| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "She05 She stopped close [close]" |
| | dialogueSentences | 25 | | tagDensity | 0.44 | | leniency | 0.88 | | rawRatio | 0.091 | | effectiveRatio | 0.08 | |
| 94.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1920 | | 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) | |
| 63.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1920 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "clandestine" | | 1 | "weight" | | 2 | "flicker" | | 3 | "electric" | | 4 | "echo" | | 5 | "footsteps" | | 6 | "quickened" | | 7 | "shimmered" | | 8 | "scanning" | | 9 | "glint" | | 10 | "flickered" | | 11 | "silence" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "weight of words/silence" | | count | 1 |
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| | highlights | | 0 | "the weight of the moment" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 145 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 145 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 159 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1904 | | ratio | 0 | | matches | (empty) | |
| 83.33% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 1 | | matches | | 0 | "When she closed to three meters, he spoke." |
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| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 56 | | wordCount | 1687 | | uniqueNames | 18 | | maxNameDensity | 1.01 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 2 | | Detective | 1 | | Harlow | 1 | | Quinn | 17 | | Raven | 1 | | Nest | 1 | | Herrera | 13 | | Greek | 1 | | Street | 1 | | Morris | 5 | | Victorian | 1 | | Tube | 1 | | Saint | 1 | | Christopher | 1 | | Veil | 2 | | Market | 1 | | Seville | 1 | | Warden | 5 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Herrera" | | 4 | "Morris" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Warden" |
| | places | | 0 | "Soho" | | 1 | "Greek" | | 2 | "Street" | | 3 | "Veil" | | 4 | "Market" | | 5 | "Seville" |
| | globalScore | 0.996 | | windowScore | 0.833 | |
| 81.19% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 109 | | glossingSentenceCount | 3 | | matches | | 0 | "quite find her" | | 1 | "looked like blackened00 blackened wax" | | 2 | "looked like when you05 you peeled off the" |
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| 42.44% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 1.576 | | wordCount | 1904 | | matches | | 0 | "not just his footfalls but the ragged edge to his breathing" | | 1 | "not just about the unlicensed stitching, but about the symbols, about the05 the deaths" | | 2 | "neither token nor" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 159 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 41.39 | | std | 29.01 | | cv | 0.701 | | sampleLengths | | 0 | 68 | | 1 | 5 | | 2 | 76 | | 3 | 19 | | 4 | 5 | | 5 | 17 | | 6 | 8 | | 7 | 106 | | 8 | 45 | | 9 | 76 | | 10 | 51 | | 11 | 54 | | 12 | 8 | | 13 | 11 | | 14 | 74 | | 15 | 96 | | 16 | 14 | | 17 | 122 | | 18 | 55 | | 19 | 83 | | 20 | 43 | | 21 | 56 | | 22 | 61 | | 23 | 12 | | 24 | 72 | | 25 | 24 | | 26 | 14 | | 27 | 21 | | 28 | 28 | | 29 | 14 | | 30 | 32 | | 31 | 73 | | 32 | 35 | | 33 | 66 | | 34 | 33 | | 35 | 26 | | 36 | 22 | | 37 | 61 | | 38 | 36 | | 39 | 15 | | 40 | 12 | | 41 | 31 | | 42 | 34 | | 43 | 59 | | 44 | 10 | | 45 | 21 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 145 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 288 | | matches | | 0 | "was heading" | | 1 | "wasn’t just fleeing" | | 2 | "wasn’t coming" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 16 | | semicolonCount | 1 | | flaggedSentences | 12 | | totalSentences | 159 | | ratio | 0.075 | | matches | | 0 | "Quinn began to understand he wasn’t just fleeing—he was heading somewhere." | | 1 | "Herrera scrabbled at something in the cobblestones—a cast-iron hatch she had missed entirely." | | 2 | "She counted them by feel—twenty-three—before her boots met solid ground." | | 3 | "She04 She quickened her stride, the beam of her torch catching the scarred walls, the graffiti that shifted from ordinary tags to symbols she didn’t recognize—interlocking triangles, crude eyes,05 eyes, the outline of a crescent moon." | | 4 | "The cavern—no, it was an old Tube station platform, she realized, the curved ceilings and abandoned tracks unmistakable—teemed with people and light." | | 5 | "The traders did not cry their wares; they murmured, they crooned, their voices weaving through the steam that rose from06 from bubbling cauldrons and hissing braziers." | | 6 | "She could retrace her steps, call in a raid, risk the market dissolving before a team could mobilize—or she could04 could go forward and grab him herself, alone." | | 7 | "The air changed as she stepped over the threshold where the tunnel ended and the05 the platform began—it thickened,05 thickened, pressing against her skin like a static charge." | | 8 | "This suspect05 suspect had information—not just about the unlicensed stitching, but about the symbols, about the05 the deaths that ended with0400 on an official’s desk with a stamp of “unsolved.” Morris had whispered a name—the Veil—in his final moments." | | 9 | "Herrera’s expression flickered—surprise, then grief." | | 10 | "From deeper in the market, a bell tolled—deep and07 and resonant." | | 11 | "Its eyes were not05 not0 not entirely human—there was a luminosity, a yellow cast." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1712 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 47 | | adverbRatio | 0.027453271028037383 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.008177570093457943 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 159 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 159 | | mean | 11.97 | | std | 8.35 | | cv | 0.697 | | sampleLengths | | 0 | 8 | | 1 | 27 | | 2 | 5 | | 3 | 28 | | 4 | 5 | | 5 | 16 | | 6 | 11 | | 7 | 2 | | 8 | 13 | | 9 | 27 | | 10 | 7 | | 11 | 17 | | 12 | 2 | | 13 | 3 | | 14 | 2 | | 15 | 13 | | 16 | 4 | | 17 | 5 | | 18 | 3 | | 19 | 6 | | 20 | 7 | | 21 | 16 | | 22 | 11 | | 23 | 22 | | 24 | 8 | | 25 | 13 | | 26 | 4 | | 27 | 11 | | 28 | 8 | | 29 | 16 | | 30 | 9 | | 31 | 16 | | 32 | 2 | | 33 | 2 | | 34 | 19 | | 35 | 7 | | 36 | 14 | | 37 | 4 | | 38 | 21 | | 39 | 11 | | 40 | 11 | | 41 | 3 | | 42 | 6 | | 43 | 13 | | 44 | 4 | | 45 | 7 | | 46 | 7 | | 47 | 7 | | 48 | 19 | | 49 | 16 |
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| 56.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.3522012578616352 | | totalSentences | 159 | | uniqueOpeners | 56 | |
| 72.46% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 138 | | matches | | 0 | "Just the pace of a" | | 1 | "Then he ran." | | 2 | "Instead, she poured her speed" |
| | ratio | 0.022 | |
| 77.97% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 49 | | totalSentences | 138 | | matches | | 0 | "It slanted through the sodium" | | 1 | "She did not adjust it." | | 2 | "She counted seconds by the" | | 3 | "He pushed his hands into" | | 4 | "She had seen him three" | | 5 | "She stepped from the mouth" | | 6 | "He didn’t stop." | | 7 | "She held up her badge," | | 8 | "His shoulders hitched a fraction." | | 9 | "She gained on him, close" | | 10 | "He knocked a bin over" | | 11 | "She hurdled it, landing10 landing" | | 12 | "She had been18 been a" | | 13 | "He broke from the alley" | | 14 | "Her fingers snatched the back" | | 15 | "She flung it aside and" | | 16 | "He knew these streets." | | 17 | "They burst into a narrow" | | 18 | "He heaved it open." | | 19 | "He swung his legs in" |
| | ratio | 0.355 | |
| 28.84% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 119 | | totalSentences | 138 | | matches | | 0 | "The rain had not let" | | 1 | "It slanted through the sodium" | | 2 | "She did not adjust it." | | 3 | "She counted seconds by the" | | 4 | "Tomás Herrera came out alone." | | 5 | "Quinn recognized the roll of" | | 6 | "He pushed his hands into" | | 7 | "She had seen him three" | | 8 | "Tonight she’d decided to close" | | 9 | "She stepped from the mouth" | | 10 | "He didn’t stop." | | 11 | "She held up her badge," | | 12 | "His shoulders hitched a fraction." | | 13 | "Quinn gave chase without a" | | 14 | "A shout cost breath and" | | 15 | "Herrera darted left into a" | | 16 | "She gained on him, close" | | 17 | "He knocked a bin over" | | 18 | "She hurdled it, landing10 landing" | | 19 | "The cold barely registered." |
| | ratio | 0.862 | |
| 36.23% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 138 | | matches | | 0 | "To follow meant stepping outside" |
| | ratio | 0.007 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 66 | | technicalSentenceCount | 6 | | matches | | 0 | "She hurdled it, landing10 landing in a puddle that soaked her trouser leg." | | 1 | "She04 She quickened her stride, the beam of her torch catching the scarred walls, the graffiti that shifted from ordinary tags to symbols she didn’t recognize—i…" | | 2 | "She passed a threshold marked by00 marked by two heavy iron sconces, unlit, their cups filled with something that looked like blackened00 blackened wax." | | 3 | "The traders did not cry their wares; they murmured, they crooned, their voices weaving through the steam that rose from06 from bubbling cauldrons and hissing br…" | | 4 | "She glimpsed05 glimpsed jars of floating things, bundles of feathers that shimmered with their own04 own light,05 light,05 light, vials of liquid that boiled wi…" | | 5 | "He stood at a stall hung with dried herbs and jars of something that might have been preserved organs, his chest heaving." |
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| 34.09% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 2 | | matches | | 0 | "She held up, though the rain blurred the lettering" | | 1 | "She kept, though her heart hammered" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | 0 | "someone murmured (murmur)" |
| | dialogueSentences | 25 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0.2 | | effectiveRatio | 0.08 | |