| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 23 | | tagDensity | 0.087 | | leniency | 0.174 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1899 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 63.14% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1899 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "pulse" | | 1 | "absolutely" | | 2 | "pulsed" | | 3 | "warmth" | | 4 | "silence" | | 5 | "footfall" | | 6 | "perfect" | | 7 | "fractured" | | 8 | "weight" | | 9 | "raced" |
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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 | 265 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 265 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 288 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | 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) | |
| 41.67% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 1 | | matches | | 0 | "On the phone, Eva whispered." |
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| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 71 | | wordCount | 1792 | | uniqueNames | 16 | | maxNameDensity | 2.01 | | worstName | "Rory" | | maxWindowNameDensity | 4 | | worstWindowName | "Rory" | | discoveredNames | | Aurora | 1 | | Heartstone | 7 | | Richmond | 1 | | Park | 1 | | Rory | 36 | | Eva | 10 | | Grove | 4 | | Isolde | 1 | | Cardiff | 1 | | Evan | 1 | | Golden | 1 | | Empress | 1 | | Evans | 1 | | Reed | 1 | | Khan | 1 | | Snip | 3 |
| | persons | | 0 | "Aurora" | | 1 | "Heartstone" | | 2 | "Rory" | | 3 | "Eva" | | 4 | "Evan" | | 5 | "Evans" | | 6 | "Reed" | | 7 | "Khan" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Grove" | | 3 | "Isolde" | | 4 | "Cardiff" | | 5 | "Golden" |
| | globalScore | 0.496 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 139 | | glossingSentenceCount | 2 | | matches | | 0 | "appeared beside Rory’s reply, followed by a timestamp" | | 1 | "seemed small when she entered" |
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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 | 1 | | totalSentences | 288 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 187 | | mean | 10.16 | | std | 11.82 | | cv | 1.164 | | sampleLengths | | 0 | 18 | | 1 | 30 | | 2 | 2 | | 3 | 7 | | 4 | 33 | | 5 | 53 | | 6 | 5 | | 7 | 9 | | 8 | 4 | | 9 | 46 | | 10 | 3 | | 11 | 5 | | 12 | 6 | | 13 | 28 | | 14 | 5 | | 15 | 7 | | 16 | 6 | | 17 | 6 | | 18 | 4 | | 19 | 10 | | 20 | 2 | | 21 | 1 | | 22 | 8 | | 23 | 20 | | 24 | 5 | | 25 | 3 | | 26 | 6 | | 27 | 3 | | 28 | 17 | | 29 | 2 | | 30 | 4 | | 31 | 52 | | 32 | 2 | | 33 | 4 | | 34 | 69 | | 35 | 7 | | 36 | 14 | | 37 | 5 | | 38 | 11 | | 39 | 23 | | 40 | 4 | | 41 | 4 | | 42 | 5 | | 43 | 6 | | 44 | 1 | | 45 | 4 | | 46 | 1 | | 47 | 6 | | 48 | 1 | | 49 | 9 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 265 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 293 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 288 | | ratio | 0.003 | | matches | | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 521 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 12 | | adverbRatio | 0.023032629558541268 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.003838771593090211 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 288 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 288 | | mean | 6.59 | | std | 4.96 | | cv | 0.753 | | sampleLengths | | 0 | 18 | | 1 | 10 | | 2 | 15 | | 3 | 3 | | 4 | 2 | | 5 | 2 | | 6 | 7 | | 7 | 8 | | 8 | 4 | | 9 | 21 | | 10 | 7 | | 11 | 22 | | 12 | 9 | | 13 | 15 | | 14 | 5 | | 15 | 9 | | 16 | 4 | | 17 | 20 | | 18 | 10 | | 19 | 4 | | 20 | 12 | | 21 | 3 | | 22 | 5 | | 23 | 6 | | 24 | 6 | | 25 | 3 | | 26 | 4 | | 27 | 15 | | 28 | 5 | | 29 | 7 | | 30 | 6 | | 31 | 4 | | 32 | 2 | | 33 | 1 | | 34 | 3 | | 35 | 3 | | 36 | 7 | | 37 | 2 | | 38 | 1 | | 39 | 6 | | 40 | 1 | | 41 | 1 | | 42 | 8 | | 43 | 12 | | 44 | 5 | | 45 | 3 | | 46 | 6 | | 47 | 3 | | 48 | 6 | | 49 | 11 |
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| 51.74% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3333333333333333 | | totalSentences | 288 | | uniqueOpeners | 96 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 10 | | totalSentences | 219 | | matches | | 0 | "Then more, stretching between the" | | 1 | "Instead, she had folded it" | | 2 | "Too tall for a deer." | | 3 | "Too narrow for a person." | | 4 | "Only smooth skin, pale and" | | 5 | "Only the silver chain, the" | | 6 | "Then Eva’s voice, faint and" | | 7 | "Then her father’s voice joined" | | 8 | "Only packed earth lifting as" | | 9 | "Then a third." |
| | ratio | 0.046 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 44 | | totalSentences | 219 | | matches | | 0 | "She caught the pendant in" | | 1 | "Her voice fell flat among" | | 2 | "Their twisted trunks rose from" | | 3 | "They looked less like trees" | | 4 | "It should have remained visible." | | 5 | "She turned towards the gap" | | 6 | "She took out her phone." | | 7 | "You had me at do" | | 8 | "She checked the signal." | | 9 | "Her screen returned to Eva’s" | | 10 | "It had begun warming near" | | 11 | "She had come because the" | | 12 | "She should have burnt it." | | 13 | "She pulled it out and" | | 14 | "YOU BROUGHT IT HOME." | | 15 | "Its bark held dozens of" | | 16 | "She backed away without touching" | | 17 | "Her left hand found the" | | 18 | "She opened the compass on" | | 19 | "Her boots had left shallow" |
| | ratio | 0.201 | |
| 87.85% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 163 | | totalSentences | 219 | | matches | | 0 | "The silver chain tightened around" | | 1 | "She caught the pendant in" | | 2 | "The deep crimson gem kicked" | | 3 | "Her voice fell flat among" | | 4 | "Rory loosened the chain and" | | 5 | "Nothing had caught it." | | 6 | "Their twisted trunks rose from" | | 7 | "They looked less like trees" | | 8 | "It should have remained visible." | | 9 | "She turned towards the gap" | | 10 | "The gap had gone." | | 11 | "Wildflowers crowded the boundary instead," | | 12 | "Rory crossed to them and" | | 13 | "She took out her phone." | | 14 | "Eva’s last message filled the" | | 15 | "You had me at do" | | 16 | "The message carried no delivery" | | 17 | "She checked the signal." | | 18 | "Rory called Eva." | | 19 | "The line connected before the" |
| | ratio | 0.744 | |
| 68.49% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 219 | | matches | | 0 | "If the pendant gets hot," | | 1 | "Now the farthest standing stones" | | 2 | "Now the gem pulled towards" |
| | ratio | 0.014 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 57 | | technicalSentenceCount | 3 | | matches | | 0 | "No bramble, hook or grasping hand, which would have ranked low on her list of acceptable explanations but high on honesty." | | 1 | "Wildflowers crowded the boundary instead, their yellow, white and violet heads open to a night that offered them no light." | | 2 | "Only the silver chain, the thumbnail-sized stone, and a smell of smoke that had clung to her hands for hours." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |