| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 1 | | adverbTags | | 0 | "Martin said finally [finally]" |
| | dialogueSentences | 55 | | tagDensity | 0.382 | | leniency | 0.764 | | rawRatio | 0.048 | | effectiveRatio | 0.036 | |
| 95.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1196 | | 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) | |
| 66.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1196 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "eyebrow" | | 1 | "scanned" | | 2 | "stomach" | | 3 | "silence" | | 4 | "traced" | | 5 | "weight" |
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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 | 94 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 94 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 125 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1196 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 25 | | unquotedAttributions | 0 | | matches | (empty) | |
| 44.21% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 51 | | wordCount | 898 | | uniqueNames | 10 | | maxNameDensity | 2.12 | | worstName | "Silas" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Silas" | | discoveredNames | | Rory | 11 | | Raven | 1 | | Nest | 1 | | Silas | 19 | | Martin | 14 | | Golden | 1 | | Empress | 1 | | Cardiff | 1 | | Vauxhall | 1 | | Thames | 1 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Silas" | | 3 | "Martin" |
| | places | | 0 | "Cardiff" | | 1 | "Vauxhall" | | 2 | "Thames" |
| | globalScore | 0.442 | | windowScore | 0.5 | |
| 57.41% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like he'd been sleeping in his goo" | | 1 | "Not quite grief, not quite blame" | | 2 | "not quite blame" |
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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 | 1196 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 125 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 75 | | mean | 15.95 | | std | 16.75 | | cv | 1.05 | | sampleLengths | | 0 | 61 | | 1 | 7 | | 2 | 84 | | 3 | 13 | | 4 | 8 | | 5 | 40 | | 6 | 27 | | 7 | 1 | | 8 | 1 | | 9 | 24 | | 10 | 6 | | 11 | 5 | | 12 | 4 | | 13 | 3 | | 14 | 48 | | 15 | 5 | | 16 | 25 | | 17 | 6 | | 18 | 15 | | 19 | 12 | | 20 | 6 | | 21 | 20 | | 22 | 37 | | 23 | 5 | | 24 | 3 | | 25 | 4 | | 26 | 4 | | 27 | 21 | | 28 | 6 | | 29 | 3 | | 30 | 7 | | 31 | 22 | | 32 | 3 | | 33 | 8 | | 34 | 7 | | 35 | 42 | | 36 | 22 | | 37 | 3 | | 38 | 11 | | 39 | 6 | | 40 | 5 | | 41 | 54 | | 42 | 5 | | 43 | 5 | | 44 | 41 | | 45 | 5 | | 46 | 1 | | 47 | 6 | | 48 | 9 | | 49 | 26 |
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| 94.06% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 94 | | matches | | 0 | "been turned" | | 1 | "was composed" | | 2 | "been carried" |
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| 79.52% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 166 | | matches | | 0 | "was watching" | | 1 | "was just having" | | 2 | "was still trying" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 125 | | ratio | 0 | | matches | (empty) | |
| 93.15% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 903 | | adjectiveStacks | 1 | | stackExamples | | 0 | "close-cropped silver hair" |
| | adverbCount | 37 | | adverbRatio | 0.04097452934662237 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.01107419712070875 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 125 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 125 | | mean | 9.57 | | std | 8.16 | | cv | 0.853 | | sampleLengths | | 0 | 3 | | 1 | 45 | | 2 | 13 | | 3 | 7 | | 4 | 16 | | 5 | 3 | | 6 | 4 | | 7 | 3 | | 8 | 8 | | 9 | 29 | | 10 | 21 | | 11 | 9 | | 12 | 4 | | 13 | 8 | | 14 | 13 | | 15 | 20 | | 16 | 7 | | 17 | 27 | | 18 | 1 | | 19 | 1 | | 20 | 6 | | 21 | 18 | | 22 | 6 | | 23 | 5 | | 24 | 4 | | 25 | 3 | | 26 | 11 | | 27 | 3 | | 28 | 25 | | 29 | 9 | | 30 | 5 | | 31 | 25 | | 32 | 4 | | 33 | 2 | | 34 | 5 | | 35 | 2 | | 36 | 4 | | 37 | 4 | | 38 | 8 | | 39 | 2 | | 40 | 2 | | 41 | 6 | | 42 | 10 | | 43 | 10 | | 44 | 12 | | 45 | 6 | | 46 | 19 | | 47 | 5 | | 48 | 3 | | 49 | 4 |
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| 63.47% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.448 | | totalSentences | 125 | | uniqueOpeners | 56 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 78 | | matches | | 0 | "More like worn through." | | 1 | "Expensively worn through." | | 2 | "Then he saw Silas, and" | | 3 | "More like the particular wariness" | | 4 | "Again that silence, but a" |
| | ratio | 0.064 | |
| 91.79% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 78 | | matches | | 0 | "She tracked his gaze toward" | | 1 | "He was around Silas's age," | | 2 | "He scanned the bar the" | | 3 | "He came around the bar," | | 4 | "He stopped two paces from" | | 5 | "She heard the bar stools" | | 6 | "She didn't look." | | 7 | "She studied the grain of" | | 8 | "She'd got good at becoming" | | 9 | "His face in profile was" | | 10 | "She'd told herself she was" | | 11 | "She'd told herself whatever happened" | | 12 | "She'd told herself a lot" | | 13 | "She turned on her stool." | | 14 | "His eyes were clear grey" | | 15 | "he asked Silas" | | 16 | "he told Silas" | | 17 | "He shook his head" | | 18 | "He set the glass down" | | 19 | "She thought about what it" |
| | ratio | 0.321 | |
| 56.15% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 78 | | matches | | 0 | "Silas rarely froze." | | 1 | "She tracked his gaze toward" | | 2 | "The man who entered looked" | | 3 | "Charcoal wool, good cut, the" | | 4 | "He was around Silas's age," | | 5 | "He scanned the bar the" | | 6 | "Rory said before she could" | | 7 | "Silas set the glass down" | | 8 | "He came around the bar," | | 9 | "He stopped two paces from" | | 10 | "These two old men stared" | | 11 | "That was all for a" | | 12 | "The jazz record Silas kept" | | 13 | "Rory turned back to her" | | 14 | "She heard the bar stools" | | 15 | "She didn't look." | | 16 | "She studied the grain of" | | 17 | "She'd got good at becoming" | | 18 | "Martin's voice was flat" | | 19 | "That made it worse." |
| | ratio | 0.808 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 78 | | matches | (empty) | | ratio | 0 | |
| 19.70% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 5 | | matches | | 0 | "In the months Rory had lived above The Raven's Nest, she'd watched him handle drunken brawlers, bad debts, and once a man who'd arrived with what she later lear…" | | 1 | "He was around Silas's age, maybe a few years younger, with close-cropped silver hair and the kind of weathered jaw that spoke of a life spent squinting at horiz…" | | 2 | "These two old men stared at each other like dogs who'd grown up in the same house and spent a decade on opposite sides of a fence." | | 3 | "Something older, the kind that had been turned over so many times it had gone smooth, like sea glass." | | 4 | "More like the particular wariness of someone who had spent too long around people who weaponised honesty." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 55 | | tagDensity | 0.291 | | leniency | 0.582 | | rawRatio | 0 | | effectiveRatio | 0 | |