| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.667 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 86.96% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1150 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "sharply" | | 1 | "slightly" | | 2 | "suddenly" |
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| 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 | 1150 | | totalAiIsms | 31 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "reminder" | | 1 | "glistening" | | 2 | "pounding" | | 3 | "navigated" | | 4 | "racing" | | 5 | "determined" | | 6 | "scanning" | | 7 | "clandestine" | | 8 | "footsteps" | | 9 | "echoed" | | 10 | "cacophony" | | 11 | "unwavering" | | 12 | "quickened" | | 13 | "weight" | | 14 | "resolve" | | 15 | "whisper" | | 16 | "echoing" | | 17 | "silence" | | 18 | "tension" | | 19 | "palpable" |
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| 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 | 76 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 76 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 78 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1146 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 1125 | | uniqueNames | 6 | | maxNameDensity | 1.33 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 15 | | Quinn | 1 | | Raven | 1 | | Nest | 1 | | Veil | 2 | | Market | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" |
| | places | (empty) | | globalScore | 0.833 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1146 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 78 | | matches | (empty) | |
| 54.28% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 40.93 | | std | 13.92 | | cv | 0.34 | | sampleLengths | | 0 | 65 | | 1 | 66 | | 2 | 52 | | 3 | 23 | | 4 | 55 | | 5 | 53 | | 6 | 53 | | 7 | 52 | | 8 | 43 | | 9 | 43 | | 10 | 54 | | 11 | 52 | | 12 | 39 | | 13 | 36 | | 14 | 39 | | 15 | 55 | | 16 | 33 | | 17 | 35 | | 18 | 30 | | 19 | 42 | | 20 | 25 | | 21 | 29 | | 22 | 35 | | 23 | 13 | | 24 | 30 | | 25 | 32 | | 26 | 51 | | 27 | 11 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 76 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 175 | | matches | | 0 | "was heading" | | 1 | "was taking" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 78 | | ratio | 0.013 | | matches | | 0 | "She knew what lay beyond it—a hidden back room used for clandestine meetings." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1129 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.022143489813994686 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.00974313551815766 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 78 | | echoCount | 0 | | echoWords | (empty) | |
| 91.23% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 78 | | mean | 14.69 | | std | 5.55 | | cv | 0.378 | | sampleLengths | | 0 | 28 | | 1 | 17 | | 2 | 20 | | 3 | 10 | | 4 | 15 | | 5 | 11 | | 6 | 30 | | 7 | 18 | | 8 | 9 | | 9 | 25 | | 10 | 16 | | 11 | 7 | | 12 | 12 | | 13 | 17 | | 14 | 8 | | 15 | 18 | | 16 | 9 | | 17 | 24 | | 18 | 3 | | 19 | 17 | | 20 | 12 | | 21 | 17 | | 22 | 10 | | 23 | 14 | | 24 | 23 | | 25 | 16 | | 26 | 13 | | 27 | 13 | | 28 | 20 | | 29 | 10 | | 30 | 14 | | 31 | 16 | | 32 | 13 | | 33 | 13 | | 34 | 3 | | 35 | 15 | | 36 | 23 | | 37 | 15 | | 38 | 21 | | 39 | 16 | | 40 | 8 | | 41 | 12 | | 42 | 19 | | 43 | 22 | | 44 | 14 | | 45 | 26 | | 46 | 13 | | 47 | 28 | | 48 | 14 | | 49 | 13 |
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| 42.31% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.2692307692307692 | | totalSentences | 78 | | uniqueOpeners | 21 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 76 | | matches | | 0 | "Then, with a burst of" | | 1 | "Instead, she took a step" | | 2 | "Suddenly, the tunnel opened into" | | 3 | "Then, with a sudden burst" |
| | ratio | 0.053 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 76 | | matches | | 0 | "Her breath came in steady" | | 1 | "she shouted, her voice cutting" | | 2 | "He hesitated, casting a desperate" | | 3 | "she called out, her voice" | | 4 | "She could follow him, but" | | 5 | "She'd been here before, knew" | | 6 | "She knew what lay beyond" | | 7 | "She approached the bookshelf, her" | | 8 | "Her senses were on high" | | 9 | "She'd heard whispers of this" | | 10 | "It was a haven for" | | 11 | "She could see the suspect" | | 12 | "She took a deep breath," | | 13 | "She couldn't let him slip" | | 14 | "She pushed through the crowd," | | 15 | "He was heading towards the" | | 16 | "She hesitated for a moment," | | 17 | "Her footsteps echoed in the" | | 18 | "she called out, her voice" | | 19 | "She grabbed his arm, twisting" |
| | ratio | 0.289 | |
| 58.68% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 76 | | matches | | 0 | "Detective Harlow Quinn's boots splashed" | | 1 | "Her breath came in steady" | | 2 | "The suspect, a wiry man" | | 3 | "she shouted, her voice cutting" | | 4 | "The man glanced back, his" | | 5 | "Harlow followed, her heart pounding" | | 6 | "The alley was narrow, the" | | 7 | "The suspect skidded to a" | | 8 | "He hesitated, casting a desperate" | | 9 | "Harlow slowed her pace, her" | | 10 | "she called out, her voice" | | 11 | "The man hesitated, his eyes" | | 12 | "Harlow cursed under her breath," | | 13 | "She could follow him, but" | | 14 | "The alley was a dead" | | 15 | "The Raven's Nest." | | 16 | "She'd been here before, knew" | | 17 | "The bar was dimly lit," | | 18 | "Patrons glanced up as she" | | 19 | "Harlow ignored them, her eyes" |
| | ratio | 0.803 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 76 | | matches | (empty) | | ratio | 0 | |
| 52.15% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 63 | | technicalSentenceCount | 8 | | matches | | 0 | "Detective Harlow Quinn's boots splashed through the puddles, each step a sharp reminder of the relentless rain that had turned the city streets into a slick, gl…" | | 1 | "The alley was narrow, the walls closing in like the jaws of a trap, but she navigated it with the precision of someone who had spent years in the field." | | 2 | "Harlow slowed her pace, her hand instinctively reaching for the worn leather watch on her wrist, a grounding gesture that reminded her of her purpose." | | 3 | "The distinctive green neon sign above the bar cast an eerie glow, highlighting the old maps and black-and-white photographs that adorned the walls." | | 4 | "She'd heard whispers of this place, an underground market that moved locations every full moon." | | 5 | "The market was a sensory overload, the sounds of haggling and whispered conversations blending into a cacophony that threatened to overwhelm her." | | 6 | "He was heading towards the far end of the market, where the stalls gave way to a series of tunnels that led deeper into the underground." | | 7 | "As she led the suspect back through the tunnel, her mind was already working, piecing together the puzzle that had brought her here." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 4 | | matches | | 0 | "she shouted, her voice cutting through the night air" | | 1 | "she called out, her voice steady despite the adrenaline coursing through her veins" | | 2 | "she called out, her voice echoing in the chamber" | | 3 | "she said, her voice calm and steady" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 3 | | fancyTags | | 0 | "she shouted (shout)" | | 1 | "she called out (call out)" | | 2 | "she called out (call out)" |
| | dialogueSentences | 6 | | tagDensity | 0.667 | | leniency | 1 | | rawRatio | 0.75 | | effectiveRatio | 0.75 | |