| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 125 | | tagDensity | 0.112 | | leniency | 0.224 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.61% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2781 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "really" | | 1 | "softly" | | 2 | "very" |
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| 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) | |
| 85.62% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2781 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "flicked" | | 1 | "silence" | | 2 | "efficient" | | 3 | "weight" | | 4 | "flicker" | | 5 | "familiar" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 2 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 200 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 200 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 311 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 76 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2781 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 24 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 113 | | wordCount | 1734 | | uniqueNames | 6 | | maxNameDensity | 3.17 | | worstName | "Aurora" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Aurora" | | discoveredNames | | Raven | 1 | | Nest | 3 | | Silas | 10 | | Aurora | 55 | | Nia | 43 | | Cardiff | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Aurora" | | 4 | "Nia" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 125 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like it knew things" |
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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 | 2781 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 311 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 225 | | mean | 12.36 | | std | 15.25 | | cv | 1.234 | | sampleLengths | | 0 | 72 | | 1 | 42 | | 2 | 31 | | 3 | 6 | | 4 | 10 | | 5 | 10 | | 6 | 7 | | 7 | 20 | | 8 | 5 | | 9 | 58 | | 10 | 19 | | 11 | 74 | | 12 | 18 | | 13 | 6 | | 14 | 9 | | 15 | 1 | | 16 | 15 | | 17 | 2 | | 18 | 1 | | 19 | 23 | | 20 | 4 | | 21 | 11 | | 22 | 7 | | 23 | 80 | | 24 | 7 | | 25 | 7 | | 26 | 5 | | 27 | 7 | | 28 | 6 | | 29 | 22 | | 30 | 20 | | 31 | 27 | | 32 | 6 | | 33 | 10 | | 34 | 2 | | 35 | 9 | | 36 | 10 | | 37 | 17 | | 38 | 6 | | 39 | 1 | | 40 | 7 | | 41 | 18 | | 42 | 9 | | 43 | 7 | | 44 | 13 | | 45 | 6 | | 46 | 3 | | 47 | 12 | | 48 | 10 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 200 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 299 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 311 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1737 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 63 | | adverbRatio | 0.03626943005181347 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.0051813471502590676 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 311 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 311 | | mean | 8.94 | | std | 8.35 | | cv | 0.933 | | sampleLengths | | 0 | 21 | | 1 | 28 | | 2 | 23 | | 3 | 9 | | 4 | 8 | | 5 | 10 | | 6 | 15 | | 7 | 7 | | 8 | 24 | | 9 | 6 | | 10 | 10 | | 11 | 10 | | 12 | 7 | | 13 | 20 | | 14 | 5 | | 15 | 17 | | 16 | 6 | | 17 | 5 | | 18 | 4 | | 19 | 6 | | 20 | 2 | | 21 | 18 | | 22 | 19 | | 23 | 11 | | 24 | 10 | | 25 | 6 | | 26 | 17 | | 27 | 4 | | 28 | 13 | | 29 | 13 | | 30 | 18 | | 31 | 6 | | 32 | 9 | | 33 | 1 | | 34 | 15 | | 35 | 2 | | 36 | 1 | | 37 | 6 | | 38 | 17 | | 39 | 4 | | 40 | 11 | | 41 | 7 | | 42 | 2 | | 43 | 16 | | 44 | 26 | | 45 | 8 | | 46 | 6 | | 47 | 8 | | 48 | 2 | | 49 | 8 |
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| 45.50% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.22508038585209003 | | totalSentences | 311 | | uniqueOpeners | 70 | |
| 57.80% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 173 | | matches | | 0 | "Then the woman lifted her" | | 1 | "Somewhere a bottle knocked another" | | 2 | "Then she drew her hand" |
| | ratio | 0.017 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 173 | | matches | | 0 | "His hazel eyes swept over" | | 1 | "She rubbed rain from her" | | 2 | "Her gaze snagged on a" | | 3 | "Her face had narrowed." | | 4 | "Her mouth looked as if" | | 5 | "She had the sort of" | | 6 | "He glanced from one of" | | 7 | "She had been shorter than" | | 8 | "Her eyes were the same," | | 9 | "They used to dart ahead" | | 10 | "He had already turned away," | | 11 | "They stood with the table" | | 12 | "She had done it since" | | 13 | "Her mother used to catch" | | 14 | "It’ll only open again." | | 15 | "Her right hand bore the" | | 16 | "She looked at the pale" | | 17 | "It flashed and was gone," | | 18 | "It came out stripped bare." | | 19 | "she went on" |
| | ratio | 0.179 | |
| 17.80% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 153 | | totalSentences | 173 | | matches | | 0 | "The green neon above The" | | 1 | "Aurora ducked in under it" | | 2 | "The bar smelled of beer," | | 3 | "A low record crackled behind" | | 4 | "Maps curled on the walls" | | 5 | "A man at the far" | | 6 | "A couple leaned over a" | | 7 | "Silas looked up from drying" | | 8 | "His hazel eyes swept over" | | 9 | "Aurora dropped the bag on" | | 10 | "Silas slid a towel across" | | 11 | "She rubbed rain from her" | | 12 | "The Nest always arrived in" | | 13 | "The dark sheen of old" | | 14 | "Strangers, regulars, tourists who walked" | | 15 | "Her gaze snagged on a" | | 16 | "The woman sat alone with" | | 17 | "A pale hand around the" | | 18 | "Hair cut shorter than fashion" | | 19 | "Her face had narrowed." |
| | ratio | 0.884 | |
| 57.80% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 173 | | matches | | 0 | "Now she matched her eye" | | 1 | "Now they held still." |
| | ratio | 0.012 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 68 | | technicalSentenceCount | 2 | | matches | | 0 | "Now she matched her eye line in heeled boots and wore a charcoal jumper that looked expensive in a way that tried not to look expensive." | | 1 | "Outside, people passed under umbrellas that looked black under the neon." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 125 | | tagDensity | 0.104 | | leniency | 0.208 | | rawRatio | 0.077 | | effectiveRatio | 0.016 | |