| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said quietly [quietly]" | | 1 | "she whispered again [again]" |
| | dialogueSentences | 4 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |
| 70.12% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1004 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "slowly" | | 1 | "slightly" | | 2 | "very" |
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| 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) | |
| 55.18% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1004 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "furrowed" | | 1 | "silence" | | 2 | "pulse" | | 3 | "flicker" | | 4 | "weight" | | 5 | "pulsed" | | 6 | "throb" | | 7 | "warmth" | | 8 | "comforting" |
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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 | 91 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 91 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 91 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 2 | | totalWords | 1004 | | ratio | 0.002 | | matches | | |
| 75.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 1 | | matches | | 0 | "Deer, she told herself." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 9 | | wordCount | 998 | | uniqueNames | 4 | | maxNameDensity | 0.4 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Tap" | | discoveredNames | | Rory | 4 | | Heartstone | 1 | | October | 1 | | Tap | 3 |
| | persons | | | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 1004 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 91 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 33.47 | | std | 19.45 | | cv | 0.581 | | sampleLengths | | 0 | 61 | | 1 | 64 | | 2 | 36 | | 3 | 36 | | 4 | 18 | | 5 | 58 | | 6 | 50 | | 7 | 13 | | 8 | 21 | | 9 | 27 | | 10 | 3 | | 11 | 23 | | 12 | 58 | | 13 | 48 | | 14 | 7 | | 15 | 56 | | 16 | 55 | | 17 | 9 | | 18 | 10 | | 19 | 50 | | 20 | 46 | | 21 | 47 | | 22 | 27 | | 23 | 11 | | 24 | 64 | | 25 | 29 | | 26 | 5 | | 27 | 20 | | 28 | 22 | | 29 | 30 |
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| 89.84% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 91 | | matches | | 0 | "been locked" | | 1 | "was carpeted" | | 2 | "been open" | | 3 | "was gone" |
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| 71.79% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 156 | | matches | | 0 | "was breathing" | | 1 | "was pointing" | | 2 | "were listening" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 91 | | ratio | 0 | | matches | (empty) | |
| 91.45% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1002 | | adjectiveStacks | 1 | | stackExamples | | 0 | "sweet, cellar-cold air," |
| | adverbCount | 43 | | adverbRatio | 0.04291417165668663 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.012974051896207584 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 91 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 91 | | mean | 11.03 | | std | 8.5 | | cv | 0.771 | | sampleLengths | | 0 | 23 | | 1 | 28 | | 2 | 4 | | 3 | 6 | | 4 | 13 | | 5 | 15 | | 6 | 31 | | 7 | 5 | | 8 | 5 | | 9 | 4 | | 10 | 27 | | 11 | 21 | | 12 | 3 | | 13 | 12 | | 14 | 4 | | 15 | 14 | | 16 | 9 | | 17 | 20 | | 18 | 11 | | 19 | 18 | | 20 | 9 | | 21 | 12 | | 22 | 3 | | 23 | 8 | | 24 | 18 | | 25 | 6 | | 26 | 7 | | 27 | 5 | | 28 | 16 | | 29 | 2 | | 30 | 7 | | 31 | 1 | | 32 | 17 | | 33 | 3 | | 34 | 9 | | 35 | 14 | | 36 | 5 | | 37 | 4 | | 38 | 19 | | 39 | 5 | | 40 | 25 | | 41 | 6 | | 42 | 22 | | 43 | 1 | | 44 | 19 | | 45 | 7 | | 46 | 17 | | 47 | 15 | | 48 | 7 | | 49 | 3 |
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| 57.51% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.38461538461538464 | | totalSentences | 91 | | uniqueOpeners | 35 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 79 | | matches | | 0 | "Only the foxgloves, the stones," | | 1 | "Just a tree, the bark" | | 2 | "Then a second rhythm answered" | | 3 | "Instead she shifted her weight," | | 4 | "Once, twice, a warm throb" | | 5 | "Only a fraction." |
| | ratio | 0.076 | |
| 32.66% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 79 | | matches | | 0 | "She stood a moment at" | | 1 | "She had found it the" | | 2 | "She switched off the torch." | | 3 | "Her eyes adjusted slowly." | | 4 | "She looked back." | | 5 | "she said quietly" | | 6 | "Her voice came out flat," | | 7 | "They stood in a loose" | | 8 | "She counted seven before she" | | 9 | "It was October." | | 10 | "She stepped over the nearest" | | 11 | "Her boot came down on" | | 12 | "*You came*, a voice said." | | 13 | "She turned slowly in a" | | 14 | "It had the particular density" | | 15 | "She took out her phone." | | 16 | "She stared at it, then" | | 17 | "She pressed the side button," | | 18 | "Her pulse ticked in her" | | 19 | "She made herself breathe in" |
| | ratio | 0.468 | |
| 67.59% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 62 | | totalSentences | 79 | | matches | | 0 | "The park gate had been" | | 1 | "She stood a moment at" | | 2 | "Deer, she told herself." | | 3 | "Richmond had more deer than" | | 4 | "The path she wanted was" | | 5 | "She had found it the" | | 6 | "The Heartstone lay against her" | | 7 | "She switched off the torch." | | 8 | "Her eyes adjusted slowly." | | 9 | "The city glow over the" | | 10 | "The path bent left, then" | | 11 | "She looked back." | | 12 | "she said quietly" | | 13 | "Her voice came out flat," | | 14 | "The grove announced itself with" | | 15 | "They stood in a loose" | | 16 | "She counted seven before she" | | 17 | "Bluebells, primroses, a wash of" | | 18 | "It was October." | | 19 | "The scent hit her a" |
| | ratio | 0.785 | |
| 63.29% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 79 | | matches | | 0 | "Now it was almost hot." |
| | ratio | 0.013 | |
| 89.29% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 3 | | matches | | 0 | "Then a second rhythm answered it from the south, slightly off-beat, as if something were listening and trying to match her." | | 1 | "It only waited, the way a held breath waits, and the flowers at its feet turned their faces toward her, all at once, like an audience that had been expecting he…" | | 2 | "Running, she understood with cold clarity, was the one thing that would make the grove stop being patient." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 25.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered again (whisper)" |
| | dialogueSentences | 4 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0.25 | | effectiveRatio | 0.25 | |