| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn said slowly [slowly]" |
| | dialogueSentences | 43 | | tagDensity | 0.488 | | leniency | 0.977 | | rawRatio | 0.048 | | effectiveRatio | 0.047 | |
| 69.54% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1149 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "slowly" | | 1 | "very" | | 2 | "suddenly" | | 3 | "utterly" | | 4 | "cautiously" |
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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) | |
| 21.67% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1149 | | totalAiIsms | 18 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | word | "down her spine" | | count | 1 |
| | 14 | | | 15 | | | 16 | |
| | highlights | | 0 | "echoing" | | 1 | "chill" | | 2 | "stark" | | 3 | "tracing" | | 4 | "etched" | | 5 | "intricate" | | 6 | "unreadable" | | 7 | "scanned" | | 8 | "flickered" | | 9 | "fleeting" | | 10 | "eyebrow" | | 11 | "racing" | | 12 | "pulse" | | 13 | "down her spine" | | 14 | "otherworldly" | | 15 | "analyzed" | | 16 | "complex" |
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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 | 2 | | narrationSentences | 91 | | matches | | 0 | "d with urgency" | | 1 | "felt a prickle" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 91 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 113 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1147 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 8.87% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 744 | | uniqueNames | 7 | | maxNameDensity | 2.82 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Eva" | | discoveredNames | | Harlow | 1 | | Quinn | 21 | | Davies | 5 | | Inspector | 1 | | Mallory | 7 | | Eva | 9 | | Kowalski | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Davies" | | 3 | "Inspector" | | 4 | "Mallory" | | 5 | "Eva" | | 6 | "Kowalski" |
| | places | (empty) | | globalScore | 0.089 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 1 | | matches | | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.616 | | wordCount | 1147 | | matches | | 0 | "Not a violent scream, not one of fear, but of…" | | 1 | "not one of fear, but of…" | | 2 | "not north, but pointing…" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 113 | | matches | (empty) | |
| 87.44% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 28.68 | | std | 13.08 | | cv | 0.456 | | sampleLengths | | 0 | 55 | | 1 | 54 | | 2 | 22 | | 3 | 36 | | 4 | 9 | | 5 | 37 | | 6 | 41 | | 7 | 33 | | 8 | 24 | | 9 | 8 | | 10 | 24 | | 11 | 9 | | 12 | 35 | | 13 | 17 | | 14 | 36 | | 15 | 31 | | 16 | 53 | | 17 | 32 | | 18 | 14 | | 19 | 14 | | 20 | 16 | | 21 | 44 | | 22 | 30 | | 23 | 13 | | 24 | 41 | | 25 | 15 | | 26 | 31 | | 27 | 3 | | 28 | 34 | | 29 | 13 | | 30 | 21 | | 31 | 41 | | 32 | 25 | | 33 | 25 | | 34 | 24 | | 35 | 44 | | 36 | 35 | | 37 | 39 | | 38 | 31 | | 39 | 38 |
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| 97.55% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 91 | | matches | | 0 | "were covered" | | 1 | "was pulled" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 138 | | matches | (empty) | |
| 67.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 113 | | ratio | 0.027 | | matches | | 0 | "The air tasted metallic, thick with dampness and something else– something indefinable, faintly floral, yet unsettling." | | 1 | "It flickered, like heat rising from asphalt, and for a moment, Quinn could swear she saw something move within it—a fleeting glimpse of impossible geometry." | | 2 | "She knew this feeling – it had haunted her ever since the case that took her partner." |
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| 78.51% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 746 | | adjectiveStacks | 2 | | stackExamples | | 0 | "lay untouched beside him." | | 1 | "worn, leather-bound book." |
| | adverbCount | 35 | | adverbRatio | 0.04691689008042895 | | lyAdverbCount | 18 | | lyAdverbRatio | 0.024128686327077747 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 113 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 113 | | mean | 10.15 | | std | 6.74 | | cv | 0.664 | | sampleLengths | | 0 | 10 | | 1 | 11 | | 2 | 16 | | 3 | 18 | | 4 | 22 | | 5 | 10 | | 6 | 1 | | 7 | 11 | | 8 | 10 | | 9 | 10 | | 10 | 5 | | 11 | 7 | | 12 | 7 | | 13 | 12 | | 14 | 5 | | 15 | 3 | | 16 | 9 | | 17 | 9 | | 18 | 17 | | 19 | 10 | | 20 | 10 | | 21 | 10 | | 22 | 11 | | 23 | 20 | | 24 | 13 | | 25 | 12 | | 26 | 4 | | 27 | 4 | | 28 | 13 | | 29 | 10 | | 30 | 1 | | 31 | 8 | | 32 | 7 | | 33 | 13 | | 34 | 4 | | 35 | 6 | | 36 | 3 | | 37 | 10 | | 38 | 14 | | 39 | 11 | | 40 | 8 | | 41 | 9 | | 42 | 5 | | 43 | 31 | | 44 | 7 | | 45 | 24 | | 46 | 10 | | 47 | 18 | | 48 | 25 | | 49 | 11 |
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| 70.50% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.46017699115044247 | | totalSentences | 113 | | uniqueOpeners | 52 | |
| 82.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 81 | | matches | | 0 | "Just the stark, unsettling calm" | | 1 | "Suddenly, Eva Kowalski appeared, pushing" |
| | ratio | 0.025 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 81 | | matches | | 0 | "His eyes were wide, fixed" | | 1 | "He gestured towards the wound." | | 2 | "He shifted uncomfortably, running a" | | 3 | "Her fingers brushed against something" | | 4 | "She picked it up." | | 5 | "It hummed faintly in her" | | 6 | "He wore a tailored suit" | | 7 | "she held up the compass" | | 8 | "She scanned the platform again," | | 9 | "Her gaze settled on a" | | 10 | "It flickered, like heat rising" | | 11 | "She pointed to the shimmering" | | 12 | "Her curly red hair was" | | 13 | "She clutched her worn leather" | | 14 | "She fumbled with the straps" | | 15 | "he muttered under his breath" | | 16 | "She'd learned long ago to" | | 17 | "She reached into her satchel" | | 18 | "She flipped through the pages," | | 19 | "It was all starting to" |
| | ratio | 0.296 | |
| 15.56% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 72 | | totalSentences | 81 | | matches | | 0 | "Rain slicked the grimy concrete" | | 1 | "Water dripped from the curved" | | 2 | "The air tasted metallic, thick" | | 3 | "Detective Harlow Quinn ignored the" | | 4 | "A body lay sprawled near" | | 5 | "His eyes were wide, fixed" | | 6 | "A single, crimson stain bloomed" | | 7 | "Sergeant Davies said, his voice" | | 8 | "He gestured towards the wound." | | 9 | "Quinn knelt, careful not to" | | 10 | "The man’s expensive shoes were" | | 11 | "Quinn asked, already knowing the" | | 12 | "He shifted uncomfortably, running a" | | 13 | "Quinn grunted, her eyes tracing" | | 14 | "The walls were covered in" | | 15 | "Quinn murmured, pulling on a" | | 16 | "Her fingers brushed against something" | | 17 | "She picked it up." | | 18 | "A small brass compass." | | 19 | "The casing was dull with" |
| | ratio | 0.889 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 1 | | matches | | 0 | "Detective Harlow Quinn ignored the chill seeping into her bones, her gaze sweeping across the tableau before her." |
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| 29.76% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 4 | | matches | | 0 | "Sergeant Davies said, his voice echoing too loudly" | | 1 | "Eva said, her voice low and urgent" | | 2 | "Quinn repeated, her mind racing" | | 3 | "Quinn ordered, her voice sharp" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 11 | | fancyTags | | 0 | "Quinn murmured (murmur)" | | 1 | "Quinn stated (state)" | | 2 | "Quinn declared (declare)" | | 3 | "Quinn corrected (correct)" | | 4 | "Eva blurted out (blurt out)" | | 5 | "he muttered (mutter)" | | 6 | "Quinn demanded (demand)" | | 7 | "Quinn explained (explain)" | | 8 | "Quinn repeated (repeat)" | | 9 | "Eva clarified (clarify)" | | 10 | "Quinn ordered (order)" |
| | dialogueSentences | 43 | | tagDensity | 0.349 | | leniency | 0.698 | | rawRatio | 0.733 | | effectiveRatio | 0.512 | |