharp and discerning," | | 8 | "The platform was littered with" | | 9 | "Markham began, flipping through his" | | 10 | "He handed her a small" | | 11 | "Quinn turned the compass over" | | 12 | "she murmured, more to herself" | | 13 | "Markham said, his voice tinged" | | 14 | "Quinn crouched beside the body," | | 15 | "The man's face was twisted" | | 16 | "she muttered, more to herself" | | 17 | "Markham shrugged, his gaze darting" | | 18 | "Quinn shook her head, her" | | 19 | "Something was off, something she" |
| | ratio | 0.804 | |
| 98.04% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 51 | | matches | | 0 | "As if someone had staged" |
| | ratio | 0.02 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 6 | | matches | | 0 | "she murmured, more to herself than to Markham" | | 1 | "she muttered, more to herself than to Markham" | | 2 | "Quinn replied, her voice thoughtful" | | 3 | "she repeated, her mind racing" | | 4 | "she said finally, her voice firm" | | 5 | "she replied, her voice steady" |
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| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 4 | | fancyTags | | 0 | "she acknowledged (acknowledge)" | | 1 | "she murmured (murmur)" | | 2 | "she muttered (mutter)" | | 3 | "she repeated (repeat)" |
| | dialogueSentences | 28 | | tagDensity | 0.357 | | leniency | 0.714 | | rawRatio | 0.4 | | effectiveRatio | 0.286 | |