| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.98% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1497 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "lazily" | | 1 | "carefully" | | 2 | "slightly" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 69.94% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1497 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "flickered" | | 1 | "etched" | | 2 | "magnetic" | | 3 | "weight" | | 4 | "traced" | | 5 | "pulse" | | 6 | "familiar" |
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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 | 123 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 123 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 147 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1477 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 79.02% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1268 | | uniqueNames | 5 | | maxNameDensity | 1.42 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 18 | | Tube | 1 | | Camden | 1 | | Chen | 5 | | Morris | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Chen" | | 2 | "Morris" |
| | places | (empty) | | globalScore | 0.79 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like they'd rather be anywhere els" |
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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 | 1477 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 147 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 23.82 | | std | 21.8 | | cv | 0.915 | | sampleLengths | | 0 | 57 | | 1 | 32 | | 2 | 31 | | 3 | 65 | | 4 | 19 | | 5 | 14 | | 6 | 1 | | 7 | 8 | | 8 | 54 | | 9 | 53 | | 10 | 4 | | 11 | 8 | | 12 | 51 | | 13 | 4 | | 14 | 4 | | 15 | 4 | | 16 | 43 | | 17 | 72 | | 18 | 9 | | 19 | 21 | | 20 | 6 | | 21 | 5 | | 22 | 78 | | 23 | 9 | | 24 | 4 | | 25 | 4 | | 26 | 27 | | 27 | 3 | | 28 | 16 | | 29 | 2 | | 30 | 2 | | 31 | 40 | | 32 | 63 | | 33 | 44 | | 34 | 65 | | 35 | 16 | | 36 | 14 | | 37 | 5 | | 38 | 5 | | 39 | 25 | | 40 | 7 | | 41 | 44 | | 42 | 8 | | 43 | 21 | | 44 | 53 | | 45 | 10 | | 46 | 22 | | 47 | 5 | | 48 | 64 | | 49 | 13 |
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| 91.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 123 | | matches | | 0 | "was loosened" | | 1 | "been knocked" | | 2 | "was unclasped" | | 3 | "been placed" | | 4 | "been sealed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 220 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 18 | | semicolonCount | 0 | | flaggedSentences | 15 | | totalSentences | 147 | | ratio | 0.102 | | matches | | 0 | "Abandoned Tube stations had a particular smell—damp iron, mildew, and the ghost of a million cigarettes smoked by commuters decades dead." | | 1 | "Emergency lighting flickered in weak amber pulses along the ceiling—someone had tapped into the old power grid, jury-rigged it to work." | | 2 | "Harlow catalogued what she could see—bundles of dried herbs hanging from hooks, a table of glass vials filled with liquids in colours that didn't exist in any chemistry textbook she'd studied." | | 3 | "Those hands were clean—too clean for someone who'd been in this place, surrounded by dust and decay." | | 4 | "The items scattered on the ground weren't random—she could see it now in the way they fanned out." | | 5 | "At the bone tokens everyone carried in and out—she still had the warm weight of hers in her pocket." | | 6 | "Or unless they were old enough—or paranoid enough—to default to analogue." | | 7 | "The kind of frames an academic would choose—functional, distinctive." | | 8 | "The journal's cover bore a small embossed crest—a serpent coiled around a pillar." | | 9 | "The crest appeared in the margins of notes Morris had kept in his personal folio—notes that disappeared from evidence forty-eight hours after his death." | | 10 | "Not fear—surprise." | | 11 | "The verdigris was real—the brass casing had genuine age, decades at minimum." | | 12 | "Harlow set the compass down on the nearest flat surface—a stack of old crates—and watched." | | 13 | "Inside, a pale liquid shifted in a way that liquid shouldn't—curling against the glass, pressing, like something alive trying to find a way out." | | 14 | "And whatever she'd found—or whatever had found her—had ended her between one heartbeat and the next, with no violence, no struggle, no evidence of any force a coroner would understand." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1293 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.02242846094354215 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0038669760247486465 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 147 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 147 | | mean | 10.05 | | std | 7.82 | | cv | 0.779 | | sampleLengths | | 0 | 17 | | 1 | 21 | | 2 | 6 | | 3 | 1 | | 4 | 1 | | 5 | 11 | | 6 | 20 | | 7 | 12 | | 8 | 3 | | 9 | 21 | | 10 | 7 | | 11 | 4 | | 12 | 21 | | 13 | 26 | | 14 | 14 | | 15 | 8 | | 16 | 11 | | 17 | 14 | | 18 | 1 | | 19 | 8 | | 20 | 5 | | 21 | 31 | | 22 | 16 | | 23 | 1 | | 24 | 1 | | 25 | 9 | | 26 | 24 | | 27 | 20 | | 28 | 4 | | 29 | 3 | | 30 | 5 | | 31 | 5 | | 32 | 18 | | 33 | 3 | | 34 | 9 | | 35 | 16 | | 36 | 4 | | 37 | 4 | | 38 | 4 | | 39 | 5 | | 40 | 3 | | 41 | 5 | | 42 | 17 | | 43 | 13 | | 44 | 9 | | 45 | 2 | | 46 | 18 | | 47 | 10 | | 48 | 20 | | 49 | 13 |
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| 61.90% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.42857142857142855 | | totalSentences | 147 | | uniqueOpeners | 63 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 106 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 106 | | matches | | 0 | "She'd called in the favour" | | 1 | "His tie was loosened, his" | | 2 | "They walked past the stalls." | | 3 | "Her eyes were open, staring" | | 4 | "She studied the woman's hands." | | 5 | "Its needle spun lazily, despite" | | 6 | "She looked at the stalls," | | 7 | "She crouched again, closer this" | | 8 | "She moved to the satchel." | | 9 | "Her pulse stayed level." | | 10 | "Her hands didn't shake." | | 11 | "She looked at those open" | | 12 | "It had simply happened, between" | | 13 | "Its needle had stopped spinning." | | 14 | "It pointed directly at the" | | 15 | "She picked up the compass." | | 16 | "It had rolled against the" | | 17 | "She'd come here for something" | | 18 | "She stood, leaving the compass" | | 19 | "She stared down at the" |
| | ratio | 0.226 | |
| 77.92% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 81 | | totalSentences | 106 | | matches | | 0 | "The bone token left a" | | 1 | "This one carried something else" | | 2 | "The faintest trace of something" | | 3 | "The uniformed constable ahead of" | | 4 | "Harlow didn't respond." | | 5 | "She'd called in the favour" | | 6 | "The tunnel yawned open." | | 7 | "Emergency lighting flickered in weak" | | 8 | "The scene was crawling with" | | 9 | "DS Chen met her at" | | 10 | "His tie was loosened, his" | | 11 | "They walked past the stalls." | | 12 | "Harlow catalogued what she could" | | 13 | "The body lay on the" | | 14 | "Her eyes were open, staring" | | 15 | "Harlow crouched beside the body." | | 16 | "The woman's skin had an" | | 17 | "The satchel was unclasped, a" | | 18 | "She studied the woman's hands." | | 19 | "Those hands were clean—too clean" |
| | ratio | 0.764 | |
| 94.34% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 106 | | matches | | 0 | "Before someone could scrub whatever" | | 1 | "Either she'd been placed here" |
| | ratio | 0.019 | |
| 60.44% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 6 | | matches | | 0 | "The officer at the door had accepted it without question, which meant it was currency here." | | 1 | "Chen hovered behind her, radiating the particular discomfort of a man who wanted to solve a case without examining the inconvenient parts." | | 2 | "The leather was worn smooth at the edges from years of handling, the kind of patina that didn't come from casual use." | | 3 | "The crest appeared in the margins of notes Morris had kept in his personal folio—notes that disappeared from evidence forty-eight hours after his death." | | 4 | "It had rolled against the wall, its stopper still sealed with wax that bore the same serpent-and-pillar imprint as the journal." | | 5 | "She'd come here for something specific, something connected to symbols and sigils and a crest that had appeared in her dead partner's files." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "Chen muttered (mutter)" |
| | dialogueSentences | 28 | | tagDensity | 0.071 | | leniency | 0.143 | | rawRatio | 0.5 | | effectiveRatio | 0.071 | |