| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva’s gaze sharpened briefly [briefly]" |
| | dialogueSentences | 194 | | tagDensity | 0.088 | | leniency | 0.175 | | rawRatio | 0.059 | | effectiveRatio | 0.01 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2289 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 95.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2289 | | totalAiIsms | 2 | | found | | | highlights | | |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 120 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 120 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 297 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2288 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 46 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 87 | | wordCount | 1098 | | uniqueNames | 6 | | maxNameDensity | 3.46 | | worstName | "Aurora" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Aurora" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Aurora | 38 | | Carter | 1 | | Silas | 15 | | Eva | 31 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Aurora" | | 3 | "Carter" | | 4 | "Silas" | | 5 | "Eva" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 79 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.437 | | wordCount | 2288 | | matches | | 0 | "not from the grey at her temples but from the effort of keeping herself upright" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 297 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 213 | | mean | 10.74 | | std | 11.49 | | cv | 1.069 | | sampleLengths | | 0 | 44 | | 1 | 42 | | 2 | 9 | | 3 | 13 | | 4 | 48 | | 5 | 6 | | 6 | 3 | | 7 | 20 | | 8 | 8 | | 9 | 11 | | 10 | 62 | | 11 | 4 | | 12 | 12 | | 13 | 31 | | 14 | 4 | | 15 | 1 | | 16 | 34 | | 17 | 1 | | 18 | 58 | | 19 | 6 | | 20 | 7 | | 21 | 4 | | 22 | 16 | | 23 | 3 | | 24 | 5 | | 25 | 11 | | 26 | 3 | | 27 | 10 | | 28 | 11 | | 29 | 14 | | 30 | 32 | | 31 | 13 | | 32 | 19 | | 33 | 4 | | 34 | 6 | | 35 | 12 | | 36 | 24 | | 37 | 2 | | 38 | 7 | | 39 | 5 | | 40 | 5 | | 41 | 14 | | 42 | 14 | | 43 | 10 | | 44 | 46 | | 45 | 2 | | 46 | 6 | | 47 | 8 | | 48 | 8 | | 49 | 3 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 120 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 185 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 297 | | ratio | 0.003 | | matches | | 0 | "Eva looked at her, and for a second the years fell away—not enough to make either of them younger, only enough to show the old argument beneath the new clothes." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1104 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 38 | | adverbRatio | 0.034420289855072464 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0036231884057971015 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 297 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 297 | | mean | 7.7 | | std | 6.64 | | cv | 0.862 | | sampleLengths | | 0 | 17 | | 1 | 27 | | 2 | 7 | | 3 | 27 | | 4 | 8 | | 5 | 9 | | 6 | 13 | | 7 | 7 | | 8 | 20 | | 9 | 16 | | 10 | 5 | | 11 | 6 | | 12 | 3 | | 13 | 18 | | 14 | 2 | | 15 | 8 | | 16 | 11 | | 17 | 5 | | 18 | 11 | | 19 | 17 | | 20 | 13 | | 21 | 16 | | 22 | 4 | | 23 | 12 | | 24 | 31 | | 25 | 4 | | 26 | 1 | | 27 | 26 | | 28 | 8 | | 29 | 1 | | 30 | 14 | | 31 | 18 | | 32 | 6 | | 33 | 20 | | 34 | 6 | | 35 | 4 | | 36 | 3 | | 37 | 4 | | 38 | 12 | | 39 | 4 | | 40 | 3 | | 41 | 3 | | 42 | 2 | | 43 | 6 | | 44 | 5 | | 45 | 3 | | 46 | 7 | | 47 | 3 | | 48 | 11 | | 49 | 9 |
| |
| 42.93% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 21 | | diversityRatio | 0.23905723905723905 | | totalSentences | 297 | | uniqueOpeners | 71 | |
| 93.46% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 107 | | matches | | 0 | "Somewhere behind the counter, a" | | 1 | "Then the woman stood." | | 2 | "Then she climbed the narrow" |
| | ratio | 0.028 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 107 | | matches | | 0 | "He had learnt to put" | | 1 | "He lifted the lid, checked" | | 2 | "Her dark hair was cut" | | 3 | "She had not heard it" | | 4 | "Her old schoolgirl softness had" | | 5 | "He limped towards the bookshelf" | | 6 | "His glance passed over Aurora" | | 7 | "He didn’t ask what the" | | 8 | "It showed where her sleeve" | | 9 | "It tasted faintly of metal." | | 10 | "She rubbed her thumb along" | | 11 | "Their coats brushed against the" | | 12 | "He wiped down the counter" | | 13 | "She looked older then, not" | | 14 | "She didn’t reach across the" | | 15 | "His ring tapped the metal" | | 16 | "She had seen it a" | | 17 | "They sat with the gap" | | 18 | "She almost smiled." |
| | ratio | 0.178 | |
| 6.73% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 97 | | totalSentences | 107 | | matches | | 0 | "The green neon sign above" | | 1 | "Rain came down in fine," | | 2 | "The bar held its usual" | | 3 | "Aurora set the bag on" | | 4 | "Silas stood behind it, his" | | 5 | "He had learnt to put" | | 6 | "Tonight the limp showed anyway." | | 7 | "He lifted the lid, checked" | | 8 | "Aurora glanced at the room." | | 9 | "A woman sat alone near" | | 10 | "Her dark hair was cut" | | 11 | "A leather jacket lay over" | | 12 | "The woman looked up." | | 13 | "Aurora stopped with one hand" | | 14 | "Aurora had heard that voice" | | 15 | "She had not heard it" | | 16 | "Eva’s mouth moved as though" | | 17 | "Her old schoolgirl softness had" | | 18 | "Eva glanced at it." | | 19 | "Eva tipped her glass, though" |
| | ratio | 0.907 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 107 | | matches | (empty) | | ratio | 0 | |
| 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 | 17 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 3 | | fancyTags | | 0 | "Eva agreed (agree)" | | 1 | "Eva continued (continue)" | | 2 | "Eva pressed (press)" |
| | dialogueSentences | 194 | | tagDensity | 0.067 | | leniency | 0.134 | | rawRatio | 0.231 | | effectiveRatio | 0.031 | |