| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "Callum said quietly [quietly]" |
| | dialogueSentences | 64 | | tagDensity | 0.203 | | leniency | 0.406 | | rawRatio | 0.077 | | effectiveRatio | 0.031 | |
| 92.34% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1305 | | totalAiIsmAdverbs | 2 | | 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) | |
| 69.35% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1305 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "electric" | | 1 | "silence" | | 2 | "etched" | | 3 | "weight" | | 4 | "silk" | | 5 | "unreadable" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "let out a breath" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "let out a breath" | | 1 | "hung in the air" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 82 | | matches | | 0 | "looked sad" | | 1 | "was bitter" |
| |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 82 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 133 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1299 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 801 | | uniqueNames | 6 | | maxNameDensity | 1.5 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Callum" | | discoveredNames | | Rory | 12 | | Raven | 1 | | Nest | 1 | | Silas | 12 | | Cardiff | 1 | | Callum | 8 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Silas" | | 3 | "Callum" |
| | places | | | globalScore | 0.751 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 1 | | matches | | 0 | "as if expecting her to vanish" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1299 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 133 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 73 | | mean | 17.79 | | std | 14.36 | | cv | 0.807 | | sampleLengths | | 0 | 57 | | 1 | 32 | | 2 | 11 | | 3 | 27 | | 4 | 8 | | 5 | 22 | | 6 | 48 | | 7 | 34 | | 8 | 3 | | 9 | 37 | | 10 | 30 | | 11 | 6 | | 12 | 1 | | 13 | 23 | | 14 | 2 | | 15 | 68 | | 16 | 21 | | 17 | 2 | | 18 | 18 | | 19 | 24 | | 20 | 2 | | 21 | 60 | | 22 | 3 | | 23 | 13 | | 24 | 17 | | 25 | 11 | | 26 | 11 | | 27 | 7 | | 28 | 20 | | 29 | 7 | | 30 | 8 | | 31 | 21 | | 32 | 15 | | 33 | 9 | | 34 | 2 | | 35 | 29 | | 36 | 3 | | 37 | 27 | | 38 | 28 | | 39 | 13 | | 40 | 18 | | 41 | 6 | | 42 | 3 | | 43 | 33 | | 44 | 14 | | 45 | 7 | | 46 | 19 | | 47 | 2 | | 48 | 28 | | 49 | 3 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 82 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 147 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 133 | | ratio | 0.008 | | matches | | 0 | "It was deeper than she remembered, roughened by time or cigarettes, but the cadence—the specific way he rounded his vowels—was unmistakable." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 805 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.02732919254658385 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.011180124223602485 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 133 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 133 | | mean | 9.77 | | std | 5.98 | | cv | 0.612 | | sampleLengths | | 0 | 20 | | 1 | 15 | | 2 | 22 | | 3 | 10 | | 4 | 5 | | 5 | 17 | | 6 | 11 | | 7 | 8 | | 8 | 19 | | 9 | 8 | | 10 | 9 | | 11 | 13 | | 12 | 6 | | 13 | 15 | | 14 | 13 | | 15 | 14 | | 16 | 10 | | 17 | 16 | | 18 | 8 | | 19 | 3 | | 20 | 8 | | 21 | 21 | | 22 | 8 | | 23 | 9 | | 24 | 10 | | 25 | 11 | | 26 | 6 | | 27 | 1 | | 28 | 9 | | 29 | 7 | | 30 | 3 | | 31 | 4 | | 32 | 2 | | 33 | 11 | | 34 | 3 | | 35 | 19 | | 36 | 35 | | 37 | 15 | | 38 | 6 | | 39 | 2 | | 40 | 18 | | 41 | 10 | | 42 | 9 | | 43 | 5 | | 44 | 2 | | 45 | 11 | | 46 | 5 | | 47 | 16 | | 48 | 18 | | 49 | 3 |
| |
| 48.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.3308270676691729 | | totalSentences | 133 | | uniqueOpeners | 44 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 52.10% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 81 | | matches | | 0 | "She leaned against the polished" | | 1 | "His movements were precise, practiced." | | 2 | "She signaled for another drink" | | 3 | "He wore a trench coat," | | 4 | "He smelled of stale rain" | | 5 | "It was deeper than she" | | 6 | "She froze, her hand tightening" | | 7 | "She forced herself to breathe," | | 8 | "She hadn't heard that name" | | 9 | "He looked older." | | 10 | "His hair was shorter, styled" | | 11 | "He blinked, as if expecting" | | 12 | "He set the glass down" | | 13 | "He shifted his weight, looking" | | 14 | "She knew what he saw." | | 15 | "He noticed it." | | 16 | "His eyes lingered on the" | | 17 | "He corrected her automatically, a" | | 18 | "He laughed, a short, dry" | | 19 | "He gestured at her clothes" |
| | ratio | 0.42 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 81 | | matches | | 0 | "The green neon sign above" | | 1 | "She leaned against the polished" | | 2 | "The Raven's Nest was quiet," | | 3 | "Silas stood opposite her, drying" | | 4 | "His movements were precise, practiced." | | 5 | "The silver signet ring on" | | 6 | "Rory scoffed, turning her coaster" | | 7 | "She signaled for another drink" | | 8 | "Silas grabbed a bottle of" | | 9 | "The heavy oak door creaked" | | 10 | "A gust of wind whipped" | | 11 | "Rory didn't look up immediately," | | 12 | "Silas paused, his eyes narrowing" | | 13 | "A man stepped to the" | | 14 | "He wore a trench coat," | | 15 | "He smelled of stale rain" | | 16 | "The voice hit Rory like" | | 17 | "It was deeper than she" | | 18 | "She froze, her hand tightening" | | 19 | "Silas poured the drink, sliding" |
| | ratio | 0.963 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 4 | | matches | | 0 | "He blinked, as if expecting her to vanish" | | 1 | "She picked up, the ice clinking softly" | | 2 | "Callum turned, his searching" | | 3 | "Silas said, his voice low and gravelly" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | 0 | "He corrected (correct)" |
| | dialogueSentences | 64 | | tagDensity | 0.063 | | leniency | 0.125 | | rawRatio | 0.25 | | effectiveRatio | 0.031 | |