| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 68 | | tagDensity | 0.294 | | leniency | 0.588 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.48% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1422 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 92.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1422 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 63 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 63 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1414 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 845 | | uniqueNames | 9 | | maxNameDensity | 1.78 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 15 | | Pimlico | 1 | | Wardour | 1 | | Street | 1 | | Raven | 1 | | Nest | 1 | | November | 1 | | Silas | 5 | | Carys | 15 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Silas" | | 3 | "Carys" |
| | places | | 0 | "Pimlico" | | 1 | "Wardour" | | 2 | "Street" |
| | globalScore | 0.612 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | 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 | 1414 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 68 | | mean | 20.79 | | std | 18.83 | | cv | 0.906 | | sampleLengths | | 0 | 64 | | 1 | 67 | | 2 | 6 | | 3 | 16 | | 4 | 41 | | 5 | 6 | | 6 | 6 | | 7 | 26 | | 8 | 60 | | 9 | 1 | | 10 | 8 | | 11 | 2 | | 12 | 25 | | 13 | 20 | | 14 | 5 | | 15 | 15 | | 16 | 21 | | 17 | 16 | | 18 | 66 | | 19 | 4 | | 20 | 3 | | 21 | 39 | | 22 | 11 | | 23 | 40 | | 24 | 3 | | 25 | 3 | | 26 | 11 | | 27 | 2 | | 28 | 15 | | 29 | 34 | | 30 | 4 | | 31 | 8 | | 32 | 5 | | 33 | 28 | | 34 | 8 | | 35 | 83 | | 36 | 11 | | 37 | 25 | | 38 | 9 | | 39 | 56 | | 40 | 5 | | 41 | 13 | | 42 | 8 | | 43 | 6 | | 44 | 18 | | 45 | 48 | | 46 | 15 | | 47 | 42 | | 48 | 23 | | 49 | 4 |
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| 94.12% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 63 | | matches | | 0 | "was gone" | | 1 | "was plastered" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 140 | | matches | (empty) | |
| 64.94% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 110 | | ratio | 0.027 | | matches | | 0 | "Carys laughed—one short note, surprised out of her—and that at least hadn't changed." | | 1 | "While she hung her coat on the stool, her gaze traveled the walls—the maps, the faces, the tall bookcase at the end of the room with a seam of light showing at its edge." | | 2 | "Carys reached across and took her hand—no announcement, the way they used to share armrests—and turned it over in the lamp glow." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 852 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.015258215962441314 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0011737089201877935 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 12.85 | | std | 9.55 | | cv | 0.743 | | sampleLengths | | 0 | 9 | | 1 | 27 | | 2 | 28 | | 3 | 15 | | 4 | 26 | | 5 | 26 | | 6 | 6 | | 7 | 11 | | 8 | 5 | | 9 | 30 | | 10 | 7 | | 11 | 4 | | 12 | 6 | | 13 | 6 | | 14 | 11 | | 15 | 15 | | 16 | 16 | | 17 | 6 | | 18 | 2 | | 19 | 6 | | 20 | 30 | | 21 | 1 | | 22 | 8 | | 23 | 2 | | 24 | 25 | | 25 | 20 | | 26 | 5 | | 27 | 12 | | 28 | 3 | | 29 | 9 | | 30 | 12 | | 31 | 14 | | 32 | 2 | | 33 | 13 | | 34 | 3 | | 35 | 19 | | 36 | 31 | | 37 | 4 | | 38 | 3 | | 39 | 6 | | 40 | 24 | | 41 | 9 | | 42 | 10 | | 43 | 1 | | 44 | 30 | | 45 | 10 | | 46 | 3 | | 47 | 3 | | 48 | 7 | | 49 | 4 |
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| 63.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.41818181818181815 | | totalSentences | 110 | | uniqueOpeners | 46 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 61 | | matches | | 0 | "She rang the coins out" | | 1 | "He limped over, took a" | | 2 | "His signet ring clicked against" | | 3 | "She got two swallows down" | | 4 | "She scanned the room the" | | 5 | "Her mouth did something that" | | 6 | "He and Rory answered together," | | 7 | "She turned her glass by" | | 8 | "She stopped, started again" | | 9 | "Her thumb circled the base" | | 10 | "She absorbed that with a" | | 11 | "Her thumb settled on the" | | 12 | "Her thumb didn't move off" | | 13 | "She gave the hand back" | | 14 | "he told the room, and" | | 15 | "She wrote across the back" |
| | ratio | 0.262 | |
| 25.57% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 53 | | totalSentences | 61 | | matches | | 0 | "Rain had followed Rory all" | | 1 | "The last delivery of the" | | 2 | "Silas stood at the far" | | 3 | "She rang the coins out" | | 4 | "He limped over, took a" | | 5 | "His signet ring clicked against" | | 6 | "The whiskey tasted of woodsmoke" | | 7 | "She got two swallows down" | | 8 | "A woman stood on the" | | 9 | "Hair cut sharp to the" | | 10 | "A phone dying in one" | | 11 | "She scanned the room the" | | 12 | "Rory set her glass down" | | 13 | "Carys crossed the floor with" | | 14 | "Her mouth did something that" | | 15 | "Silas drew a second glass" | | 16 | "Rory pushed the neighboring stool" | | 17 | "Carys laughed—one short note, surprised" | | 18 | "The rest had." | | 19 | "The woman folding herself onto" |
| | ratio | 0.869 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 61 | | matches | | 0 | "By the time she wheeled" | | 1 | "While she hung her coat" |
| | ratio | 0.033 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 1 | | matches | | 0 | "She scanned the room the way people scan rooms when a hotel room is the alternative, and her gaze crossed the bar and stopped as if it had hit glass." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 68 | | tagDensity | 0.044 | | leniency | 0.088 | | rawRatio | 0.333 | | effectiveRatio | 0.029 | |