| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.8 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.33% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1070 | | totalAiIsmAdverbs | 1 | | 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) | |
| 39.25% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1070 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "chill" | | 1 | "silence" | | 2 | "weight" | | 3 | "pulsed" | | 4 | "rhythmic" | | 5 | "throb" | | 6 | "echo" | | 7 | "loomed" | | 8 | "velvet" | | 9 | "throbbed" | | 10 | "pulse" | | 11 | "echoed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 88 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 88 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 89 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1067 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 92.03% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1035 | | uniqueNames | 11 | | maxNameDensity | 1.16 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Richmond | 2 | | Park | 1 | | London | 2 | | Heartstone | 2 | | Pendant | 2 | | Eva | 3 | | Aurora | 12 | | Fae | 1 | | Grove | 1 | | Earth | 1 | | Cardiff | 1 |
| | persons | | | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "London" | | 3 | "Fae" | | 4 | "Grove" | | 5 | "Cardiff" |
| | globalScore | 0.92 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like Eva—the same sharp chin, the" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.937 | | wordCount | 1067 | | matches | | 0 | "not the rich, rotting musk of earth, but something cloying" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 89 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 28.84 | | std | 16.47 | | cv | 0.571 | | sampleLengths | | 0 | 54 | | 1 | 37 | | 2 | 53 | | 3 | 7 | | 4 | 30 | | 5 | 13 | | 6 | 31 | | 7 | 48 | | 8 | 6 | | 9 | 41 | | 10 | 25 | | 11 | 21 | | 12 | 57 | | 13 | 28 | | 14 | 14 | | 15 | 56 | | 16 | 44 | | 17 | 16 | | 18 | 6 | | 19 | 30 | | 20 | 5 | | 21 | 17 | | 22 | 10 | | 23 | 62 | | 24 | 17 | | 25 | 26 | | 26 | 40 | | 27 | 19 | | 28 | 56 | | 29 | 17 | | 30 | 41 | | 31 | 26 | | 32 | 7 | | 33 | 35 | | 34 | 18 | | 35 | 31 | | 36 | 23 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 88 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 158 | | matches | | 0 | "was stretching" | | 1 | "was still glowing" |
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| 14.45% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 1 | | flaggedSentences | 4 | | totalSentences | 89 | | ratio | 0.045 | | matches | | 0 | "A scent rose from her footprints—not the rich, rotting musk of earth, but something cloying and sweet." | | 1 | "Not a breath of wind stirred the grove, yet the sound had been distinct—the dry friction of fabric scraping against bark." | | 2 | "At first glance, it looked like Eva—the same sharp chin, the same spill of dark hair." | | 3 | "It didn't grab her; it merely hovered an inch from her face, its palm sweating a clear, foul-smelling grease." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1042 | | adjectiveStacks | 1 | | stackExamples | | 0 | "many small, needle-sharp teeth." |
| | adverbCount | 28 | | adverbRatio | 0.026871401151631478 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.0067178502879078695 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 89 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 89 | | mean | 11.99 | | std | 6.9 | | cv | 0.576 | | sampleLengths | | 0 | 12 | | 1 | 23 | | 2 | 19 | | 3 | 4 | | 4 | 18 | | 5 | 15 | | 6 | 6 | | 7 | 24 | | 8 | 7 | | 9 | 16 | | 10 | 7 | | 11 | 15 | | 12 | 2 | | 13 | 13 | | 14 | 13 | | 15 | 3 | | 16 | 16 | | 17 | 12 | | 18 | 5 | | 19 | 14 | | 20 | 17 | | 21 | 12 | | 22 | 6 | | 23 | 2 | | 24 | 13 | | 25 | 5 | | 26 | 21 | | 27 | 13 | | 28 | 12 | | 29 | 2 | | 30 | 19 | | 31 | 13 | | 32 | 11 | | 33 | 33 | | 34 | 3 | | 35 | 25 | | 36 | 14 | | 37 | 3 | | 38 | 14 | | 39 | 15 | | 40 | 3 | | 41 | 21 | | 42 | 13 | | 43 | 16 | | 44 | 15 | | 45 | 16 | | 46 | 6 | | 47 | 11 | | 48 | 5 | | 49 | 3 |
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| 38.76% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.2808988764044944 | | totalSentences | 89 | | uniqueOpeners | 25 | |
| 81.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 82 | | matches | | 0 | "Only the visual trick of" | | 1 | "Just a quiet corner of" |
| | ratio | 0.024 | |
| 88.29% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 82 | | matches | | 0 | "She dug her hands into" | | 1 | "She shouldn't have come." | | 2 | "She reached inside her collar," | | 3 | "She took three paces forward." | | 4 | "It smelled of overripe peaches" | | 5 | "Her gaze snapped upward, tracking" | | 6 | "She turned on her heel," | | 7 | "She felt it in the" | | 8 | "She kept her eyes locked" | | 9 | "It had moved with an" | | 10 | "Her skin prickled." | | 11 | "It wasn't an earthquake, but" | | 12 | "She backed up until her" | | 13 | "She looked at her wrist." | | 14 | "It wasn't water." | | 15 | "Her throat felt dry, lined" | | 16 | "It hung upside down, suspended" | | 17 | "It just stared, its pupils" | | 18 | "She didn't look up again." | | 19 | "She broke into a sprint," |
| | ratio | 0.329 | |
| 33.17% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 82 | | matches | | 0 | "Aurora pulled her collar tight" | | 1 | "Midnight had come and gone," | | 2 | "She dug her hands into" | | 3 | "She shouldn't have come." | | 4 | "The text from Eva had" | | 5 | "The silence here possessed a" | | 6 | "Here, the air hung dead" | | 7 | "Wildflowers, vibrant and unyielding to" | | 8 | "A sharp heat bloomed against" | | 9 | "She reached inside her collar," | | 10 | "A slow, rhythmic throb, like" | | 11 | "Aurora’s voice sounded flat, stripped" | | 12 | "The standing stones loomed like" | | 13 | "She took three paces forward." | | 14 | "The grass beneath her boots" | | 15 | "A scent rose from her" | | 16 | "It smelled of overripe peaches" | | 17 | "A rustle slipped through the" | | 18 | "Her gaze snapped upward, tracking" | | 19 | "The leaves remained perfectly still." |
| | ratio | 0.854 | |
| 60.98% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 82 | | matches | | | ratio | 0.012 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 4 | | matches | | 0 | "Midnight had come and gone, leaving the sprawling grounds swallowed in a thick, choking fog that muffled the distant rumble of London traffic." | | 1 | "The gap between the two northernmost standing stones had narrowed, the colossal oaks seeming to lean closer together, their branches weaving a wooden lattice th…" | | 2 | "The eyes sat too far apart, stretching toward the temples, and the mouth curved into a smile that split the pale cheeks too wide, revealing too many small, need…" | | 3 | "Aurora’s instincts, honed by years of running from things that meant her harm, screamed at her to bolt." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 1 | | matches | | 0 | "Aurora said, her voice tighter this time" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "Aurora whispered (whisper)" |
| | dialogueSentences | 5 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.5 | | effectiveRatio | 0.4 | |