| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 15 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.37% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1899 | | 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) | |
| 60.51% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1899 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "weight" | | 1 | "pulsed" | | 2 | "pulse" | | 3 | "warmth" | | 4 | "footfall" | | 5 | "furrowed" | | 6 | "vibrated" | | 7 | "charged" | | 8 | "silence" | | 9 | "traced" | | 10 | "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 | 257 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 257 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 267 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1899 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 68 | | wordCount | 1868 | | uniqueNames | 14 | | maxNameDensity | 2.09 | | worstName | "Aurora" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Aurora" | | discoveredNames | | Carter | 1 | | Park | 1 | | Grove | 6 | | Heartstone | 4 | | Richmond | 2 | | Earth | 1 | | Fae | 1 | | Cardiff | 1 | | Aurora | 39 | | Rory | 1 | | Eva | 4 | | Evan | 1 | | Knock | 3 | | Three | 3 |
| | persons | | 0 | "Carter" | | 1 | "Grove" | | 2 | "Heartstone" | | 3 | "Aurora" | | 4 | "Rory" | | 5 | "Eva" | | 6 | "Evan" |
| | places | | 0 | "Park" | | 1 | "Richmond" | | 2 | "Cardiff" | | 3 | "Knock" |
| | globalScore | 0.456 | | windowScore | 0.167 | |
| 78.06% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 139 | | glossingSentenceCount | 4 | | matches | | 0 | "appeared somewhere nearby" | | 1 | "seemed denser now" | | 2 | "appeared long and jointed, the skin stretched thin over the knuckles" | | 3 | "looked like Aurora’s own" |
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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 | 1899 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 267 | | matches | | 0 | "understand that people" | | 1 | "force that pain" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 185 | | mean | 10.26 | | std | 12.16 | | cv | 1.185 | | sampleLengths | | 0 | 12 | | 1 | 65 | | 2 | 6 | | 3 | 12 | | 4 | 20 | | 5 | 12 | | 6 | 8 | | 7 | 7 | | 8 | 3 | | 9 | 12 | | 10 | 8 | | 11 | 63 | | 12 | 2 | | 13 | 14 | | 14 | 30 | | 15 | 5 | | 16 | 3 | | 17 | 56 | | 18 | 12 | | 19 | 8 | | 20 | 8 | | 21 | 3 | | 22 | 72 | | 23 | 5 | | 24 | 1 | | 25 | 5 | | 26 | 12 | | 27 | 6 | | 28 | 35 | | 29 | 7 | | 30 | 23 | | 31 | 5 | | 32 | 2 | | 33 | 6 | | 34 | 6 | | 35 | 2 | | 36 | 14 | | 37 | 8 | | 38 | 10 | | 39 | 4 | | 40 | 3 | | 41 | 38 | | 42 | 3 | | 43 | 38 | | 44 | 5 | | 45 | 8 | | 46 | 45 | | 47 | 5 | | 48 | 8 | | 49 | 11 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 257 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 318 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 267 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 217 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 7 | | adverbRatio | 0.03225806451612903 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.009216589861751152 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 267 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 267 | | mean | 7.11 | | std | 5.14 | | cv | 0.723 | | sampleLengths | | 0 | 12 | | 1 | 6 | | 2 | 16 | | 3 | 13 | | 4 | 30 | | 5 | 6 | | 6 | 12 | | 7 | 12 | | 8 | 6 | | 9 | 2 | | 10 | 2 | | 11 | 4 | | 12 | 6 | | 13 | 8 | | 14 | 7 | | 15 | 3 | | 16 | 4 | | 17 | 8 | | 18 | 8 | | 19 | 17 | | 20 | 16 | | 21 | 17 | | 22 | 13 | | 23 | 2 | | 24 | 14 | | 25 | 7 | | 26 | 7 | | 27 | 16 | | 28 | 5 | | 29 | 3 | | 30 | 15 | | 31 | 13 | | 32 | 28 | | 33 | 12 | | 34 | 8 | | 35 | 4 | | 36 | 4 | | 37 | 3 | | 38 | 9 | | 39 | 15 | | 40 | 27 | | 41 | 4 | | 42 | 17 | | 43 | 5 | | 44 | 1 | | 45 | 5 | | 46 | 12 | | 47 | 6 | | 48 | 11 | | 49 | 5 |
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| 41.73% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 22 | | diversityRatio | 0.24812030075187969 | | totalSentences | 266 | | uniqueOpeners | 66 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 8 | | totalSentences | 231 | | matches | | 0 | "Usually, the Heartstone stayed cold" | | 1 | "Instead, she heard a footstep." | | 2 | "Then the figure leaned out." | | 3 | "Only smooth, pale skin stretched" | | 4 | "Then another set farther back." | | 5 | "Then she pointed towards Aurora’s" | | 6 | "Only the flowers remained, their" | | 7 | "Then a voice spoke beside" |
| | ratio | 0.035 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 52 | | totalSentences | 231 | | matches | | 0 | "Its pale glow clung to" | | 1 | "Her phone showed a dead" | | 2 | "She lifted it, waited, lowered" | | 3 | "It did not travel beyond" | | 4 | "She had come because the" | | 5 | "It rested beneath her jumper" | | 6 | "She had seen what the" | | 7 | "She had seen what came" | | 8 | "She had also seen enough" | | 9 | "It carried the scent of" | | 10 | "She rubbed her thumb over" | | 11 | "Their branches twisted together high" | | 12 | "She knew the Grove held" | | 13 | "She checked the phone again." | | 14 | "she muttered, though she had" | | 15 | "She found none of it." | | 16 | "Her breath tightened." | | 17 | "She waited for another sound." | | 18 | "She drew the small folding" | | 19 | "It would not help against" |
| | ratio | 0.225 | |
| 46.58% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 191 | | totalSentences | 231 | | matches | | 0 | "Aurora Carter crossed beneath the" | | 1 | "The last streetlamp vanished behind" | | 2 | "Its pale glow clung to" | | 3 | "Richmond Park settled around her," | | 4 | "The Grove had always looked" | | 5 | "Tonight, it looked as though" | | 6 | "Aurora stopped with one hand" | | 7 | "The leather creaked under her" | | 8 | "Her phone showed a dead" | | 9 | "She lifted it, waited, lowered" | | 10 | "The word fell flat." | | 11 | "It did not travel beyond" | | 12 | "She had come because the" | | 13 | "It rested beneath her jumper" | | 14 | "Tonight it had pulsed against" | | 15 | "That was the only reason" | | 16 | "She had seen what the" | | 17 | "She had seen what came" | | 18 | "She had also seen enough" | | 19 | "Aurora stepped into the clearing." |
| | ratio | 0.827 | |
| 43.29% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 231 | | matches | | 0 | "By the time she reached" | | 1 | "Now the circle looked undisturbed." |
| | ratio | 0.009 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 59 | | technicalSentenceCount | 2 | | matches | | 0 | "She rubbed her thumb over the small crescent scar on her left wrist, a habit from childhood that appeared whenever her instincts began to scrape at her nerves." | | 1 | "She had found a portal there once, a thin vertical tear in the air that showed a place full of red light and distant, shifting silhouettes." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 4 | | fancyTags | | 0 | "she murmured (murmur)" | | 1 | "she muttered (mutter)" | | 2 | "Eva’s voice whispered (whisper)" | | 3 | "she whispered (whisper)" |
| | dialogueSentences | 15 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.8 | | effectiveRatio | 0.533 | |