| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 30 | | tagDensity | 0.367 | | leniency | 0.733 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.10% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1725 | | 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) | |
| 65.22% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1725 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "streaming" | | 1 | "echoed" | | 2 | "footsteps" | | 3 | "standard" | | 4 | "resolved" | | 5 | "depths" | | 6 | "absolutely" | | 7 | "flicked" | | 8 | "perfect" |
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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 | 122 | | matches | (empty) | |
| 96.02% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 122 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 141 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1711 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 91.13% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 1359 | | uniqueNames | 19 | | maxNameDensity | 1.18 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 16 | | Greek | 1 | | Street | 2 | | November | 1 | | Morris | 5 | | Deptford | 2 | | Bateman | 1 | | Raven | 1 | | Nest | 1 | | Tube | 1 | | West | 1 | | End | 1 | | London | 1 | | Veil | 1 | | Market | 1 | | Glock | 1 | | English | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "English" |
| | places | | 0 | "Soho" | | 1 | "Greek" | | 2 | "Street" | | 3 | "November" | | 4 | "Deptford" | | 5 | "Bateman" | | 6 | "Raven" | | 7 | "West" | | 8 | "End" | | 9 | "London" |
| | globalScore | 0.911 | | windowScore | 1 | |
| 63.79% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like conspiracy theory masqueradin" | | 1 | "fabrics that seemed to absorb and emit light simultaneously" | | 2 | "seless anyway, apparently—and stepped off 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 | 1711 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 141 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 55 | | mean | 31.11 | | std | 20.98 | | cv | 0.675 | | sampleLengths | | 0 | 43 | | 1 | 44 | | 2 | 66 | | 3 | 56 | | 4 | 56 | | 5 | 28 | | 6 | 2 | | 7 | 18 | | 8 | 24 | | 9 | 5 | | 10 | 2 | | 11 | 41 | | 12 | 16 | | 13 | 28 | | 14 | 16 | | 15 | 43 | | 16 | 9 | | 17 | 62 | | 18 | 77 | | 19 | 37 | | 20 | 7 | | 21 | 63 | | 22 | 45 | | 23 | 29 | | 24 | 47 | | 25 | 33 | | 26 | 4 | | 27 | 36 | | 28 | 4 | | 29 | 38 | | 30 | 32 | | 31 | 5 | | 32 | 39 | | 33 | 55 | | 34 | 11 | | 35 | 12 | | 36 | 11 | | 37 | 32 | | 38 | 53 | | 39 | 13 | | 40 | 71 | | 41 | 31 | | 42 | 39 | | 43 | 6 | | 44 | 15 | | 45 | 26 | | 46 | 72 | | 47 | 10 | | 48 | 7 | | 49 | 33 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 122 | | matches | | |
| 86.04% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 234 | | matches | | 0 | "was chasing" | | 1 | "was coming" | | 2 | "was getting" | | 3 | "were ticking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 141 | | ratio | 0.064 | | matches | | 0 | "The man—if he was a man—had been at The Raven's Nest fifteen minutes ago, slipping out the back the moment she'd walked through the front door." | | 1 | "No footsteps either—he'd stopped somewhere in that darkness." | | 2 | "Not footsteps—something else." | | 3 | "The hum resolved into voices—dozens of them, maybe hundreds, the sound of a crowd engaged in commerce and argument and laughter." | | 4 | "Crowds moved between the vendors—and Quinn's trained eye, her eighteen years of reading people on London's streets, told her immediately that not all of them were people." | | 5 | "\"First time at market, detective?\" His voice carried an accent she couldn't place—something old, something that made the words feel like they were being translated from a language that predated English." | | 6 | "Faces turned toward her—curious, hostile, hungry." | | 7 | "Quinn holstered her weapon—useless anyway, apparently—and stepped off the platform into the crowd." | | 8 | "The singing fountain announced itself before she saw it—a basin of mercury that hummed in harmonies that made her teeth ache." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1372 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.02478134110787172 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.009475218658892129 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 141 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 141 | | mean | 12.13 | | std | 8.77 | | cv | 0.723 | | sampleLengths | | 0 | 16 | | 1 | 27 | | 2 | 18 | | 3 | 9 | | 4 | 2 | | 5 | 4 | | 6 | 11 | | 7 | 2 | | 8 | 33 | | 9 | 7 | | 10 | 3 | | 11 | 21 | | 12 | 7 | | 13 | 17 | | 14 | 26 | | 15 | 6 | | 16 | 7 | | 17 | 3 | | 18 | 2 | | 19 | 12 | | 20 | 19 | | 21 | 13 | | 22 | 15 | | 23 | 13 | | 24 | 2 | | 25 | 8 | | 26 | 2 | | 27 | 8 | | 28 | 12 | | 29 | 6 | | 30 | 3 | | 31 | 3 | | 32 | 5 | | 33 | 2 | | 34 | 10 | | 35 | 13 | | 36 | 18 | | 37 | 4 | | 38 | 3 | | 39 | 9 | | 40 | 6 | | 41 | 18 | | 42 | 4 | | 43 | 4 | | 44 | 11 | | 45 | 1 | | 46 | 22 | | 47 | 21 | | 48 | 9 | | 49 | 5 |
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| 58.39% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3971631205673759 | | totalSentences | 141 | | uniqueOpeners | 56 | |
| 30.58% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 109 | | matches | | | ratio | 0.009 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 109 | | matches | | 0 | "She'd seen the symbols painted" | | 1 | "She'd been watching that bar" | | 2 | "Her voice echoed off the" | | 3 | "She drew her service weapon," | | 4 | "She advanced to the escalator's" | | 5 | "Her phone's torch cut a" | | 6 | "She emerged onto the platform" | | 7 | "She'd heard the name whispered" | | 8 | "Her suspect had vanished into" | | 9 | "She was alone, armed with" | | 10 | "His eyes were the yellow" | | 11 | "His voice carried an accent" | | 12 | "She'd taken it from his" | | 13 | "He laughed, a sound like" | | 14 | "She counted six, eight, a" | | 15 | "He held out a palm" | | 16 | "It was the last physical" | | 17 | "Her suspect was getting further" | | 18 | "She unclasped the watch, her" | | 19 | "She placed it in that" |
| | ratio | 0.229 | |
| 88.44% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 81 | | totalSentences | 109 | | matches | | 0 | "The rain hammered down on" | | 1 | "Detective Harlow Quinn's boots slapped" | | 2 | "Quinn's fingers twitched toward her" | | 3 | "The official report called it" | | 4 | "Quinn knew better." | | 5 | "She'd seen the symbols painted" | | 6 | "The suspect ducked left into" | | 7 | "Quinn pushed harder, her lungs" | | 8 | "The man—if he was a" | | 9 | "She'd been watching that bar" | | 10 | "The suspect vaulted a railing" | | 11 | "Quinn skidded to a stop" | | 12 | "Her voice echoed off the" | | 13 | "She drew her service weapon," | | 14 | "The emergency lighting cast everything" | | 15 | "The ticket barriers stood open," | | 16 | "A sound reached her." | | 17 | "A low hum, almost musical," | | 18 | "She advanced to the escalator's" | | 19 | "Her phone's torch cut a" |
| | ratio | 0.743 | |
| 91.74% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 109 | | matches | | 0 | "To whatever happened in the" | | 1 | "As if in response, the" |
| | ratio | 0.018 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 56 | | technicalSentenceCount | 8 | | matches | | 0 | "Quinn pushed harder, her lungs burning, her worn leather watch slapping against her wrist with each stride." | | 1 | "Building a case that looked like conspiracy theory masquerading as police work." | | 2 | "Where there should have been empty tracks and dead signal lights, there stretched a sprawling marketplace that defied the architecture she'd memorized from deca…" | | 3 | "She was alone, armed with nothing but a standard-issue Glock and a warrant card that meant absolutely nothing here." | | 4 | "But somewhere in that impossible bazaar walked a man who knew something about the symbols in the Deptford warehouse." | | 5 | "His eyes were the yellow of old newspaper, his smile full of teeth that were definitely not human." | | 6 | "She'd taken it from his belongings after the funeral, when his widow hadn't wanted anything that reminded her of the job." | | 7 | "The singing fountain announced itself before she saw it—a basin of mercury that hummed in harmonies that made her teeth ache." |
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| 34.09% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 2 | | matches | | 0 | "He laughed, a sound like dry leaves scraping stone" | | 1 | "Quinn leaned, her hands flat on the edge of the bone table" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 30 | | tagDensity | 0.1 | | leniency | 0.2 | | rawRatio | 0.333 | | effectiveRatio | 0.067 | |