| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.36% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1773 | | totalAiIsmAdverbs | 2 | | 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) | |
| 6.94% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1773 | | totalAiIsms | 33 | | found | | 0 | | | 1 | | | 2 | | word | "practiced ease" | | count | 1 |
| | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | | | 23 | | | 24 | | | 25 | |
| | highlights | | 0 | "rhythmic" | | 1 | "determined" | | 2 | "practiced ease" | | 3 | "measured" | | 4 | "scanning" | | 5 | "familiar" | | 6 | "chill" | | 7 | "fleeting" | | 8 | "vibrated" | | 9 | "stomach" | | 10 | "footsteps" | | 11 | "echoing" | | 12 | "etched" | | 13 | "electric" | | 14 | "dancing" | | 15 | "stark" | | 16 | "shimmered" | | 17 | "pulse" | | 18 | "echoed" | | 19 | "quickened" | | 20 | "pounding" | | 21 | "silence" | | 22 | "synchronized" | | 23 | "potential" | | 24 | "encounter" | | 25 | "predator" |
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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 | 0 | | narrationSentences | 98 | | matches | (empty) | |
| 55.39% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 5 | | narrationSentences | 98 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 106 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 55 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1760 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 1662 | | uniqueNames | 12 | | maxNameDensity | 1.32 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Harlow" | | discoveredNames | | London | 3 | | Detective | 2 | | Harlow | 22 | | Quinn | 2 | | Camden | 1 | | Morris | 8 | | Tube | 1 | | Metropolitan | 1 | | Police | 1 | | Veil | 3 | | Market | 3 | | One | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Camden" | | 3 | "Morris" | | 4 | "Market" | | 5 | "One" |
| | places | | | globalScore | 0.838 | | windowScore | 0.667 | |
| 96.24% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 93 | | glossingSentenceCount | 2 | | matches | | 0 | "chill that seemed to emanate from the very stones beneath her feet" | | 1 | "artifacts that seemed to pulse with their own energy" |
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| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 4 | | per1kWords | 2.273 | | wordCount | 1760 | | matches | | 0 | "not just from the rain but from an unnatural chill" | | 1 | "not fear in those eyes but something else" | | 2 | "not an opening to another street, but a staircase descending into darkness" | | 3 | "not her service pistol, but something more specialized" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 106 | | matches | (empty) | |
| 65.99% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 46.32 | | std | 17.64 | | cv | 0.381 | | sampleLengths | | 0 | 76 | | 1 | 64 | | 2 | 69 | | 3 | 67 | | 4 | 44 | | 5 | 52 | | 6 | 66 | | 7 | 58 | | 8 | 40 | | 9 | 66 | | 10 | 73 | | 11 | 65 | | 12 | 54 | | 13 | 35 | | 14 | 61 | | 15 | 59 | | 16 | 55 | | 17 | 62 | | 18 | 43 | | 19 | 55 | | 20 | 48 | | 21 | 44 | | 22 | 35 | | 23 | 49 | | 24 | 28 | | 25 | 21 | | 26 | 14 | | 27 | 46 | | 28 | 19 | | 29 | 33 | | 30 | 47 | | 31 | 20 | | 32 | 44 | | 33 | 18 | | 34 | 18 | | 35 | 11 | | 36 | 50 | | 37 | 51 |
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| 87.36% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 98 | | matches | | 0 | "been dismissed" | | 1 | "been found" | | 2 | "were lined" | | 3 | "were supposed" | | 4 | "was transferred" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 256 | | matches | | 0 | "was vanishing" | | 1 | "was approaching" | | 2 | "was saying" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 106 | | ratio | 0.094 | | matches | | 0 | "Harlow's military precision served her well in these moments—measured steps, controlled breathing, eyes scanning for any sign of hesitation or deviation from the expected escape route." | | 1 | "The alley smelled of damp brick and something else—something metallic and ancient that prickled at the edges of her memory." | | 2 | "The familiar London streets had given way to a section of the city she rarely patrolled—Camden's underbelly, where the modern facades crumbled to reveal older, more forgotten layers of existence." | | 3 | "Harlow saw not fear in those eyes but something else—challenge." | | 4 | "She knew this feeling—the same one that had gripped her three years ago when she'd lost DS Morris in a case that defied all logical explanation." | | 5 | "Harlow's hand hovered near the weapon at her hip—not her service pistol, but something more specialized that she rarely carried but always kept close." | | 6 | "The man who had information about the clique she suspected of involvement in criminal activity—supernormal criminal activity—was vanishing into what could be a trap." | | 7 | "This wasn't just an illegal market—it was a community, one operating entirely beneath the notice of the Metropolitan Police." | | 8 | "The two exchanged words, then a small object—bone-shaped and pale—was transferred from the suspect's hand to the cloaked figure's." | | 9 | "She assessed the situation quickly—three armed opponents, the element of surprise lost, and herself deep in enemy territory with little hope of immediate backup." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1681 | | adjectiveStacks | 1 | | stackExamples | | 0 | "familiar, rain-soaked streets" |
| | adverbCount | 42 | | adverbRatio | 0.024985127900059488 | | lyAdverbCount | 19 | | lyAdverbRatio | 0.011302795954788817 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 106 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 106 | | mean | 16.6 | | std | 8.41 | | cv | 0.506 | | sampleLengths | | 0 | 26 | | 1 | 28 | | 2 | 22 | | 3 | 22 | | 4 | 26 | | 5 | 16 | | 6 | 17 | | 7 | 32 | | 8 | 20 | | 9 | 11 | | 10 | 30 | | 11 | 26 | | 12 | 18 | | 13 | 15 | | 14 | 10 | | 15 | 1 | | 16 | 13 | | 17 | 39 | | 18 | 11 | | 19 | 26 | | 20 | 29 | | 21 | 12 | | 22 | 24 | | 23 | 22 | | 24 | 11 | | 25 | 13 | | 26 | 16 | | 27 | 18 | | 28 | 24 | | 29 | 24 | | 30 | 23 | | 31 | 15 | | 32 | 18 | | 33 | 17 | | 34 | 17 | | 35 | 9 | | 36 | 6 | | 37 | 20 | | 38 | 13 | | 39 | 21 | | 40 | 14 | | 41 | 19 | | 42 | 16 | | 43 | 19 | | 44 | 13 | | 45 | 15 | | 46 | 19 | | 47 | 14 | | 48 | 18 | | 49 | 9 |
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| 48.43% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.330188679245283 | | totalSentences | 106 | | uniqueOpeners | 35 | |
| 34.72% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 96 | | matches | | 0 | "Then the man reached into" |
| | ratio | 0.01 | |
| 99.17% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 96 | | matches | | 0 | "Her leather jacket absorbed the" | | 1 | "She'd been on this suspect's" | | 2 | "Her brown eyes, sharp and" | | 3 | "she muttered under her breath," | | 4 | "She followed without hesitation, her" | | 5 | "He glanced back, and for" | | 6 | "He pressed it against the" | | 7 | "She knew this feeling—the same" | | 8 | "Her fingers brushed against cold" | | 9 | "Her training screamed at her" | | 10 | "She descended the first step," | | 11 | "They carried satchels and cases," | | 12 | "Her suspect was approaching a" | | 13 | "She could still retreat, still" | | 14 | "She remembered Morris's last words," | | 15 | "She heard his footsteps moving" | | 16 | "Her military precision warred with" | | 17 | "She thought of the cold" | | 18 | "She moved with purpose, her" | | 19 | "Her suspect approached a set" |
| | ratio | 0.302 | |
| 32.92% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 96 | | matches | | 0 | "The rain fell in London" | | 1 | "Her leather jacket absorbed the" | | 2 | "The city lights blurred through" | | 3 | "She'd been on this suspect's" | | 4 | "Harlow's military precision served her" | | 5 | "Her brown eyes, sharp and" | | 6 | "she muttered under her breath," | | 7 | "She followed without hesitation, her" | | 8 | "The alley smelled of damp" | | 9 | "The familiar London streets had" | | 10 | "The air grew colder here," | | 11 | "The suspect stood before a" | | 12 | "He glanced back, and for" | | 13 | "Harlow saw not fear in" | | 14 | "He pressed it against the" | | 15 | "A cold dread settled in" | | 16 | "She knew this feeling—the same" | | 17 | "The supernatural elements Morris had" | | 18 | "The suspect began to descend," | | 19 | "Harlow's hand hovered near the" |
| | ratio | 0.854 | |
| 52.08% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 96 | | matches | | 0 | "Either way, she would bring" |
| | ratio | 0.01 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 79 | | technicalSentenceCount | 20 | | matches | | 0 | "The rain fell in London like a persistent drum solo, each droplet hitting the pavement with a rhythmic precision that matched Detective Harlow Quinn's determine…" | | 1 | "Her leather jacket absorbed the worst of the downpour, the water beading on the surface before trickling down to her dark trousers, which clung stubbornly to he…" | | 2 | "The city lights blurred through the wetness, creating a watercolor landscape of neon signs and streetlamps that reflected in the growing puddles." | | 3 | "The air grew colder here, not just from the rain but from an unnatural chill that seemed to emanate from the very stones beneath her feet." | | 4 | "He pressed it against the wall, and with a grinding sound that vibrated through the soles of Harlow's boots, a section of the brickwork receded inward, revealin…" | | 5 | "She knew this feeling—the same one that had gripped her three years ago when she'd lost DS Morris in a case that defied all logical explanation." | | 6 | "The supernatural elements Morris had insisted were involved had been dismissed by her superiors, but Harlow had seen things that night that couldn't be explaine…" | | 7 | "Her fingers brushed against cold metal etched with symbols she'd studied for years, symbols that had been found at Morris's crime scene." | | 8 | "The man who had information about the clique she suspected of involvement in criminal activity—supernormal criminal activity—was vanishing into what could be a …" | | 9 | "Vendors had set up stalls along the platforms, their wares displayed under flickering gas lamps that cast long dancing shadows." | | 10 | "A market that moved locations with each full moon, accessible only with bone tokens." | | 11 | "Her military precision warred with the recklessness that had driven her for three years since Morris's disappearance." | | 12 | "She thought of the cold case files on her desk, of the dismissive attitudes of her superiors, of the supernatural clues that couldn't be explained away." | | 13 | "Stalls displayed potions that shimmered with unnatural light, books bound in unfamiliar hides, and artifacts that seemed to pulse with their own energy." | | 14 | "Vendors whispered of abilities that defied physics, of creatures that walked among humans unnoticed." | | 15 | "He exchanged a few more words with the gray-cloaked figure, then slipped through the doors, which closed behind him with a soft click that echoed through the ch…" | | 16 | "One of the newcomers stepped forward, revealing a face that was unnaturally pale." | | 17 | "The pale one smiled, revealing teeth that were too sharp, too white." | | 18 | "She thought of Morris, of the unexplained supernatural elements of his case, of the clues that had led her here." | | 19 | "Either way, she would bring light to the darkness that had claimed her partner and threatened her city." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 3 | | matches | | 0 | "the suspect was saying, his voice low but clear" | | 1 | "she announced, her voice steady despite the adrenaline coursing through her veins" | | 2 | "she said, her voice leaving no room for doubt" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 3 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "the suspect was saying (be say)" | | 2 | "she announced (announce)" |
| | dialogueSentences | 14 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0.75 | | effectiveRatio | 0.429 | |