| 18.18% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn said grimly [grimly]" |
| | dialogueSentences | 11 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0.25 | | effectiveRatio | 0.182 | |
| 84.50% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 968 | | totalAiIsmAdverbs | 3 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 968 | | totalAiIsms | 25 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "flickered" | | 1 | "sinister" | | 2 | "echoed" | | 3 | "reminder" | | 4 | "weight" | | 5 | "scanned" | | 6 | "flicker" | | 7 | "facade" | | 8 | "footsteps" | | 9 | "tension" | | 10 | "silence" | | 11 | "pulse" | | 12 | "thundered" | | 13 | "reverberated" | | 14 | "depths" | | 15 | "familiar" | | 16 | "wavered" | | 17 | "trembled" | | 18 | "pulsed" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "without second thought" | | count | 1 |
|
| | highlights | | 0 | "Without a second thought" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 82 | | matches | (empty) | |
| 90.59% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 82 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 88 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 952 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 882 | | uniqueNames | 7 | | maxNameDensity | 1.25 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 11 | | Glock | 1 | | Veil | 1 | | Market | 1 | | Morris | 1 | | Detective | 1 | | Quinn | 6 |
| | persons | | 0 | "Harlow" | | 1 | "Morris" | | 2 | "Detective" | | 3 | "Quinn" |
| | places | (empty) | | globalScore | 0.876 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 94.96% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.05 | | wordCount | 952 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 88 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 18.31 | | std | 13.53 | | cv | 0.739 | | sampleLengths | | 0 | 28 | | 1 | 33 | | 2 | 4 | | 3 | 49 | | 4 | 56 | | 5 | 22 | | 6 | 28 | | 7 | 41 | | 8 | 33 | | 9 | 43 | | 10 | 3 | | 11 | 33 | | 12 | 20 | | 13 | 43 | | 14 | 31 | | 15 | 6 | | 16 | 35 | | 17 | 25 | | 18 | 7 | | 19 | 10 | | 20 | 34 | | 21 | 7 | | 22 | 25 | | 23 | 5 | | 24 | 18 | | 25 | 7 | | 26 | 26 | | 27 | 10 | | 28 | 7 | | 29 | 3 | | 30 | 28 | | 31 | 12 | | 32 | 24 | | 33 | 23 | | 34 | 4 | | 35 | 14 | | 36 | 11 | | 37 | 20 | | 38 | 5 | | 39 | 21 | | 40 | 7 | | 41 | 10 | | 42 | 8 | | 43 | 11 | | 44 | 5 | | 45 | 7 | | 46 | 14 | | 47 | 5 | | 48 | 1 | | 49 | 10 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 82 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 158 | | matches | | 0 | "was cooling" | | 1 | "was being" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 12 | | totalSentences | 88 | | ratio | 0.136 | | matches | | 0 | "Harlow’s boots pounded the uneven pavement as she closed the gap—just a few more steps, then she’d get a clear shot at her target." | | 1 | "She couldn’t afford hesitation—even if the shadows whispered warnings she refused to hear." | | 2 | "Her instincts screamed danger—this was no ordinary hideout." | | 3 | "The air tasted sharp with stale smoke and something else—old magic, perhaps, or desperation." | | 4 | "Tales spun in whispered tones about this place—an illegal bazaar for the supernatural, a hive of broken deals and darker purposes." | | 5 | "Harlow scanned for the suspect and saw a flicker of movement near a bookshelf built into the back wall—a barely perceptible shift in the layers of dust." | | 6 | "Every instinct screamed to retreat, but she couldn’t—Morris’s memory was a quiet drum behind each breath, a reminder of unfinished business." | | 7 | "Every step dragged her further from the world she knew, deeper into a maze where danger lurked in every corner—and trust was the rarest currency." | | 8 | "The air grew colder—faint traces of sulphur and old incense warred for dominance." | | 9 | "Her breath hitched—Detective Quinn, at arm’s length." | | 10 | "Ahead, the suspect’s footfalls echoed rapidly—no chance of catch-up unless she took the risk." | | 11 | "Quinn smiled—thin, like a blade slicing the last thread of patience." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 858 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.022144522144522144 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.008158508158508158 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 88 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 88 | | mean | 10.82 | | std | 6.12 | | cv | 0.566 | | sampleLengths | | 0 | 4 | | 1 | 24 | | 2 | 9 | | 3 | 14 | | 4 | 10 | | 5 | 4 | | 6 | 21 | | 7 | 13 | | 8 | 15 | | 9 | 17 | | 10 | 11 | | 11 | 15 | | 12 | 13 | | 13 | 16 | | 14 | 6 | | 15 | 2 | | 16 | 8 | | 17 | 6 | | 18 | 12 | | 19 | 8 | | 20 | 20 | | 21 | 13 | | 22 | 19 | | 23 | 14 | | 24 | 9 | | 25 | 34 | | 26 | 3 | | 27 | 3 | | 28 | 21 | | 29 | 9 | | 30 | 16 | | 31 | 4 | | 32 | 27 | | 33 | 16 | | 34 | 3 | | 35 | 7 | | 36 | 21 | | 37 | 6 | | 38 | 19 | | 39 | 11 | | 40 | 5 | | 41 | 12 | | 42 | 13 | | 43 | 7 | | 44 | 4 | | 45 | 6 | | 46 | 12 | | 47 | 10 | | 48 | 12 | | 49 | 7 |
| |
| 62.88% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.4318181818181818 | | totalSentences | 88 | | uniqueOpeners | 38 | |
| 83.33% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 80 | | matches | | 0 | "Suddenly, a voice, low and" | | 1 | "Suddenly the gates slammed shut." |
| | ratio | 0.025 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 80 | | matches | | 0 | "She barreled past the shuttered" | | 1 | "She couldn’t afford hesitation—even if" | | 2 | "Her instincts screamed danger—this was" | | 3 | "She tightened her grip on" | | 4 | "Her heart hammered as she" | | 5 | "Her gut twisted." | | 6 | "She spotted a weathered face" | | 7 | "She was being watched." | | 8 | "Her jaw tightened." | | 9 | "Her boots stilled for a" | | 10 | "She brushed past a stall" | | 11 | "Her grip tightened on the" | | 12 | "she hissed to herself" | | 13 | "She rounded a corner, gun" | | 14 | "She whipped around." | | 15 | "Her breath hitched—Detective Quinn, at" |
| | ratio | 0.2 | |
| 60.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 80 | | matches | | 0 | "Tyres screeched behind her." | | 1 | "Harlow’s boots pounded the uneven" | | 2 | "The suspect’s shadow flickered between" | | 3 | "The city’s grime gleamed wet" | | 4 | "She barreled past the shuttered" | | 5 | "The suspect dove into a" | | 6 | "The alley reeked of damp" | | 7 | "The thudding of her boots" | | 8 | "The figure ahead was nimble," | | 9 | "Harlow’s fingers brushed her worn" | | 10 | "She couldn’t afford hesitation—even if" | | 11 | "The suspect slipped inside without" | | 12 | "Her instincts screamed danger—this was" | | 13 | "She tightened her grip on" | | 14 | "The staircase reeked of mold" | | 15 | "Each step rattled beneath her" | | 16 | "The patter of rain above" | | 17 | "Her heart hammered as she" | | 18 | "The air tasted sharp with" | | 19 | "Stalls groaned under heaps of" |
| | ratio | 0.8 | |
| 62.50% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 80 | | matches | | 0 | "Before Harlow could answer, the" |
| | ratio | 0.013 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn said, eyes sharp as glass" |
| |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "she hissed (hiss)" | | 1 | "The suspect’s voice called out (call out)" |
| | dialogueSentences | 11 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0.5 | | effectiveRatio | 0.364 | |