| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 43 | | tagDensity | 0.488 | | leniency | 0.977 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.78% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1552 | | 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) | |
| 32.35% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1552 | | totalAiIsms | 21 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "looming" | | 1 | "sentinels" | | 2 | "pulse" | | 3 | "gloom" | | 4 | "familiar" | | 5 | "silence" | | 6 | "chill" | | 7 | "grave" | | 8 | "scanned" | | 9 | "standard" | | 10 | "echo" | | 11 | "pulsed" | | 12 | "throb" | | 13 | "racing" | | 14 | "loomed" | | 15 | "perfect" | | 16 | "lilt" | | 17 | "structure" |
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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 | 194 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 194 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 216 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 22 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 18 | | totalWords | 1546 | | ratio | 0.012 | | matches | | 0 | "The Grove. Midnight. Don't let the lights go out." | | 1 | "snick" | | 2 | "Thump-thump. Thump-thump." | | 3 | "Run, Rory." | | 4 | "00:00" | | 5 | "Run. Run. Run." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.28% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 1349 | | uniqueNames | 19 | | maxNameDensity | 1.33 | | worstName | "Aurora" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 18 | | Richmond | 1 | | Park | 1 | | Heartstone | 3 | | London | 1 | | Fae | 1 | | Grove | 2 | | November | 1 | | Golden | 3 | | Empress | 3 | | Uber | 1 | | Eats | 1 | | Heatstone | 1 | | Ice | 1 | | Eva | 2 | | Rory | 2 | | Welsh | 1 | | Cardiff | 1 | | Evan | 3 |
| | persons | | 0 | "Aurora" | | 1 | "Heartstone" | | 2 | "November" | | 3 | "Eats" | | 4 | "Ice" | | 5 | "Eva" | | 6 | "Rory" | | 7 | "Evan" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "London" | | 3 | "Fae" | | 4 | "Grove" | | 5 | "Golden" | | 6 | "Cardiff" |
| | globalScore | 0.833 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 95 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1546 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 216 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 106 | | mean | 14.58 | | std | 11.37 | | cv | 0.779 | | sampleLengths | | 0 | 37 | | 1 | 11 | | 2 | 29 | | 3 | 40 | | 4 | 32 | | 5 | 3 | | 6 | 18 | | 7 | 59 | | 8 | 3 | | 9 | 45 | | 10 | 13 | | 11 | 12 | | 12 | 42 | | 13 | 1 | | 14 | 9 | | 15 | 5 | | 16 | 12 | | 17 | 8 | | 18 | 28 | | 19 | 18 | | 20 | 16 | | 21 | 26 | | 22 | 2 | | 23 | 15 | | 24 | 16 | | 25 | 29 | | 26 | 8 | | 27 | 5 | | 28 | 24 | | 29 | 4 | | 30 | 11 | | 31 | 4 | | 32 | 19 | | 33 | 6 | | 34 | 11 | | 35 | 3 | | 36 | 11 | | 37 | 1 | | 38 | 10 | | 39 | 10 | | 40 | 4 | | 41 | 23 | | 42 | 8 | | 43 | 12 | | 44 | 27 | | 45 | 7 | | 46 | 12 | | 47 | 7 | | 48 | 25 | | 49 | 18 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 194 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 234 | | matches | | 0 | "was deafening" | | 1 | "was vibrating" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 216 | | ratio | 0.005 | | matches | | 0 | "Their scent hit her a moment later—cloying, sweet, like lilies left on a grave a day too long." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1355 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.022878228782287822 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.005904059040590406 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 216 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 216 | | mean | 7.16 | | std | 4.68 | | cv | 0.654 | | sampleLengths | | 0 | 16 | | 1 | 21 | | 2 | 5 | | 3 | 6 | | 4 | 7 | | 5 | 14 | | 6 | 5 | | 7 | 3 | | 8 | 10 | | 9 | 15 | | 10 | 15 | | 11 | 11 | | 12 | 21 | | 13 | 3 | | 14 | 5 | | 15 | 13 | | 16 | 12 | | 17 | 18 | | 18 | 12 | | 19 | 4 | | 20 | 13 | | 21 | 3 | | 22 | 16 | | 23 | 11 | | 24 | 18 | | 25 | 4 | | 26 | 9 | | 27 | 6 | | 28 | 6 | | 29 | 4 | | 30 | 22 | | 31 | 2 | | 32 | 1 | | 33 | 13 | | 34 | 1 | | 35 | 4 | | 36 | 5 | | 37 | 5 | | 38 | 12 | | 39 | 1 | | 40 | 7 | | 41 | 12 | | 42 | 9 | | 43 | 7 | | 44 | 12 | | 45 | 6 | | 46 | 6 | | 47 | 3 | | 48 | 7 | | 49 | 7 |
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| 47.69% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 27 | | diversityRatio | 0.3611111111111111 | | totalSentences | 216 | | uniqueOpeners | 78 | |
| 61.35% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 163 | | matches | | 0 | "Just the swaying heads of" | | 1 | "Only Eva called her Rory." | | 2 | "Just a wall of ancient" |
| | ratio | 0.018 | |
| 70.31% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 61 | | totalSentences | 163 | | matches | | 0 | "Her boot heel caught on" | | 1 | "She stumbled but corrected her" | | 2 | "It wasn't the gentle pulse" | | 3 | "She hissed and pulled the" | | 4 | "She clicked her torch on." | | 5 | "It was heavy, like the" | | 6 | "Their scent hit her a" | | 7 | "She tapped the glass face" | | 8 | "She scanned the clearing." | | 9 | "She reached into her back" | | 10 | "She slid the blade out" | | 11 | "she said to the darkness" | | 12 | "She pressed her hand over" | | 13 | "It was too fast to" | | 14 | "She took a step forward." | | 15 | "It felt spongy, like walking" | | 16 | "She approached it, the box" | | 17 | "It wasn't a stone." | | 18 | "It was a backpack." | | 19 | "She hooked a finger under" |
| | ratio | 0.374 | |
| 24.42% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 142 | | totalSentences | 163 | | matches | | 0 | "The ancient oak standing stones," | | 1 | "Her boot heel caught on" | | 2 | "She stumbled but corrected her" | | 3 | "The air here tasted metallic." | | 4 | "Copper and ozone." | | 5 | "The Heartstone pendant beneath her" | | 6 | "It wasn't the gentle pulse" | | 7 | "This was a sear, a" | | 8 | "She hissed and pulled the" | | 9 | "The crimson gem glowed through" | | 10 | "She clicked her torch on." | | 11 | "The beam cut through the" | | 12 | "The distant roar of the" | | 13 | "The silence wasn't empty." | | 14 | "It was heavy, like the" | | 15 | "The Fae Grove." | | 16 | "A meadow of wildflowers stretched" | | 17 | "Foxgloves, poppies, and monkshood swayed" | | 18 | "Their scent hit her a" | | 19 | "Aurora checked her watch." |
| | ratio | 0.871 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 163 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 2 | | matches | | 0 | "The ancient oak standing stones, usually looming like silent sentinels over Richmond Park, hummed with a vibration that rattled her teeth." | | 1 | "A throb of heat that matched her own racing heart." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 7 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "she whispered (whisper)" | | 2 | "The thing laughed (laugh)" | | 3 | "Aurora whispered (whisper)" | | 4 | "she spat (spit)" | | 5 | "it snarled (snarl)" | | 6 | "they whispered (whisper)" |
| | dialogueSentences | 43 | | tagDensity | 0.279 | | leniency | 0.558 | | rawRatio | 0.583 | | effectiveRatio | 0.326 | |