| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 92.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1392 | | 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) | |
| 60.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1392 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "stomach" | | 1 | "perfect" | | 2 | "weight" | | 3 | "pulse" | | 4 | "glistening" | | 5 | "vibrated" | | 6 | "chill" | | 7 | "shattered" | | 8 | "gleaming" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 141 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 141 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 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 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1392 | | 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 | 1381 | | uniqueNames | 9 | | maxNameDensity | 0.8 | | worstName | "Nyx" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Nyx" | | discoveredNames | | Sunday | 1 | | Eva | 1 | | London | 1 | | Silas | 1 | | One | 4 | | Cardiff | 1 | | Evan | 1 | | Nyx | 11 | | Rory | 10 |
| | persons | | 0 | "Eva" | | 1 | "Silas" | | 2 | "One" | | 3 | "Evan" | | 4 | "Nyx" | | 5 | "Rory" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 103 | | glossingSentenceCount | 2 | | matches | | 0 | "smelled like her mother's Sunday roasts an" | | 1 | "felt like winter air" |
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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 | 1392 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 141 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 73 | | mean | 19.07 | | std | 15.59 | | cv | 0.817 | | sampleLengths | | 0 | 51 | | 1 | 57 | | 2 | 36 | | 3 | 9 | | 4 | 4 | | 5 | 44 | | 6 | 6 | | 7 | 40 | | 8 | 30 | | 9 | 8 | | 10 | 6 | | 11 | 53 | | 12 | 9 | | 13 | 12 | | 14 | 11 | | 15 | 16 | | 16 | 34 | | 17 | 5 | | 18 | 6 | | 19 | 9 | | 20 | 11 | | 21 | 8 | | 22 | 11 | | 23 | 44 | | 24 | 4 | | 25 | 6 | | 26 | 58 | | 27 | 11 | | 28 | 11 | | 29 | 11 | | 30 | 14 | | 31 | 20 | | 32 | 45 | | 33 | 9 | | 34 | 10 | | 35 | 13 | | 36 | 11 | | 37 | 5 | | 38 | 29 | | 39 | 11 | | 40 | 9 | | 41 | 43 | | 42 | 38 | | 43 | 26 | | 44 | 13 | | 45 | 4 | | 46 | 24 | | 47 | 16 | | 48 | 6 | | 49 | 40 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 141 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 260 | | matches | (empty) | |
| 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) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 690 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.03188405797101449 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005797101449275362 | |
| 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 | 9.87 | | std | 6.1 | | cv | 0.618 | | sampleLengths | | 0 | 13 | | 1 | 20 | | 2 | 18 | | 3 | 5 | | 4 | 17 | | 5 | 22 | | 6 | 13 | | 7 | 20 | | 8 | 16 | | 9 | 9 | | 10 | 4 | | 11 | 5 | | 12 | 24 | | 13 | 6 | | 14 | 9 | | 15 | 3 | | 16 | 3 | | 17 | 6 | | 18 | 26 | | 19 | 8 | | 20 | 14 | | 21 | 16 | | 22 | 8 | | 23 | 6 | | 24 | 24 | | 25 | 13 | | 26 | 16 | | 27 | 3 | | 28 | 6 | | 29 | 12 | | 30 | 11 | | 31 | 5 | | 32 | 11 | | 33 | 12 | | 34 | 7 | | 35 | 15 | | 36 | 5 | | 37 | 6 | | 38 | 9 | | 39 | 5 | | 40 | 6 | | 41 | 8 | | 42 | 3 | | 43 | 8 | | 44 | 19 | | 45 | 25 | | 46 | 4 | | 47 | 6 | | 48 | 3 | | 49 | 20 |
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| 59.34% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.36879432624113473 | | totalSentences | 141 | | uniqueOpeners | 52 | |
| 50.89% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 131 | | matches | | 0 | "Even the plants fight back." | | 1 | "Right after I punch them." |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 131 | | matches | | 0 | "She drew a slow breath." | | 1 | "Its crimson light beat faster" | | 2 | "She slid the fae-forged blade" | | 3 | "We keep moving." | | 4 | "They walked deeper between the" | | 5 | "Her scar itched." | | 6 | "She rubbed her wrist without" | | 7 | "I have everything I never" | | 8 | "He vanished between the vines" | | 9 | "She exhaled hard." | | 10 | "She looked away fast." | | 11 | "They pressed on." | | 12 | "Their petals opened like mouths" | | 13 | "She tightened her grip on" | | 14 | "We circle it." | | 15 | "I want to see what" | | 16 | "They slipped through a gap" | | 17 | "His voice rolled thick and" | | 18 | "She lifted the blade so" | | 19 | "We pass through." |
| | ratio | 0.275 | |
| 32.52% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 112 | | totalSentences | 131 | | matches | | 0 | "Aurora pushed through the rift" | | 1 | "The heartstone burned against her" | | 2 | "Nyx flowed beside her, their" | | 3 | "She drew a slow breath." | | 4 | "Scents crashed over her, roasted" | | 5 | "Vines thicker than her thigh" | | 6 | "Clusters of fruit hung heavy," | | 7 | "The sky stretched without clouds" | | 8 | "Nyx spoke, voice a dry" | | 9 | "This place remembers hunger." | | 10 | "Rory touched the pendant again." | | 11 | "Its crimson light beat faster" | | 12 | "She slid the fae-forged blade" | | 13 | "The moonsilver felt cold enough" | | 14 | "We keep moving." | | 15 | "They walked deeper between the" | | 16 | "Each step released small clouds" | | 17 | "The memories rose so sharply" | | 18 | "A single fruit dropped from" | | 19 | "Juice bubbled up in the" |
| | ratio | 0.855 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 131 | | matches | (empty) | | ratio | 0 | |
| 32.02% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 9 | | matches | | 0 | "The heartstone burned against her collarbone and pulled her onward into soil that sank beneath her boots like fresh bread." | | 1 | "Scents crashed over her, roasted spices and caramelized sugars and something savory that made her stomach clench." | | 2 | "Its crimson light beat faster here, matching the rhythm of distant clinking goblets and low satisfied moans that drifted from beyond the orchard rows." | | 3 | "Each step released small clouds of scented mist that smelled like her mother's Sunday roasts and the cheap cider she drank with Eva on London rooftops." | | 4 | "Nyx gestured toward a cluster of ancient trees whose branches bore fruit that showed moving pictures inside their skins." | | 5 | "Their petals opened like mouths and released puffs of pollen that spelled her name in sparkling letters before dissolving." | | 6 | "Each bloom sang in a different key, their voices braiding into a song that loosened the knot between her shoulders." | | 7 | "A fountain bubbled in the center, but instead of water it poured dark chocolate that shaped itself into tiny running deer before collapsing back into the basin." | | 8 | "Nyx expanded beside her, becoming a wall of living darkness that swallowed the warm glow." |
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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 | |