| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 2 | | adverbTags | | 0 | "Aurora gestured vaguely [vaguely]" | | 1 | "Silas leaned back [back]" |
| | dialogueSentences | 53 | | tagDensity | 0.377 | | leniency | 0.755 | | rawRatio | 0.1 | | effectiveRatio | 0.075 | |
| 92.75% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1379 | | totalAiIsmAdverbs | 2 | | 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) | |
| 63.74% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1379 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "solitary" | | 1 | "chill" | | 2 | "traced" | | 3 | "scanning" | | 4 | "etched" | | 5 | "familiar" | | 6 | "warmth" | | 7 | "silk" | | 8 | "weight" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 62 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 62 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1379 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 803 | | uniqueNames | 10 | | maxNameDensity | 1.62 | | worstName | "Evan" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Evan" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | London | 2 | | Cardiff | 1 | | Evan | 13 | | Aurora | 10 | | South | 1 | | Wales | 1 | | Silas | 12 |
| | persons | | | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "London" | | 3 | "Cardiff" | | 4 | "South" | | 5 | "Wales" |
| | globalScore | 0.691 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | 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 | 1379 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 29.34 | | std | 18.87 | | cv | 0.643 | | sampleLengths | | 0 | 82 | | 1 | 69 | | 2 | 22 | | 3 | 44 | | 4 | 1 | | 5 | 16 | | 6 | 13 | | 7 | 44 | | 8 | 5 | | 9 | 13 | | 10 | 5 | | 11 | 65 | | 12 | 6 | | 13 | 52 | | 14 | 35 | | 15 | 38 | | 16 | 20 | | 17 | 41 | | 18 | 5 | | 19 | 29 | | 20 | 33 | | 21 | 10 | | 22 | 39 | | 23 | 7 | | 24 | 46 | | 25 | 15 | | 26 | 41 | | 27 | 53 | | 28 | 6 | | 29 | 23 | | 30 | 39 | | 31 | 34 | | 32 | 24 | | 33 | 26 | | 34 | 55 | | 35 | 13 | | 36 | 25 | | 37 | 30 | | 38 | 4 | | 39 | 49 | | 40 | 13 | | 41 | 40 | | 42 | 23 | | 43 | 28 | | 44 | 25 | | 45 | 20 | | 46 | 53 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 62 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 123 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 95 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 808 | | adjectiveStacks | 1 | | stackExamples | | 0 | "faint crescent-shaped scar" |
| | adverbCount | 13 | | adverbRatio | 0.01608910891089109 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.009900990099009901 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 14.52 | | std | 6.6 | | cv | 0.455 | | sampleLengths | | 0 | 17 | | 1 | 19 | | 2 | 13 | | 3 | 18 | | 4 | 15 | | 5 | 17 | | 6 | 18 | | 7 | 22 | | 8 | 12 | | 9 | 8 | | 10 | 14 | | 11 | 17 | | 12 | 12 | | 13 | 15 | | 14 | 1 | | 15 | 9 | | 16 | 7 | | 17 | 13 | | 18 | 22 | | 19 | 14 | | 20 | 8 | | 21 | 5 | | 22 | 13 | | 23 | 5 | | 24 | 11 | | 25 | 16 | | 26 | 38 | | 27 | 6 | | 28 | 15 | | 29 | 19 | | 30 | 18 | | 31 | 15 | | 32 | 20 | | 33 | 21 | | 34 | 17 | | 35 | 20 | | 36 | 15 | | 37 | 26 | | 38 | 5 | | 39 | 12 | | 40 | 17 | | 41 | 16 | | 42 | 17 | | 43 | 10 | | 44 | 10 | | 45 | 12 | | 46 | 17 | | 47 | 7 | | 48 | 9 | | 49 | 13 |
| |
| 54.74% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.37894736842105264 | | totalSentences | 95 | | uniqueOpeners | 36 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 62 | | matches | | 0 | "He tossed a fresh beer" | | 1 | "She traced the rim with" | | 2 | "He paused, scanning the tavern" | | 3 | "He unbuttoned his coat, revealing" | | 4 | "His hazel eyes searched her" | | 5 | "He dismissed the accusation with" | | 6 | "He adjusted his cuffs, his" | | 7 | "He didn't raise his voice," | | 8 | "His hazel eyes remained locked" | | 9 | "He turned on his heel" | | 10 | "He walked over, set the" | | 11 | "He lowered himself onto the" | | 12 | "she whispered, her voice cracking" | | 13 | "He picked up her empty" |
| | ratio | 0.226 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 62 | | matches | | 0 | "The green neon sign above" | | 1 | "Maps of forgotten continents and" | | 2 | "Silas dragged his left leg" | | 3 | "He tossed a fresh beer" | | 4 | "Aurora pulled the collar of" | | 5 | "A faint crescent-shaped scar on" | | 6 | "She traced the rim with" | | 7 | "The brass bell above the" | | 8 | "A gust of wet London" | | 9 | "A man stepped out of" | | 10 | "He paused, scanning the tavern" | | 11 | "Evan dropped his leather briefcase" | | 12 | "The polished leather scuffed against" | | 13 | "Aurora froze, her fingers tightening" | | 14 | "Evan slid into the opposite" | | 15 | "The familiar scent of sandalwood" | | 16 | "Evan chuckled, a low, smooth" | | 17 | "He unbuttoned his coat, revealing" | | 18 | "Evan leaned forward, resting forearms" | | 19 | "His hazel eyes searched her" |
| | ratio | 0.952 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 2 | | matches | | 0 | "Grey-streaked auburn hair framed a face etched with lines that hadn't existed back in Cardiff." | | 1 | "Silas stopped wiping the counter, his hand sliding instinctively toward the heavy timber beneath the cash register." |
| |
| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 4 | | matches | | 0 | "Evan reached, his palm resting flat near her glass" | | 1 | "Silas said, his voice gravelly and quiet" | | 2 | "she whispered, her voice cracking for the first time" | | 3 | "Silas stood up, his knee clicking as he straightened his frame" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 53 | | tagDensity | 0.038 | | leniency | 0.075 | | rawRatio | 0.5 | | effectiveRatio | 0.038 | |