| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 1 | | adverbTags | | 0 | "Mills gestured upward [upward]" |
| | dialogueSentences | 47 | | tagDensity | 0.191 | | leniency | 0.383 | | rawRatio | 0.111 | | effectiveRatio | 0.043 | |
| 91.95% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1242 | | 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) | |
| 75.85% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1242 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "echoed" | | 1 | "synthetic" | | 2 | "etched" | | 3 | "pulse" | | 4 | "warmth" | | 5 | "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 | 1 | | narrationSentences | 69 | | matches | | |
| 18.63% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 4 | | narrationSentences | 69 | | filterMatches | | | hedgeMatches | | 0 | "appeared to" | | 1 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1226 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 62.75% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 745 | | uniqueNames | 13 | | maxNameDensity | 1.74 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Tube | 1 | | Detective | 2 | | Harlow | 1 | | Quinn | 13 | | Victorian-era | 1 | | Sergeant | 1 | | Mills | 8 | | Morris | 2 | | Hartwell | 3 | | Italian | 1 | | British | 1 | | English | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Victorian-era" | | 3 | "Sergeant" | | 4 | "Mills" | | 5 | "Morris" | | 6 | "Hartwell" |
| | places | | | globalScore | 0.628 | | windowScore | 0.833 | |
| 59.09% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like vendor stalls—wooden crates," | | 1 | "metals that seemed to absorb light rather than reflect it" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1226 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 107 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 54 | | mean | 22.7 | | std | 15.94 | | cv | 0.702 | | sampleLengths | | 0 | 55 | | 1 | 35 | | 2 | 36 | | 3 | 4 | | 4 | 18 | | 5 | 31 | | 6 | 7 | | 7 | 7 | | 8 | 32 | | 9 | 14 | | 10 | 27 | | 11 | 4 | | 12 | 7 | | 13 | 30 | | 14 | 8 | | 15 | 35 | | 16 | 42 | | 17 | 9 | | 18 | 4 | | 19 | 50 | | 20 | 6 | | 21 | 35 | | 22 | 11 | | 23 | 10 | | 24 | 12 | | 25 | 42 | | 26 | 61 | | 27 | 11 | | 28 | 9 | | 29 | 66 | | 30 | 9 | | 31 | 13 | | 32 | 5 | | 33 | 36 | | 34 | 21 | | 35 | 37 | | 36 | 9 | | 37 | 50 | | 38 | 13 | | 39 | 28 | | 40 | 16 | | 41 | 4 | | 42 | 27 | | 43 | 10 | | 44 | 8 | | 45 | 22 | | 46 | 17 | | 47 | 20 | | 48 | 37 | | 49 | 10 |
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| 90.01% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 69 | | matches | | 0 | "was etched" | | 1 | "been lowered" | | 2 | "was written" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 128 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 107 | | ratio | 0.075 | | matches | | 0 | "The abandoned Camden Tube station reeked of decay and something else—something metallic that made Detective Harlow Quinn's teeth ache." | | 1 | "Something nagged at her—the same feeling she'd had three years ago when Morris died." | | 2 | "There—carved into the grimy tile work." | | 3 | "Scattered across the platform were the remnants of what looked like vendor stalls—wooden crates, fabric scraps, and strange glass bottles that caught the torchlight like prisms." | | 4 | "The liquid inside swirled with colours that shouldn't exist—deep purples that shifted to silver, then to something that hurt to look at directly." | | 5 | "Scattered coins lay across the warped wooden surface—but not British currency." | | 6 | "She'd found something else—a small brass compass half-hidden beneath an overturned crate." | | 7 | "A piece of parchment caught her attention—old paper covered in handwritten text." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 756 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.03835978835978836 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.01455026455026455 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 11.46 | | std | 6.01 | | cv | 0.525 | | sampleLengths | | 0 | 19 | | 1 | 19 | | 2 | 17 | | 3 | 13 | | 4 | 8 | | 5 | 14 | | 6 | 11 | | 7 | 17 | | 8 | 8 | | 9 | 4 | | 10 | 8 | | 11 | 10 | | 12 | 9 | | 13 | 14 | | 14 | 8 | | 15 | 7 | | 16 | 7 | | 17 | 8 | | 18 | 17 | | 19 | 7 | | 20 | 2 | | 21 | 12 | | 22 | 4 | | 23 | 14 | | 24 | 9 | | 25 | 4 | | 26 | 4 | | 27 | 3 | | 28 | 16 | | 29 | 14 | | 30 | 8 | | 31 | 27 | | 32 | 8 | | 33 | 6 | | 34 | 22 | | 35 | 14 | | 36 | 9 | | 37 | 4 | | 38 | 6 | | 39 | 26 | | 40 | 18 | | 41 | 6 | | 42 | 12 | | 43 | 23 | | 44 | 5 | | 45 | 6 | | 46 | 10 | | 47 | 12 | | 48 | 9 | | 49 | 7 |
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| 80.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5046728971962616 | | totalSentences | 107 | | uniqueOpeners | 54 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 68 | | matches | | 0 | "She descended the rusted stairs," | | 1 | "His voice echoed strangely in" | | 2 | "She played her torch across" | | 3 | "She lifted one polished oxford" | | 4 | "She picked up one of" | | 5 | "She crouched beside what appeared" | | 6 | "She'd found something else—a small" | | 7 | "It spun wildly for a" | | 8 | "She pocketed the compass." | | 9 | "She walked to the platform" | | 10 | "She turned back to the" | | 11 | "She faced him directly, her" | | 12 | "She pocketed the parchment" |
| | ratio | 0.191 | |
| 55.59% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 68 | | matches | | 0 | "The abandoned Camden Tube station" | | 1 | "She descended the rusted stairs," | | 2 | "The beam of her torch" | | 3 | "Detective Sergeant Mills called from" | | 4 | "His voice echoed strangely in" | | 5 | "Quinn's boots crunched on broken" | | 6 | "Hartwell lay sprawled beside what" | | 7 | "Blood pooled beneath his head," | | 8 | "Mills gestured upward" | | 9 | "Quinn knelt beside the corpse," | | 10 | "Something nagged at her—the same" | | 11 | "The same wrongness that preceded" | | 12 | "She played her torch across" | | 13 | "The metal safety barriers stood" | | 14 | "Quinn examined Hartwell's clothing." | | 15 | "Designer jeans, expensive leather jacket," | | 16 | "Mills crouched beside her." | | 17 | "She lifted one polished oxford" | | 18 | "Quinn stood and swept her" | | 19 | "The beam caught something that" |
| | ratio | 0.809 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 79.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 3 | | matches | | 0 | "Designer jeans, expensive leather jacket, Italian shoes that cost more than her monthly salary." | | 1 | "The liquid inside swirled with colours that shouldn't exist—deep purples that shifted to silver, then to something that hurt to look at directly." | | 2 | "It spun wildly for a moment before settling on a direction that led deeper into the abandoned station." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.021 | | leniency | 0.043 | | rawRatio | 0 | | effectiveRatio | 0 | |