| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 9 | | tagDensity | 0.556 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1217 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 38.37% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1217 | | totalAiIsms | 15 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | word | "the last thing" | | count | 1 |
| | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | |
| | highlights | | 0 | "gloom" | | 1 | "measured" | | 2 | "flickered" | | 3 | "flicker" | | 4 | "the last thing" | | 5 | "dancing" | | 6 | "echoed" | | 7 | "footsteps" | | 8 | "mechanical" | | 9 | "intricate" | | 10 | "vibrated" | | 11 | "potential" | | 12 | "tension" | | 13 | "resolved" | | 14 | "cacophony" |
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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 | 111 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 111 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 114 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 17 | | totalWords | 1211 | | ratio | 0.014 | | matches | | 0 | "Click." | | 1 | "‘The door under the city. The bone key. They trade in things that shouldn’t be.’" | | 2 | "snick" |
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| 62.50% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 1 | | matches | | 0 | "The boy—no older than twenty, she guessed—was trapped." |
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| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 1133 | | uniqueNames | 12 | | maxNameDensity | 1.15 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Harlow" | | discoveredNames | | Soho | 1 | | Quinn | 2 | | Harlow | 13 | | Met | 1 | | Herrera | 1 | | Tomás | 2 | | Close | 1 | | Tube | 1 | | Morris | 2 | | Londoners | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Harlow" | | 2 | "Herrera" | | 3 | "Tomás" | | 4 | "Morris" | | 5 | "Market" |
| | places | | | globalScore | 0.926 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.826 | | wordCount | 1211 | | matches | | 0 | "Not back the way he came, but towards a rusted iron gate set into the far wall of the cour" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 114 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 36.7 | | std | 22.59 | | cv | 0.616 | | sampleLengths | | 0 | 73 | | 1 | 65 | | 2 | 8 | | 3 | 56 | | 4 | 20 | | 5 | 10 | | 6 | 55 | | 7 | 8 | | 8 | 40 | | 9 | 41 | | 10 | 2 | | 11 | 54 | | 12 | 12 | | 13 | 64 | | 14 | 29 | | 15 | 21 | | 16 | 49 | | 17 | 1 | | 18 | 32 | | 19 | 20 | | 20 | 65 | | 21 | 74 | | 22 | 25 | | 23 | 21 | | 24 | 55 | | 25 | 9 | | 26 | 53 | | 27 | 47 | | 28 | 69 | | 29 | 58 | | 30 | 28 | | 31 | 8 | | 32 | 39 |
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| 86.30% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 111 | | matches | | 0 | "been drilled" | | 1 | "were lined" | | 2 | "were cracked" | | 3 | "was swallowed" | | 4 | "been used" | | 5 | "were crammed" | | 6 | "was gone" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 182 | | matches | | 0 | "was running" | | 1 | "was looking" | | 2 | "was falling" | | 3 | "was scrambling" | | 4 | "was selling" |
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| 67.67% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 2 | | flaggedSentences | 3 | | totalSentences | 114 | | ratio | 0.026 | | matches | | 0 | "He wasn't just running from the law; he was running from something else." | | 1 | "The boy—no older than twenty, she guessed—was trapped." | | 2 | "He wasn’t running anymore; he was falling down the tunnel in his haste." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 707 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.02545968882602546 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005657708628005658 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 10.62 | | std | 7.6 | | cv | 0.716 | | sampleLengths | | 0 | 22 | | 1 | 16 | | 2 | 6 | | 3 | 3 | | 4 | 13 | | 5 | 13 | | 6 | 13 | | 7 | 13 | | 8 | 18 | | 9 | 8 | | 10 | 13 | | 11 | 8 | | 12 | 3 | | 13 | 26 | | 14 | 14 | | 15 | 4 | | 16 | 9 | | 17 | 17 | | 18 | 3 | | 19 | 10 | | 20 | 6 | | 21 | 8 | | 22 | 13 | | 23 | 8 | | 24 | 2 | | 25 | 10 | | 26 | 5 | | 27 | 3 | | 28 | 8 | | 29 | 9 | | 30 | 14 | | 31 | 11 | | 32 | 6 | | 33 | 12 | | 34 | 8 | | 35 | 6 | | 36 | 7 | | 37 | 8 | | 38 | 2 | | 39 | 20 | | 40 | 6 | | 41 | 4 | | 42 | 18 | | 43 | 6 | | 44 | 12 | | 45 | 12 | | 46 | 23 | | 47 | 22 | | 48 | 7 | | 49 | 7 |
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| 38.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.32456140350877194 | | totalSentences | 114 | | uniqueOpeners | 37 | |
| 31.15% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 107 | | matches | | | ratio | 0.009 | |
| 96.64% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 107 | | matches | | 0 | "He was young, panicked, and" | | 1 | "He’d already glanced back three" | | 2 | "He wasn't just running from" | | 3 | "He darted left, down an" | | 4 | "He spun around, chest heaving," | | 5 | "His voice was a reedy" | | 6 | "She just walked towards him," | | 7 | "He saw a cop." | | 8 | "He didn't see the ghosts" | | 9 | "he stammered, backing up until" | | 10 | "His voice, usually warm and" | | 11 | "He was high on something," | | 12 | "He hesitated, his gaze darting" | | 13 | "He was looking for an" | | 14 | "He hit it with his" | | 15 | "He vanished into the darkness" | | 16 | "Her boots echoed on the" | | 17 | "He wasn’t running anymore; he" | | 18 | "He fumbled in his pocket," | | 19 | "He slapped it against a" |
| | ratio | 0.308 | |
| 34.77% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 91 | | totalSentences | 107 | | matches | | 0 | "The suspect’s cheap trainers slapped" | | 1 | "Harlow Quinn kept a steady" | | 2 | "He was young, panicked, and" | | 3 | "A bad combination." | | 4 | "He’d already glanced back three" | | 5 | "He wasn't just running from" | | 6 | "He darted left, down an" | | 7 | "Harlow followed, her hand instinctively" | | 8 | "The alley opened into a" | | 9 | "The boy—no older than twenty," | | 10 | "He spun around, chest heaving," | | 11 | "His voice was a reedy" | | 12 | "Harlow didn’t speak." | | 13 | "She just walked towards him," | | 14 | "The boy’s eyes flickered to" | | 15 | "He saw a cop." | | 16 | "He didn't see the ghosts" | | 17 | "he stammered, backing up until" | | 18 | "Harlow’s voice was flat, devoid" | | 19 | "The boy flinched at the" |
| | ratio | 0.85 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 107 | | matches | (empty) | | ratio | 0 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 3 | | matches | | 0 | "She just walked towards him, her pace measured, her bearing radiating the military precision that had been drilled into her long before she’d joined the Met." | | 1 | "The air that hit her was thick and heavy, a cloying cocktail of exotic spices, burning incense, and the musky scent of wet fur and unwashed bodies." | | 2 | "She saw the boy, a flash of a cheap nylon jacket, disappearing into the throng near a stall that sold knives with blades made of pure, frozen starlight." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 1 | | matches | | 0 | "Harlow broke, the cold air burning her lungs" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "he stammered (stammer)" | | 1 | "the boy pleaded (plead)" |
| | dialogueSentences | 9 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 1 | | effectiveRatio | 0.444 | |