| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1421 | | 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) | |
| 54.26% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1421 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "warmth" | | 1 | "echo" | | 2 | "glint" | | 3 | "pulsed" | | 4 | "footfall" | | 5 | "silence" | | 6 | "scanned" | | 7 | "pulse" | | 8 | "loomed" | | 9 | "whisper" | | 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 | 175 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 175 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 182 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1421 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 74.57% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 1392 | | uniqueNames | 4 | | maxNameDensity | 1.51 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 1 | | Park | 1 | | Heartstone | 2 | | Rory | 21 |
| | persons | | | places | | | globalScore | 0.746 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 106 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like grain in old timber" |
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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 | 1421 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 182 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 86 | | mean | 16.52 | | std | 15.35 | | cv | 0.929 | | sampleLengths | | 0 | 9 | | 1 | 48 | | 2 | 7 | | 3 | 58 | | 4 | 8 | | 5 | 35 | | 6 | 7 | | 7 | 16 | | 8 | 49 | | 9 | 32 | | 10 | 5 | | 11 | 55 | | 12 | 6 | | 13 | 2 | | 14 | 43 | | 15 | 28 | | 16 | 2 | | 17 | 6 | | 18 | 5 | | 19 | 8 | | 20 | 6 | | 21 | 42 | | 22 | 6 | | 23 | 31 | | 24 | 5 | | 25 | 5 | | 26 | 39 | | 27 | 40 | | 28 | 3 | | 29 | 14 | | 30 | 8 | | 31 | 29 | | 32 | 9 | | 33 | 12 | | 34 | 5 | | 35 | 51 | | 36 | 9 | | 37 | 4 | | 38 | 28 | | 39 | 27 | | 40 | 4 | | 41 | 6 | | 42 | 30 | | 43 | 4 | | 44 | 7 | | 45 | 14 | | 46 | 6 | | 47 | 5 | | 48 | 35 | | 49 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 175 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 223 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 182 | | ratio | 0 | | matches | (empty) | |
| 81.43% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 49 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 3 | | adverbRatio | 0.061224489795918366 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 182 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 182 | | mean | 7.81 | | std | 5.04 | | cv | 0.645 | | sampleLengths | | 0 | 9 | | 1 | 22 | | 2 | 12 | | 3 | 14 | | 4 | 7 | | 5 | 6 | | 6 | 10 | | 7 | 15 | | 8 | 15 | | 9 | 12 | | 10 | 4 | | 11 | 4 | | 12 | 13 | | 13 | 3 | | 14 | 19 | | 15 | 3 | | 16 | 4 | | 17 | 8 | | 18 | 2 | | 19 | 6 | | 20 | 8 | | 21 | 16 | | 22 | 14 | | 23 | 11 | | 24 | 9 | | 25 | 3 | | 26 | 20 | | 27 | 5 | | 28 | 5 | | 29 | 21 | | 30 | 13 | | 31 | 16 | | 32 | 6 | | 33 | 2 | | 34 | 12 | | 35 | 7 | | 36 | 2 | | 37 | 22 | | 38 | 8 | | 39 | 13 | | 40 | 7 | | 41 | 2 | | 42 | 3 | | 43 | 3 | | 44 | 5 | | 45 | 8 | | 46 | 6 | | 47 | 6 | | 48 | 7 | | 49 | 13 |
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| 45.05% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.21978021978021978 | | totalSentences | 182 | | uniqueOpeners | 40 | |
| 63.29% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 158 | | matches | | 0 | "Then came another click." | | 1 | "Perhaps fewer if she ran." | | 2 | "Then another, each dent appearing" |
| | ratio | 0.019 | |
| 88.35% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 52 | | totalSentences | 158 | | matches | | 0 | "It had never glowed like" | | 1 | "She had followed the warmth" | | 2 | "Their bark-dark surfaces bore ridges" | | 3 | "She had crossed the park’s" | | 4 | "Her legs disagreed." | | 5 | "Her voice travelled a short" | | 6 | "She drew the Heartstone from" | | 7 | "Its faint inner light coloured" | | 8 | "She had come to find" | | 9 | "They smelled green and sharp," | | 10 | "She moved towards the centre" | | 11 | "She turned and searched the" | | 12 | "She looked at the trees." | | 13 | "She turned in a slow" | | 14 | "Its glow brightened when she" | | 15 | "Her boots pressed the grass" | | 16 | "She glanced over her shoulder." | | 17 | "She could still pick out" | | 18 | "She held still, breathing through" | | 19 | "Her phone buzzed in her" |
| | ratio | 0.329 | |
| 13.80% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 141 | | totalSentences | 158 | | matches | | 0 | "The pendant had warmed three" | | 1 | "Rory had felt it through" | | 2 | "It had never glowed like" | | 3 | "She had followed the warmth" | | 4 | "The clearing held its own" | | 5 | "Moonlight gathered above it but" | | 6 | "Wildflowers crowded the grass in" | | 7 | "Their bark-dark surfaces bore ridges" | | 8 | "Rory checked her phone." | | 9 | "The screen showed 11:18." | | 10 | "She had crossed the park’s" | | 11 | "Her legs disagreed." | | 12 | "A tight ache had settled" | | 13 | "Her voice travelled a short" | | 14 | "She drew the Heartstone from" | | 15 | "The silver chain caught against" | | 16 | "The pendant rested against her" | | 17 | "Its faint inner light coloured" | | 18 | "She had come to find" | | 19 | "That was all." |
| | ratio | 0.892 | |
| 94.94% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 158 | | matches | | 0 | "Now she stood where the" | | 1 | "If the thing had a" | | 2 | "Now she could see eight." |
| | ratio | 0.019 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 1 | | matches | | 0 | "Their bark-dark surfaces bore ridges that looked like grain in old timber." |
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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 | 3 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "Rory muttered (mutter)" | | 2 | "she whispered (whisper)" |
| | dialogueSentences | 12 | | tagDensity | 0.417 | | leniency | 0.833 | | rawRatio | 0.6 | | effectiveRatio | 0.5 | |