| 46.15% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 1 | | adverbTags | | 0 | "he called softly [softly]" |
| | dialogueSentences | 13 | | tagDensity | 0.462 | | leniency | 0.923 | | rawRatio | 0.167 | | effectiveRatio | 0.154 | |
| 67.86% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1089 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "softly" | | 1 | "slowly" | | 2 | "really" | | 3 | "slightly" | | 4 | "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) | |
| 58.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1089 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "streaming" | | 1 | "quickened" | | 2 | "stomach" | | 3 | "coded" | | 4 | "echoing" | | 5 | "echoed" | | 6 | "electric" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 57 | | matches | (empty) | |
| 17.54% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 3 | | narrationSentences | 57 | | filterMatches | | | hedgeMatches | | 0 | "began to" | | 1 | "appeared to" | | 2 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 64 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1081 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 70.21% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 940 | | uniqueNames | 17 | | maxNameDensity | 1.6 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 15 | | Tomás | 1 | | Herrera | 8 | | Soho | 1 | | Raven | 3 | | Nest | 3 | | Saint | 1 | | Christopher | 1 | | Morris | 3 | | Glock | 2 | | Victorian | 1 | | Underground | 1 | | London | 2 | | Spanish | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Raven" | | 5 | "Nest" | | 6 | "Saint" | | 7 | "Christopher" | | 8 | "Morris" | | 9 | "Glock" | | 10 | "Spanish" |
| | places | | 0 | "Soho" | | 1 | "Underground" | | 2 | "London" |
| | globalScore | 0.702 | | windowScore | 0.833 | |
| 51.96% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 51 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like it led nowhere" | | 1 | "looked like a maintenance entrance to the" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1081 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 64 | | matches | | 0 | "understand that Morris" |
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| 54.84% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 23 | | mean | 47 | | std | 16.07 | | cv | 0.342 | | sampleLengths | | 0 | 71 | | 1 | 62 | | 2 | 75 | | 3 | 64 | | 4 | 45 | | 5 | 48 | | 6 | 56 | | 7 | 52 | | 8 | 54 | | 9 | 24 | | 10 | 27 | | 11 | 31 | | 12 | 36 | | 13 | 36 | | 14 | 54 | | 15 | 22 | | 16 | 56 | | 17 | 67 | | 18 | 54 | | 19 | 51 | | 20 | 34 | | 21 | 48 | | 22 | 14 |
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| 86.80% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 57 | | matches | | 0 | "was plastered" | | 1 | "been rusted" | | 2 | "been wounded" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 167 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 64 | | ratio | 0.125 | | matches | | 0 | "Her worn leather watch caught the dim streetlight—11:47 PM." | | 1 | "They didn't understand that Morris hadn't simply died—something had torn him apart in ways that defied explanation, left him a broken shell of a man who spoke in whispers about things that shouldn't exist." | | 2 | "He stopped abruptly at what appeared to be a dead end—a narrow passage between two Victorian buildings that looked like it led nowhere." | | 3 | "Quinn crouched behind a collection of wheelie bins, watching as Herrera produced something from his pocket—small, pale, roughly the size and shape of a domino." | | 4 | "Quinn had heard whispers of something called the Veil Market during her investigation—fragments of conversations, coded references in text messages she'd intercepted." | | 5 | "Quinn had seen similar scars during her investigation—all of them on people connected to The Raven's Nest, all of them claiming no memory of how they'd been wounded." | | 6 | "But Morris's broken voice echoed in her memory—his rambling about shadows with teeth and doorways that led to impossible places." | | 7 | "Quinn checked her watch one final time—11:52 PM." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 949 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.03582718651211802 | | lyAdverbCount | 17 | | lyAdverbRatio | 0.01791359325605901 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 64 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 64 | | mean | 16.89 | | std | 8.24 | | cv | 0.488 | | sampleLengths | | 0 | 30 | | 1 | 9 | | 2 | 32 | | 3 | 19 | | 4 | 20 | | 5 | 23 | | 6 | 16 | | 7 | 14 | | 8 | 34 | | 9 | 8 | | 10 | 3 | | 11 | 11 | | 12 | 16 | | 13 | 26 | | 14 | 3 | | 15 | 8 | | 16 | 10 | | 17 | 18 | | 18 | 17 | | 19 | 23 | | 20 | 19 | | 21 | 6 | | 22 | 18 | | 23 | 25 | | 24 | 13 | | 25 | 25 | | 26 | 27 | | 27 | 23 | | 28 | 12 | | 29 | 19 | | 30 | 15 | | 31 | 9 | | 32 | 4 | | 33 | 17 | | 34 | 6 | | 35 | 11 | | 36 | 20 | | 37 | 12 | | 38 | 18 | | 39 | 6 | | 40 | 4 | | 41 | 18 | | 42 | 14 | | 43 | 22 | | 44 | 14 | | 45 | 18 | | 46 | 11 | | 47 | 11 | | 48 | 28 | | 49 | 28 |
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| 61.46% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.40625 | | totalSentences | 64 | | uniqueOpeners | 26 | |
| 59.52% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 56 | | matches | | 0 | "Instead, they gleamed dully in" |
| | ratio | 0.018 | |
| 98.57% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 56 | | matches | | 0 | "Her worn leather watch caught" | | 1 | "She'd been tailing him for" | | 2 | "Her superiors called it paranoia," | | 3 | "They didn't understand that Morris" | | 4 | "She wiped her eyes and" | | 5 | "He stopped abruptly at what" | | 6 | "She waited thirty seconds, then" | | 7 | "He pressed it against a" | | 8 | "he called softly, his Spanish" | | 9 | "She rose slowly from behind" | | 10 | "He smiled, but there was" | | 11 | "She stepped forward, her military" | | 12 | "He gestured toward the open" | | 13 | "Her informants either claimed ignorance" | | 14 | "she said, though her voice" | | 15 | "He began descending the stairs," | | 16 | "She drew her Glock, holding" |
| | ratio | 0.304 | |
| 40.36% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 56 | | matches | | 0 | "Detective Harlow Quinn pressed her" | | 1 | "Her worn leather watch caught" | | 2 | "She'd been tailing him for" | | 3 | "The storm had turned the" | | 4 | "Quinn's service boots splashed through" | | 5 | "Herrera moved with purpose, checking" | | 6 | "Quinn had been building a" | | 7 | "Her superiors called it paranoia," | | 8 | "They didn't understand that Morris" | | 9 | "The official report called it" | | 10 | "Quinn knew better." | | 11 | "Herrera turned left onto a" | | 12 | "Quinn counted to five before" | | 13 | "The former paramedic had always" | | 14 | "Tonight felt different." | | 15 | "Tonight he moved like someone" | | 16 | "The rain intensified, drumming against" | | 17 | "Quinn's closely cropped hair was" | | 18 | "She wiped her eyes and" | | 19 | "He stopped abruptly at what" |
| | ratio | 0.839 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 56 | | matches | | 0 | "Before disappearing inside, he turned" | | 1 | "Even through the rain and" | | 2 | "Now she stood at its" |
| | ratio | 0.054 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 7 | | matches | | 0 | "She'd been tailing him for three hours through the maze of Soho's rain-slicked streets, ever since he'd left The Raven's Nest carrying a leather satchel that ha…" | | 1 | "They didn't understand that Morris hadn't simply died—something had torn him apart in ways that defied explanation, left him a broken shell of a man who spoke i…" | | 2 | "He stopped abruptly at what appeared to be a dead end—a narrow passage between two Victorian buildings that looked like it led nowhere." | | 3 | "The former paramedic lifted one of the heavy doors as if it weighed nothing, revealing a set of stairs descending into absolute darkness." | | 4 | "She stepped forward, her military bearing keeping her spine straight despite the fear crawling up from her stomach." | | 5 | "Herrera shifted the leather satchel to his other shoulder, the movement causing his shirt to ride up slightly, revealing the pale scar that ran along his left f…" | | 6 | "But Morris's broken voice echoed in her memory—his rambling about shadows with teeth and doorways that led to impossible places." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, though her voice lacked conviction" | | 1 | "He began, his voice echoing strangely in the enclosed space" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.231 | | leniency | 0.462 | | rawRatio | 0 | | effectiveRatio | 0 | |