| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 3 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 79.12% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 958 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "lightly" | | 1 | "tightly" | | 2 | "quickly" | | 3 | "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 | 958 | | totalAiIsms | 21 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "chill" | | 1 | "symphony" | | 2 | "flickered" | | 3 | "glint" | | 4 | "traced" | | 5 | "echoed" | | 6 | "tension" | | 7 | "solitary" | | 8 | "glinting" | | 9 | "gloom" | | 10 | "quickened" | | 11 | "clandestine" | | 12 | "raced" | | 13 | "echoes" | | 14 | "pulsed" | | 15 | "could feel" | | 16 | "predator" | | 17 | "weight" | | 18 | "familiar" | | 19 | "depths" |
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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 | 61 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 61 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 61 | | 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 | 944 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 74.89% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 932 | | uniqueNames | 11 | | maxNameDensity | 1.5 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 14 | | Soho | 1 | | London | 3 | | Raven | 1 | | Nest | 3 | | Morris | 2 | | Veil | 1 | | Market | 1 | | Tube | 1 | | Camden | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Morris" | | 4 | "Camden" |
| | places | | | globalScore | 0.749 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | 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 | 944 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 61 | | matches | | |
| 70.50% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 23 | | mean | 41.04 | | std | 16.28 | | cv | 0.397 | | sampleLengths | | 0 | 66 | | 1 | 17 | | 2 | 37 | | 3 | 78 | | 4 | 29 | | 5 | 52 | | 6 | 50 | | 7 | 51 | | 8 | 54 | | 9 | 29 | | 10 | 57 | | 11 | 44 | | 12 | 41 | | 13 | 36 | | 14 | 54 | | 15 | 46 | | 16 | 47 | | 17 | 34 | | 18 | 25 | | 19 | 22 | | 20 | 45 | | 21 | 25 | | 22 | 5 |
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| 82.25% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 61 | | matches | | 0 | "was swallowed" | | 1 | "were rumored" | | 2 | "was cloaked" | | 3 | "were brokered" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 155 | | matches | | 0 | "were entering" | | 1 | "was dragging" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 15 | | semicolonCount | 1 | | flaggedSentences | 14 | | totalSentences | 61 | | ratio | 0.23 | | matches | | 0 | "Her sharp eyes, brown and bloodshot from hours without rest, locked onto the figure darting ahead—lean, quick, a blur beneath a drenched hood." | | 1 | "A low hum of the city—clinking glass, the occasional shout, the steady patter of the downpour—filled the space between them." | | 2 | "Her heart thudded, steady despite the exertion—a rhythm learned from eighteen years on the force, from battles fought in back alleys and interrogation rooms." | | 3 | "Inside, the smell hit her first—a mixture of stale beer, wood polish, and something darker, underlaid with a hint of smoke or incense." | | 4 | "Quinn’s hand went instinctively to her sidearm, though she knew better than to draw in a crowded bar; sudden violence here would only bring chaos, and her quarry might vanish before backup could arrive." | | 5 | "Quinn’s breath caught—legend told of a hidden back room in the Nest, a place whispered about among London’s underbelly, where deals, and darker things, were brokered." | | 6 | "From below came a faint murmur—voices, the clink of glass, perhaps the scrape of leather." | | 7 | "She’d stumbled onto something deeper—something connected to the whispers she’d chased ever since DS Morris died three years ago." | | 8 | "Quinn paused, fingers brushing the rail–her closest touchstone to the world above." | | 9 | "A faint glow flickered ahead—green, unnatural—and beyond it, the scent of damp earth and something metallic hung heavy." | | 10 | "Then she saw it—a token clutched tightly in the suspect’s hand." | | 11 | "The supernatural whispered in the edges of her world—echoes of a case she’d never solved, the mystery that took Morris away." | | 12 | "She could feel the eyes of the market on her—curious, hostile." | | 13 | "Rain had driven her here, and now it was anything but washing away sins—it was dragging them into the depths." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 952 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.022058823529411766 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.01050420168067227 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 61 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 61 | | mean | 15.48 | | std | 7.53 | | cv | 0.487 | | sampleLengths | | 0 | 25 | | 1 | 18 | | 2 | 23 | | 3 | 17 | | 4 | 17 | | 5 | 20 | | 6 | 23 | | 7 | 10 | | 8 | 6 | | 9 | 20 | | 10 | 19 | | 11 | 24 | | 12 | 4 | | 13 | 1 | | 14 | 22 | | 15 | 7 | | 16 | 23 | | 17 | 14 | | 18 | 19 | | 19 | 17 | | 20 | 17 | | 21 | 34 | | 22 | 14 | | 23 | 14 | | 24 | 26 | | 25 | 11 | | 26 | 3 | | 27 | 15 | | 28 | 13 | | 29 | 19 | | 30 | 6 | | 31 | 19 | | 32 | 14 | | 33 | 12 | | 34 | 18 | | 35 | 12 | | 36 | 14 | | 37 | 15 | | 38 | 11 | | 39 | 11 | | 40 | 14 | | 41 | 34 | | 42 | 20 | | 43 | 3 | | 44 | 4 | | 45 | 4 | | 46 | 21 | | 47 | 14 | | 48 | 36 | | 49 | 11 |
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| 65.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.4098360655737705 | | totalSentences | 61 | | uniqueOpeners | 25 | |
| 55.56% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 60 | | matches | | 0 | "Then she saw it—a token" |
| | ratio | 0.017 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 9 | | totalSentences | 60 | | matches | | 0 | "Her sharp eyes, brown and" | | 1 | "she barked, but the sound" | | 2 | "She broadened her stride, the" | | 3 | "Her heart thudded, steady despite" | | 4 | "Her boot heels echoed as" | | 5 | "She’d stumbled onto something deeper—something" | | 6 | "It was unfamiliar, dangerous." | | 7 | "She could feel the eyes" | | 8 | "she said, voice hard" |
| | ratio | 0.15 | |
| 51.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 60 | | matches | | 0 | "The rain hammered down as" | | 1 | "Detective Harlow Quinn’s breath came" | | 2 | "Her sharp eyes, brown and" | | 3 | "she barked, but the sound" | | 4 | "Quinn’s boots slapped against uneven" | | 5 | "A low hum of the" | | 6 | "The suspect’s steps faltered near" | | 7 | "Quinn’s instincts sharpened like a" | | 8 | "The walls inside were rumored" | | 9 | "She broadened her stride, the" | | 10 | "Her heart thudded, steady despite" | | 11 | "The suspect veered left, her" | | 12 | "Quinn paused only a heartbeat" | | 13 | "The bar’s interior was cloaked" | | 14 | "Walls hung thick with old" | | 15 | "The chatter died as Quinn" | | 16 | "The suspect slipped through the" | | 17 | "Quinn’s hand went instinctively to" | | 18 | "Another few steps and the" | | 19 | "Quinn’s breath caught—legend told of" |
| | ratio | 0.817 | |
| 83.33% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 60 | | matches | | 0 | "To descend was to tread" |
| | ratio | 0.017 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 2 | | matches | | 0 | "The rain hammered down as if the sky itself were furious, turning the slick pavement into a slick mirror reflecting spilled streetlamps and neon signs." | | 1 | "The suspect veered left, her boots skittering lightly under the downpour, and disappeared inside the Nest, pushing open the bar’s heavy door." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "she barked (bark)" | | 1 | "the voice hissed (hiss)" |
| | dialogueSentences | 3 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0.667 | | effectiveRatio | 0.667 | |