| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 27 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1227 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 30.73% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1227 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "vibrated" | | 1 | "rhythmic" | | 2 | "pulsed" | | 3 | "throb" | | 4 | "silence" | | 5 | "mechanical" | | 6 | "weight" | | 7 | "echoed" | | 8 | "pulse" | | 9 | "whisper" | | 10 | "lilt" | | 11 | "echoing" | | 12 | "raced" | | 13 | "familiar" | | 14 | "loomed" | | 15 | "searing" |
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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 | 105 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 105 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 121 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1227 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 1079 | | uniqueNames | 16 | | maxNameDensity | 0.93 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Leo" | | discoveredNames | | Aurora | 1 | | Carter | 1 | | Richmond | 2 | | Park | 2 | | Heartstone | 2 | | Pendant | 2 | | London | 1 | | British | 2 | | Swiss | 1 | | Swedish | 1 | | Leo | 4 | | Welsh | 1 | | Rory | 10 | | Evan | 3 | | Cardiff | 1 | | Fae | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Carter" | | 2 | "Pendant" | | 3 | "Leo" | | 4 | "Rory" | | 5 | "Evan" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "London" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 76 | | glossingSentenceCount | 1 | | matches | | 0 | "as if sniffing her sweat" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.815 | | wordCount | 1227 | | matches | | 0 | "Not with rainwater, but with a thick transparent slime" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 121 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 21.91 | | std | 17.18 | | cv | 0.784 | | sampleLengths | | 0 | 60 | | 1 | 90 | | 2 | 17 | | 3 | 4 | | 4 | 44 | | 5 | 41 | | 6 | 18 | | 7 | 35 | | 8 | 4 | | 9 | 49 | | 10 | 11 | | 11 | 17 | | 12 | 1 | | 13 | 19 | | 14 | 8 | | 15 | 4 | | 16 | 10 | | 17 | 29 | | 18 | 9 | | 19 | 20 | | 20 | 6 | | 21 | 27 | | 22 | 12 | | 23 | 53 | | 24 | 18 | | 25 | 8 | | 26 | 9 | | 27 | 25 | | 28 | 4 | | 29 | 4 | | 30 | 38 | | 31 | 7 | | 32 | 24 | | 33 | 42 | | 34 | 1 | | 35 | 26 | | 36 | 16 | | 37 | 11 | | 38 | 43 | | 39 | 18 | | 40 | 33 | | 41 | 13 | | 42 | 40 | | 43 | 26 | | 44 | 22 | | 45 | 5 | | 46 | 15 | | 47 | 40 | | 48 | 16 | | 49 | 11 |
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| 91.90% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 105 | | matches | | 0 | "was amused" | | 1 | "were placed" | | 2 | "were petrified" | | 3 | "was dragged" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 170 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 121 | | ratio | 0.008 | | matches | | 0 | "The trees weren't oaks; they were petrified giants, their hollow trunks yawning like hungry mouths." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 282 | | adjectiveStacks | 1 | | stackExamples | | 0 | "massive old grey British" |
| | adverbCount | 5 | | adverbRatio | 0.01773049645390071 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 121 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 121 | | mean | 10.14 | | std | 5.77 | | cv | 0.569 | | sampleLengths | | 0 | 14 | | 1 | 15 | | 2 | 16 | | 3 | 15 | | 4 | 10 | | 5 | 27 | | 6 | 18 | | 7 | 6 | | 8 | 14 | | 9 | 6 | | 10 | 9 | | 11 | 8 | | 12 | 9 | | 13 | 4 | | 14 | 9 | | 15 | 24 | | 16 | 11 | | 17 | 5 | | 18 | 13 | | 19 | 23 | | 20 | 18 | | 21 | 11 | | 22 | 7 | | 23 | 1 | | 24 | 16 | | 25 | 4 | | 26 | 12 | | 27 | 3 | | 28 | 10 | | 29 | 12 | | 30 | 9 | | 31 | 3 | | 32 | 11 | | 33 | 15 | | 34 | 2 | | 35 | 1 | | 36 | 10 | | 37 | 4 | | 38 | 5 | | 39 | 8 | | 40 | 4 | | 41 | 10 | | 42 | 7 | | 43 | 6 | | 44 | 16 | | 45 | 4 | | 46 | 5 | | 47 | 11 | | 48 | 9 | | 49 | 6 |
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| 39.39% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.30578512396694213 | | totalSentences | 121 | | uniqueOpeners | 37 | |
| 66.01% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 101 | | matches | | 0 | "Only a soft click-clock sound" | | 1 | "Instead, she backed away, her" |
| | ratio | 0.02 | |
| 85.35% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 101 | | matches | | 0 | "She squeezed her eyes shut," | | 1 | "She opened her eyes to" | | 2 | "They bloomed with impossible vitality," | | 3 | "They leaned toward her, as" | | 4 | "She stood and brushed crushed" | | 5 | "She had followed the pulsing" | | 6 | "She rubbed the crescent-shaped scar" | | 7 | "She reached out and touched" | | 8 | "she called out" | | 9 | "Her voice died in the" | | 10 | "She looked up, but the" | | 11 | "Her breath hitched." | | 12 | "It sounded like Leo." | | 13 | "It didn't belong to any" | | 14 | "It was tall, too thin," | | 15 | "She gripped her sharp small" | | 16 | "It was amused." | | 17 | "His mouth was too wide," | | 18 | "It wore Leo's boots, but" | | 19 | "She flinched at the name." |
| | ratio | 0.337 | |
| 44.16% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 101 | | matches | | 0 | "The silver chain bit into" | | 1 | "The Heartstone Pendant pulsed against" | | 2 | "She squeezed her eyes shut," | | 3 | "She opened her eyes to" | | 4 | "They bloomed with impossible vitality," | | 5 | "They leaned toward her, as" | | 6 | "Rory checked her small gold" | | 7 | "The hands whirred backward in" | | 8 | "She stood and brushed crushed" | | 9 | "She had followed the pulsing" | | 10 | "Every step demanded monumental effort." | | 11 | "The air possessed a physical" | | 12 | "She rubbed the crescent-shaped scar" | | 13 | "Rory crossed the clearing, her" | | 14 | "She reached out and touched" | | 15 | "she called out" | | 16 | "Her voice died in the" | | 17 | "She looked up, but the" | | 18 | "Something shifted in the canopy" | | 19 | "Her breath hitched." |
| | ratio | 0.832 | |
| 99.01% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 101 | | matches | | 0 | "Yet, the tall purple stalks" | | 1 | "Now, the signal directed her" |
| | ratio | 0.02 | |
| 61.99% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 6 | | matches | | 0 | "The Heartstone Pendant pulsed against her bare skin, a hot throb that mirrored her frantic heartbeat." | | 1 | "She opened her eyes to a landscape that defied logic." | | 2 | "Not with rainwater, but with a thick transparent slime that clung to her fingers like grease." | | 3 | "The massive old grey British oak standing stones ground against each other with a deafening screech that vibrated through the soles of her boots." | | 4 | "The Heartstone Pendant flared, a blinding crimson light that illuminated the entire grove." | | 5 | "It was a dry rattling sound that filled her ears and drowned out her own ragged breathing." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 3 | | matches | | 0 | "Rory said, her voice steady despite the hammer of her pulse" | | 1 | "Rory said, her knuckles white around the handle of her pocketknife" | | 2 | "the void whispered, a chorus of a thousand dead voices" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 6 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "the voice whispered (whisper)" | | 2 | "the beast hissed (hiss)" | | 3 | "the thing sneered (sneer)" | | 4 | "the void whispered (whisper)" | | 5 | "Rory spat (spit)" |
| | dialogueSentences | 27 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.667 | | effectiveRatio | 0.444 | |