| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 24 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1967 | | totalAiIsmAdverbs | 4 | | 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) | |
| 41.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1967 | | totalAiIsms | 23 | | found | | | highlights | | 0 | "echo" | | 1 | "warmth" | | 2 | "pulse" | | 3 | "throb" | | 4 | "chill" | | 5 | "scanned" | | 6 | "stomach" | | 7 | "porcelain" | | 8 | "unsettled" | | 9 | "silence" | | 10 | "measured" | | 11 | "flickered" | | 12 | "whisper" | | 13 | "lurched" | | 14 | "pulsed" | | 15 | "perfect" | | 16 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 242 | | matches | | 0 | "m with relief" | | 1 | "was angry" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 242 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 262 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1967 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 1908 | | uniqueNames | 13 | | maxNameDensity | 0.73 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Carter | 1 | | Fae | 1 | | Grove | 5 | | Richmond | 2 | | Heartstone | 3 | | Yu-Fei | 1 | | London | 2 | | Five | 1 | | Park | 1 | | Eva | 1 | | Cardiff | 1 | | Moonlight | 3 | | Rory | 14 |
| | persons | | 0 | "Carter" | | 1 | "Heartstone" | | 2 | "Yu-Fei" | | 3 | "Eva" | | 4 | "Moonlight" | | 5 | "Rory" |
| | places | | 0 | "Fae" | | 1 | "Grove" | | 2 | "Richmond" | | 3 | "London" | | 4 | "Park" | | 5 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 134 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 98.32% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.017 | | wordCount | 1967 | | matches | | 0 | "not physically, not enough to move her hand, but her body answered all the same" | | 1 | "not enough to move her hand, but her body answered all the same" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 262 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 134 | | mean | 14.68 | | std | 16.03 | | cv | 1.092 | | sampleLengths | | 0 | 33 | | 1 | 3 | | 2 | 79 | | 3 | 65 | | 4 | 1 | | 5 | 18 | | 6 | 46 | | 7 | 14 | | 8 | 16 | | 9 | 7 | | 10 | 86 | | 11 | 6 | | 12 | 11 | | 13 | 13 | | 14 | 51 | | 15 | 38 | | 16 | 1 | | 17 | 14 | | 18 | 8 | | 19 | 41 | | 20 | 2 | | 21 | 7 | | 22 | 8 | | 23 | 4 | | 24 | 4 | | 25 | 50 | | 26 | 1 | | 27 | 2 | | 28 | 4 | | 29 | 24 | | 30 | 2 | | 31 | 18 | | 32 | 3 | | 33 | 4 | | 34 | 12 | | 35 | 2 | | 36 | 14 | | 37 | 8 | | 38 | 41 | | 39 | 2 | | 40 | 2 | | 41 | 17 | | 42 | 40 | | 43 | 31 | | 44 | 27 | | 45 | 60 | | 46 | 7 | | 47 | 3 | | 48 | 9 | | 49 | 33 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 242 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 303 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 262 | | ratio | 0.004 | | matches | | 0 | "She fixed on them with relief, counted one, two, three, four—" |
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| 97.93% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1912 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 81 | | adverbRatio | 0.04236401673640167 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.006276150627615063 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 262 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 262 | | mean | 7.51 | | std | 6.15 | | cv | 0.819 | | sampleLengths | | 0 | 33 | | 1 | 3 | | 2 | 11 | | 3 | 35 | | 4 | 11 | | 5 | 22 | | 6 | 12 | | 7 | 12 | | 8 | 9 | | 9 | 9 | | 10 | 23 | | 11 | 1 | | 12 | 4 | | 13 | 2 | | 14 | 5 | | 15 | 7 | | 16 | 14 | | 17 | 18 | | 18 | 9 | | 19 | 5 | | 20 | 14 | | 21 | 2 | | 22 | 2 | | 23 | 12 | | 24 | 7 | | 25 | 22 | | 26 | 24 | | 27 | 23 | | 28 | 3 | | 29 | 3 | | 30 | 11 | | 31 | 6 | | 32 | 11 | | 33 | 13 | | 34 | 5 | | 35 | 23 | | 36 | 6 | | 37 | 7 | | 38 | 5 | | 39 | 5 | | 40 | 10 | | 41 | 16 | | 42 | 12 | | 43 | 1 | | 44 | 3 | | 45 | 5 | | 46 | 6 | | 47 | 3 | | 48 | 5 | | 49 | 6 |
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| 44.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 19 | | diversityRatio | 0.31297709923664124 | | totalSentences | 262 | | uniqueOpeners | 82 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 12 | | totalSentences | 197 | | matches | | 0 | "Just enough to feel alive." | | 1 | "Even her breathing sounded borrowed." | | 2 | "Just the open patch of" | | 3 | "Then another click." | | 4 | "Just a denser vertical slice" | | 5 | "Only open grass and flowers" | | 6 | "Too many joints in the" | | 7 | "Only one person had called" | | 8 | "Then, from her left, in" | | 9 | "Only flowers, waist-high now, their" | | 10 | "Even the pendant’s pulse paused." | | 11 | "Slowly, carefully, she lifted her" |
| | ratio | 0.061 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 59 | | totalSentences | 197 | | matches | | 0 | "It had not." | | 1 | "Their trunks leaned at angles" | | 2 | "Her voice landed flat." | | 3 | "She reached beneath the collar" | | 4 | "It held a faint warmth," | | 5 | "She had cut through a" | | 6 | "She had followed the heat" | | 7 | "She moved slowly, boots sinking" | | 8 | "She scanned the ring of" | | 9 | "She crouched and touched the" | | 10 | "She pinched a blue flower" | | 11 | "Its petals felt waxy, thick" | | 12 | "She stared at it until" | | 13 | "She rose too fast, her" | | 14 | "She fixed on them with" | | 15 | "Her stomach tightened." | | 16 | "She counted again." | | 17 | "She stepped sideways, craning her" | | 18 | "She pivoted again." | | 19 | "Her own senses felt out" |
| | ratio | 0.299 | |
| 89.44% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 146 | | totalSentences | 197 | | matches | | 0 | "Aurora Carter stood with one" | | 1 | "It had not." | | 2 | "The Fae Grove sat in" | | 3 | "Moonlight spilled through the branches" | | 4 | "The ancient oaks ringed the" | | 5 | "Their trunks leaned at angles" | | 6 | "Rory let the stone go" | | 7 | "The drive out to Richmond" | | 8 | "The walk from the road" | | 9 | "Her voice landed flat." | | 10 | "The Grove swallowed sound and" | | 11 | "She reached beneath the collar" | | 12 | "The crimson gem sat in" | | 13 | "It held a faint warmth," | | 14 | "A dull throb against her" | | 15 | "That had been her reason" | | 16 | "She had cut through a" | | 17 | "She had followed the heat" | | 18 | "A pinprick ember in the" | | 19 | "Tonight she had come back" |
| | ratio | 0.741 | |
| 50.76% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 197 | | matches | | 0 | "By the time she found" | | 1 | "To her left this time." |
| | ratio | 0.01 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 75 | | technicalSentenceCount | 2 | | matches | | 0 | "Moonlight spilled through the branches in thin silver bars, caught on wildflowers that should not have bloomed in late autumn, and pooled over the grass with a …" | | 1 | "She headed for the nearest gap in the trees with quick, hard steps, keeping her eyes fixed on one lichen-covered stone as if concentration alone would hold it s…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 25.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 3 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "she whispered (whisper)" | | 2 | "Rory snapped (snap)" |
| | dialogueSentences | 24 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0.75 | | effectiveRatio | 0.25 | |