| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1030 | | 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) | |
| 12.62% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1030 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "predator" | | 1 | "symphony" | | 2 | "weight" | | 3 | "familiar" | | 4 | "echoing" | | 5 | "silence" | | 6 | "footsteps" | | 7 | "oppressive" | | 8 | "flickered" | | 9 | "dancing" | | 10 | "hulking" | | 11 | "measured" | | 12 | "chaotic" | | 13 | "pulsed" | | 14 | "throb" |
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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 | 90 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 90 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 91 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1026 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 1013 | | uniqueNames | 14 | | maxNameDensity | 0.79 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 8 | | Herrera | 7 | | Raven | 1 | | Nest | 1 | | Saint | 1 | | Christopher | 1 | | London | 3 | | Underground | 1 | | Tube | 1 | | Morris | 3 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Raven" | | 4 | "Nest" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Morris" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like carved animal bone, shimmerin" |
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| 5.07% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.949 | | wordCount | 1026 | | matches | | 0 | "not another tunnel, but a sprawling, chaotic marketplace" | | 1 | "not of pain or fear, but of blank, utter confusion, just before the light consumed hi" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 91 | | matches | (empty) | |
| 63.38% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 18 | | mean | 57 | | std | 21.19 | | cv | 0.372 | | sampleLengths | | 0 | 59 | | 1 | 78 | | 2 | 20 | | 3 | 84 | | 4 | 24 | | 5 | 72 | | 6 | 71 | | 7 | 57 | | 8 | 79 | | 9 | 56 | | 10 | 48 | | 11 | 54 | | 12 | 80 | | 13 | 79 | | 14 | 21 | | 15 | 29 | | 16 | 44 | | 17 | 71 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 90 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 158 | | matches | | 0 | "wasn’t running" | | 1 | "was panting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 91 | | ratio | 0.011 | | matches | | 0 | "The air that drifted out carried an alien scent—ozone, cinnamon, and something thick and coppery, like old blood." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1017 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.02654867256637168 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.010816125860373648 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 91 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 91 | | mean | 11.27 | | std | 6.95 | | cv | 0.616 | | sampleLengths | | 0 | 6 | | 1 | 15 | | 2 | 20 | | 3 | 16 | | 4 | 2 | | 5 | 18 | | 6 | 8 | | 7 | 13 | | 8 | 8 | | 9 | 31 | | 10 | 20 | | 11 | 3 | | 12 | 5 | | 13 | 15 | | 14 | 20 | | 15 | 9 | | 16 | 9 | | 17 | 23 | | 18 | 16 | | 19 | 8 | | 20 | 3 | | 21 | 11 | | 22 | 15 | | 23 | 11 | | 24 | 18 | | 25 | 14 | | 26 | 14 | | 27 | 6 | | 28 | 6 | | 29 | 18 | | 30 | 13 | | 31 | 9 | | 32 | 3 | | 33 | 2 | | 34 | 10 | | 35 | 7 | | 36 | 14 | | 37 | 11 | | 38 | 15 | | 39 | 8 | | 40 | 26 | | 41 | 4 | | 42 | 12 | | 43 | 25 | | 44 | 4 | | 45 | 13 | | 46 | 11 | | 47 | 3 | | 48 | 17 | | 49 | 4 |
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| 43.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.3516483516483517 | | totalSentences | 91 | | uniqueOpeners | 32 | |
| 75.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 88 | | matches | | 0 | "Of course, he didn't listen." | | 1 | "Then he turned and stepped" |
| | ratio | 0.023 | |
| 65.45% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 88 | | matches | | 0 | "It slicked the cobblestones and" | | 1 | "He was fast, faster than" | | 2 | "He moved with a desperate," | | 3 | "Her lungs burned with the" | | 4 | "Her voice was a sharp" | | 5 | "He didn't listen." | | 6 | "He vaulted a stack of" | | 7 | "She landed cleanly, the impact" | | 8 | "He wrenched the door open" | | 9 | "She descended a set of" | | 10 | "Her own breathing sounded unnaturally" | | 11 | "Her footsteps crunched on loose" | | 12 | "She reached the bottom and" | | 13 | "She stood on an abandoned" | | 14 | "He stood before a makeshift" | | 15 | "He wasn’t running anymore." | | 16 | "He was panting, his shoulders" | | 17 | "It was a warning." | | 18 | "He fumbled inside his jacket," | | 19 | "It was white, carved, and" |
| | ratio | 0.386 | |
| 50.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 72 | | totalSentences | 88 | | matches | | 0 | "It slicked the cobblestones and" | | 1 | "Detective Harlow Quinn’s feet pounded" | | 2 | "The green neon of The" | | 3 | "He was fast, faster than" | | 4 | "He moved with a desperate," | | 5 | "Quinn moved with the economy" | | 6 | "Her lungs burned with the" | | 7 | "Her voice was a sharp" | | 8 | "He didn't listen." | | 9 | "He vaulted a stack of" | | 10 | "Quinn followed without breaking stride," | | 11 | "She landed cleanly, the impact" | | 12 | "The alley stank of stale" | | 13 | "Herrera was already at the" | | 14 | "Quinn drew her service weapon," | | 15 | "The lock clicked." | | 16 | "He wrenched the door open" | | 17 | "The heavy door swung shut" | | 18 | "Quinn reached it in seconds," | | 19 | "A wave of cold, stagnant" |
| | ratio | 0.818 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 88 | | matches | (empty) | | ratio | 0 | |
| 66.87% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 47 | | technicalSentenceCount | 5 | | matches | | 0 | "Detective Harlow Quinn’s feet pounded the pavement, each stride a controlled splash that sent dirty water spraying against her trousers." | | 1 | "The tracks were gone, replaced by a wide, dusty concourse that stretched into impenetrable darkness." | | 2 | "He was panting, his shoulders heaving, his hand pressed to his side." | | 3 | "The air that drifted out carried an alien scent—ozone, cinnamon, and something thick and coppery, like old blood." | | 4 | "The man who had been at the warehouse with Morris three years ago, the off-the-books paramedic who stitched up the unexplainable." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |