| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 119 | | tagDensity | 0.109 | | leniency | 0.218 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1572 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 74.55% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1572 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "familiar" | | 1 | "flicked" | | 2 | "pulse" | | 3 | "mechanical" | | 4 | "warmth" | | 5 | "racing" | | 6 | "flickered" |
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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 | 145 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 145 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 250 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1572 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 31 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 103 | | wordCount | 1124 | | uniqueNames | 15 | | maxNameDensity | 3.74 | | worstName | "Eva" | | maxWindowNameDensity | 6 | | worstWindowName | "Eva" | | discoveredNames | | Aurora | 30 | | Rory | 6 | | Eva | 42 | | Silas | 14 | | Blackwood | 1 | | Raven | 1 | | Nest | 1 | | Prague | 1 | | Aberystwyth | 1 | | Cardiff | 1 | | Evan | 1 | | Leave | 1 | | London | 1 | | Golden | 1 | | Empress | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Rory" | | 2 | "Eva" | | 3 | "Silas" | | 4 | "Blackwood" | | 5 | "Raven" | | 6 | "Nest" | | 7 | "Evan" |
| | places | | 0 | "Prague" | | 1 | "Aberystwyth" | | 2 | "Cardiff" | | 3 | "London" | | 4 | "Golden" |
| | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 78 | | glossingSentenceCount | 1 | | matches | | 0 | "not quite fear, not quite anger" | | 1 | "not quite anger" |
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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 | 1572 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 250 | | matches | | 0 | "complained that Aurora" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 187 | | mean | 8.41 | | std | 11.51 | | cv | 1.37 | | sampleLengths | | 0 | 9 | | 1 | 19 | | 2 | 10 | | 3 | 3 | | 4 | 6 | | 5 | 69 | | 6 | 4 | | 7 | 1 | | 8 | 21 | | 9 | 4 | | 10 | 4 | | 11 | 61 | | 12 | 61 | | 13 | 6 | | 14 | 15 | | 15 | 2 | | 16 | 1 | | 17 | 9 | | 18 | 9 | | 19 | 1 | | 20 | 1 | | 21 | 8 | | 22 | 3 | | 23 | 22 | | 24 | 8 | | 25 | 5 | | 26 | 4 | | 27 | 34 | | 28 | 43 | | 29 | 10 | | 30 | 7 | | 31 | 5 | | 32 | 3 | | 33 | 3 | | 34 | 12 | | 35 | 15 | | 36 | 4 | | 37 | 6 | | 38 | 4 | | 39 | 4 | | 40 | 14 | | 41 | 4 | | 42 | 6 | | 43 | 3 | | 44 | 2 | | 45 | 5 | | 46 | 3 | | 47 | 13 | | 48 | 21 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 145 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 214 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 250 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1130 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 30 | | adverbRatio | 0.02654867256637168 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0035398230088495575 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 250 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 250 | | mean | 6.29 | | std | 5.18 | | cv | 0.823 | | sampleLengths | | 0 | 9 | | 1 | 19 | | 2 | 6 | | 3 | 4 | | 4 | 3 | | 5 | 6 | | 6 | 22 | | 7 | 5 | | 8 | 20 | | 9 | 12 | | 10 | 10 | | 11 | 4 | | 12 | 1 | | 13 | 7 | | 14 | 14 | | 15 | 4 | | 16 | 4 | | 17 | 6 | | 18 | 6 | | 19 | 22 | | 20 | 14 | | 21 | 13 | | 22 | 8 | | 23 | 21 | | 24 | 16 | | 25 | 16 | | 26 | 6 | | 27 | 9 | | 28 | 6 | | 29 | 2 | | 30 | 1 | | 31 | 9 | | 32 | 9 | | 33 | 1 | | 34 | 1 | | 35 | 5 | | 36 | 3 | | 37 | 3 | | 38 | 5 | | 39 | 4 | | 40 | 13 | | 41 | 8 | | 42 | 5 | | 43 | 4 | | 44 | 15 | | 45 | 2 | | 46 | 17 | | 47 | 13 | | 48 | 9 | | 49 | 5 |
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| 46.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.268 | | totalSentences | 250 | | uniqueOpeners | 67 | |
| 54.20% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 123 | | matches | | 0 | "Then Eva had vanished." | | 1 | "Then the front windows exploded." |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 123 | | matches | | 0 | "Her blond hair, once long" | | 1 | "Its pendant rested against her" | | 2 | "He saw Aurora’s face, then" | | 3 | "His gaze settled on Eva." | | 4 | "He noticed everything, though he" | | 5 | "He picked up two fresh" | | 6 | "He had never needed to." | | 7 | "She had believed motion meant" | | 8 | "His silver signet ring caught" | | 9 | "he said to Eva" | | 10 | "His voice had lost its" | | 11 | "She hated Eva for making" | | 12 | "He walked away, though not" | | 13 | "It held battered novels, old" | | 14 | "She remembered Eva pressing a" | | 15 | "She remembered Eva saying, Leave" | | 16 | "Her childhood name." | | 17 | "Her face turned towards a" |
| | ratio | 0.146 | |
| 8.78% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 111 | | totalSentences | 123 | | matches | | 0 | "The glass struck the bar" | | 1 | "Aurora caught it before it" | | 2 | "Aurora looked up." | | 3 | "Eva had grown a sharper" | | 4 | "The last time Rory had" | | 5 | "Her blond hair, once long" | | 6 | "A thin silver chain disappeared" | | 7 | "Its pendant rested against her" | | 8 | "Aurora released the glass." | | 9 | "Eva’s hand tightened around her" | | 10 | "The bar carried on around" | | 11 | "A laugh burst near the" | | 12 | "Someone fed coins into the" | | 13 | "He saw Aurora’s face, then" | | 14 | "The Raven’s Nest gathered secrets" | | 15 | "Aurora had delivered food here," | | 16 | "Aurora touched the ends of" | | 17 | "Eva smiled, but nothing in" | | 18 | "Silas came over, moving with" | | 19 | "His gaze settled on Eva." |
| | ratio | 0.902 | |
| 81.30% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 123 | | matches | | 0 | "Now the bones showed through." | | 1 | "Now she looked at Eva’s" |
| | ratio | 0.016 | |
| 69.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 4 | | matches | | 0 | "The last time Rory had seen her, Eva had possessed a round, open beauty that made strangers trust her before she spoke." | | 1 | "The image held the grey, stunned expression of a place that had watched too much burn." | | 2 | "A faint red mark circled the left wrist, as if someone had fastened a cord there and pulled it tight." | | 3 | "The name Eva had given her in secret when they were children, after Rory complained that Aurora sounded too grand for someone who fell out of trees and stole ap…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 119 | | tagDensity | 0.109 | | leniency | 0.218 | | rawRatio | 0 | | effectiveRatio | 0 | |