| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 85.06% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1339 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slowly" | | 1 | "perfectly" | | 2 | "suddenly" | | 3 | "very" |
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| 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1339 | | totalAiIsms | 32 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | |
| | highlights | | 0 | "pulsed" | | 1 | "rhythmic" | | 2 | "warmth" | | 3 | "echoed" | | 4 | "measured" | | 5 | "navigating" | | 6 | "calculating" | | 7 | "fractured" | | 8 | "silence" | | 9 | "footsteps" | | 10 | "gloom" | | 11 | "pulse" | | 12 | "tracing" | | 13 | "racing" | | 14 | "cataloged" | | 15 | "whisper" | | 16 | "trembled" | | 17 | "stomach" | | 18 | "could feel" | | 19 | "weight" | | 20 | "comforting" | | 21 | "beacon" | | 22 | "vibrated" |
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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 | 141 | | matches | (empty) | |
| 92.20% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 2 | | narrationSentences | 141 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 141 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1339 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 1339 | | uniqueNames | 10 | | maxNameDensity | 0.52 | | worstName | "Aurora" | | maxWindowNameDensity | 1 | | worstWindowName | "Hel" | | discoveredNames | | Carter | 2 | | Park | 1 | | Heartstone | 4 | | London | 2 | | Evan | 1 | | Silas | 2 | | Chinatown | 1 | | Eva | 2 | | Hel | 2 | | Aurora | 7 |
| | persons | | 0 | "Carter" | | 1 | "Heartstone" | | 2 | "Evan" | | 3 | "Silas" | | 4 | "Eva" | | 5 | "Aurora" |
| | places | | 0 | "Park" | | 1 | "London" | | 2 | "Chinatown" |
| | globalScore | 1 | | windowScore | 1 | |
| 91.86% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 86 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like ten minutes" | | 1 | "hum that seemed to scrape against the inside of her skull" |
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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 | 1339 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 141 | | matches | (empty) | |
| 71.34% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 14 | | mean | 95.64 | | std | 38.23 | | cv | 0.4 | | sampleLengths | | 0 | 115 | | 1 | 145 | | 2 | 143 | | 3 | 120 | | 4 | 74 | | 5 | 92 | | 6 | 129 | | 7 | 99 | | 8 | 110 | | 9 | 106 | | 10 | 62 | | 11 | 102 | | 12 | 4 | | 13 | 38 |
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| 95.31% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 141 | | matches | | 0 | "was scarred" | | 1 | "was engineered" | | 2 | "was gone" | | 3 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 226 | | matches | | 0 | "was walking" | | 1 | "were spinning" | | 2 | "was coming" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 141 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1347 | | adjectiveStacks | 2 | | stackExamples | | 0 | "smooth, thumbnail-sized crimson" | | 1 | "small crescent-shaped scar" |
| | adverbCount | 45 | | adverbRatio | 0.0334075723830735 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.009651076466221232 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 141 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 141 | | mean | 9.5 | | std | 7.54 | | cv | 0.794 | | sampleLengths | | 0 | 22 | | 1 | 6 | | 2 | 21 | | 3 | 34 | | 4 | 5 | | 5 | 1 | | 6 | 1 | | 7 | 2 | | 8 | 16 | | 9 | 4 | | 10 | 3 | | 11 | 16 | | 12 | 21 | | 13 | 18 | | 14 | 8 | | 15 | 6 | | 16 | 31 | | 17 | 25 | | 18 | 20 | | 19 | 7 | | 20 | 13 | | 21 | 16 | | 22 | 4 | | 23 | 8 | | 24 | 14 | | 25 | 7 | | 26 | 16 | | 27 | 18 | | 28 | 4 | | 29 | 3 | | 30 | 27 | | 31 | 4 | | 32 | 2 | | 33 | 5 | | 34 | 18 | | 35 | 18 | | 36 | 2 | | 37 | 12 | | 38 | 13 | | 39 | 16 | | 40 | 10 | | 41 | 9 | | 42 | 5 | | 43 | 12 | | 44 | 15 | | 45 | 17 | | 46 | 10 | | 47 | 8 | | 48 | 2 | | 49 | 6 |
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| 39.95% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 22 | | diversityRatio | 0.3333333333333333 | | totalSentences | 141 | | uniqueOpeners | 47 | |
| 56.98% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 117 | | matches | | 0 | "Only the soft, syncopated rhythm" | | 1 | "Just the dry slide of" |
| | ratio | 0.017 | |
| 79.83% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 41 | | totalSentences | 117 | | matches | | 0 | "She kept her boots on" | | 1 | "They stood frozen in perpetual," | | 2 | "They simply waited." | | 3 | "She adjusted her gloves and" | | 4 | "It pulsed once, twice, a" | | 5 | "It wakes when the veil" | | 6 | "She had come to London" | | 7 | "She had not volunteered for" | | 8 | "She stepped past the first" | | 9 | "She frowned, her bright blue" | | 10 | "She forced her shoulders down," | | 11 | "She mapped the grove in" | | 12 | "It was a wet, deliberate" | | 13 | "She turned her head slowly," | | 14 | "It lingered just beyond the" | | 15 | "She repeated it like a" | | 16 | "She exhaled, watching her breath" | | 17 | "She tapped it once with" | | 18 | "She kept walking." | | 19 | "Her heart hammered a steady," |
| | ratio | 0.35 | |
| 71.11% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 91 | | totalSentences | 117 | | matches | | 0 | "The iron gate groaned behind" | | 1 | "Aurora Carter did not look" | | 2 | "She kept her boots on" | | 3 | "Richmond Park had surrendered to" | | 4 | "Wildflowers pushed through the shadows." | | 5 | "They stood frozen in perpetual," | | 6 | "They simply waited." | | 7 | "The Heartstone pendant pressed against" | | 8 | "She adjusted her gloves and" | | 9 | "It pulsed once, twice, a" | | 10 | "The unfamiliar benefactor’s warning echoed" | | 11 | "It wakes when the veil" | | 12 | "She had come to London" | | 13 | "She had not volunteered for" | | 14 | "She stepped past the first" | | 15 | "The bark was scarred and" | | 16 | "Aurora checked her watch." | | 17 | "The second hand jerked forward," | | 18 | "She frowned, her bright blue" | | 19 | "Time felt viscous here, stretched" |
| | ratio | 0.778 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 6 | | totalSentences | 117 | | matches | | 0 | "If this was a Hel" | | 1 | "If something had crossed over," | | 2 | "To find the angle." | | 3 | "If an hour inside could" | | 4 | "Before Eva started calling the" | | 5 | "Before the London streets swallowed" |
| | ratio | 0.051 | |
| 30.08% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 57 | | technicalSentenceCount | 9 | | matches | | 0 | "The iron gate groaned behind her, sealing shut with a finality that felt less like mechanics and more like a jaw closing." | | 1 | "It pulsed once, twice, a slow rhythmic warmth that traveled up her throat and settled behind her ribs." | | 2 | "She had not volunteered for a midnight trek through a pocket of ground that the locals swore didn’t exist, clutching a stone that felt alive." | | 3 | "And bleed-through meant things that had been sleeping, or watching, or waiting." | | 4 | "The wildflowers seemed to tilt toward her, their stems bending at impossible angles, petals parting to reveal dark, hollow centers." | | 5 | "Just the dry slide of air over something that shouldn’t be there." | | 6 | "Standing in the treeline, perfectly still, their outlines bleeding into the bark like charcoal smudges." | | 7 | "The crimson gem pulsed in time with her heartbeat, its inner glow spilling over her knuckles, illuminating the faint scar on her wrist." | | 8 | "She felt the brush of something that was not wind against her hair, felt the deliberate shift of weight in the space beside her, felt the certainty settle into …" |
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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 | |