| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 166 | | tagDensity | 0.06 | | leniency | 0.12 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.43% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1942 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 79.40% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1942 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "flickered" | | 1 | "eyebrow" | | 2 | "affection" | | 3 | "warmth" | | 4 | "stomach" | | 5 | "silk" | | 6 | "silence" | | 7 | "pulse" |
| |
| 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 | 1 | | narrationSentences | 131 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 131 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 287 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1942 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 30 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 87 | | wordCount | 1109 | | uniqueNames | 6 | | maxNameDensity | 3.52 | | worstName | "Eva" | | maxWindowNameDensity | 7 | | worstWindowName | "Eva" | | discoveredNames | | Nest | 2 | | Aurora | 32 | | London | 1 | | Eva | 39 | | Silas | 11 | | Cardiff | 2 |
| | persons | | | places | | 0 | "Nest" | | 1 | "London" | | 2 | "Cardiff" |
| | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | 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 | 1942 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 287 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 210 | | mean | 9.25 | | std | 11.22 | | cv | 1.213 | | sampleLengths | | 0 | 21 | | 1 | 65 | | 2 | 4 | | 3 | 5 | | 4 | 6 | | 5 | 14 | | 6 | 44 | | 7 | 8 | | 8 | 3 | | 9 | 3 | | 10 | 26 | | 11 | 7 | | 12 | 63 | | 13 | 6 | | 14 | 4 | | 15 | 5 | | 16 | 1 | | 17 | 11 | | 18 | 6 | | 19 | 14 | | 20 | 3 | | 21 | 7 | | 22 | 34 | | 23 | 12 | | 24 | 53 | | 25 | 9 | | 26 | 6 | | 27 | 12 | | 28 | 5 | | 29 | 3 | | 30 | 4 | | 31 | 5 | | 32 | 15 | | 33 | 2 | | 34 | 2 | | 35 | 2 | | 36 | 5 | | 37 | 4 | | 38 | 6 | | 39 | 5 | | 40 | 8 | | 41 | 2 | | 42 | 4 | | 43 | 45 | | 44 | 6 | | 45 | 12 | | 46 | 37 | | 47 | 8 | | 48 | 2 | | 49 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 131 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 194 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 287 | | ratio | 0.003 | | matches | | 0 | "The old habit returned before she could prevent it: Eva chose the seat with her back to the wall; Aurora sat facing the door." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1116 | | adjectiveStacks | 1 | | stackExamples | | 0 | "blunt, silver-edged cut." |
| | adverbCount | 36 | | adverbRatio | 0.03225806451612903 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0008960573476702509 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 287 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 287 | | mean | 6.77 | | std | 5.82 | | cv | 0.86 | | sampleLengths | | 0 | 21 | | 1 | 16 | | 2 | 16 | | 3 | 16 | | 4 | 17 | | 5 | 4 | | 6 | 5 | | 7 | 6 | | 8 | 7 | | 9 | 7 | | 10 | 10 | | 11 | 17 | | 12 | 17 | | 13 | 8 | | 14 | 3 | | 15 | 3 | | 16 | 13 | | 17 | 13 | | 18 | 7 | | 19 | 18 | | 20 | 13 | | 21 | 8 | | 22 | 24 | | 23 | 6 | | 24 | 4 | | 25 | 5 | | 26 | 1 | | 27 | 11 | | 28 | 5 | | 29 | 1 | | 30 | 9 | | 31 | 5 | | 32 | 3 | | 33 | 4 | | 34 | 3 | | 35 | 27 | | 36 | 7 | | 37 | 7 | | 38 | 5 | | 39 | 6 | | 40 | 8 | | 41 | 11 | | 42 | 28 | | 43 | 9 | | 44 | 6 | | 45 | 12 | | 46 | 5 | | 47 | 3 | | 48 | 4 | | 49 | 5 |
| |
| 44.43% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.21254355400696864 | | totalSentences | 287 | | uniqueOpeners | 61 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 116 | | matches | | 0 | "Once, Eva had said them" | | 1 | "Of course you did." | | 2 | "Of course you slept through" | | 3 | "Of course you kissed the" | | 4 | "Of course you’d left the" | | 5 | "Instead, she reached for the" |
| | ratio | 0.052 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 116 | | matches | | 0 | "He had done that since" | | 1 | "His silver signet ring caught" | | 2 | "He poured whisky into a" | | 3 | "She folded the umbrella with" | | 4 | "Her coat fell to her" | | 5 | "Her hair, once a thick" | | 6 | "His hand stopped." | | 7 | "It burned down to her" | | 8 | "She draped the coat over" | | 9 | "He returned to the counter" | | 10 | "Its surface carried hundreds of" | | 11 | "She had said it too" | | 12 | "His expression stayed blank, but" | | 13 | "She covered it again." | | 14 | "He opened the small refrigerator" | | 15 | "They had done that in" | | 16 | "She picked up a fork," |
| | ratio | 0.147 | |
| 11.72% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 104 | | totalSentences | 116 | | matches | | 0 | "The green raven above the" | | 1 | "Aurora shoved the door with" | | 2 | "Water ran from the ends" | | 3 | "The bar smelled of wet" | | 4 | "Silas stood behind the counter," | | 5 | "Aurora set the crate beside" | | 6 | "Silas’s hazel eyes moved over" | | 7 | "He had done that since" | | 8 | "His silver signet ring caught" | | 9 | "He poured whisky into a" | | 10 | "Aurora took it, but the" | | 11 | "A woman entered beneath a" | | 12 | "She folded the umbrella with" | | 13 | "Her coat fell to her" | | 14 | "A thin gold chain rested" | | 15 | "Her hair, once a thick" | | 16 | "Aurora’s fingers closed around the" | | 17 | "The woman saw her." | | 18 | "The name struck with the" | | 19 | "Aurora put the tumbler down." |
| | ratio | 0.897 | |
| 86.21% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 116 | | matches | | 0 | "Now Eva wore a diamond" | | 1 | "Now the phrase landed without" |
| | ratio | 0.017 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 166 | | tagDensity | 0.06 | | leniency | 0.12 | | rawRatio | 0.1 | | effectiveRatio | 0.012 | |