| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 1 | | adverbTags | | 0 | "Silas said again [again]" |
| | dialogueSentences | 90 | | tagDensity | 0.244 | | leniency | 0.489 | | rawRatio | 0.045 | | effectiveRatio | 0.022 | |
| 93.29% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1491 | | 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) | |
| 53.05% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1491 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "gloom" | | 1 | "scanned" | | 2 | "crystal" | | 3 | "throbbed" | | 4 | "silence" | | 5 | "flickered" | | 6 | "weight" | | 7 | "familiar" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "weight of words/silence" | | count | 1 |
|
| | highlights | | 0 | "the weight of the silence" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 170 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 170 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 238 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1491 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 88 | | wordCount | 1094 | | uniqueNames | 15 | | maxNameDensity | 2.65 | | worstName | "Rory" | | maxWindowNameDensity | 5 | | worstWindowName | "Rory" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Carter | 1 | | Yu-Fei | 1 | | Cheung | 1 | | Silas | 19 | | Blackwood | 1 | | Rory | 29 | | Eva | 25 | | Golden | 1 | | Empress | 1 | | Cardiff | 2 | | Prague | 1 | | Aurora | 3 |
| | persons | | 0 | "Raven" | | 1 | "Carter" | | 2 | "Yu-Fei" | | 3 | "Cheung" | | 4 | "Silas" | | 5 | "Blackwood" | | 6 | "Rory" | | 7 | "Eva" | | 8 | "Empress" | | 9 | "Aurora" |
| | places | | 0 | "Soho" | | 1 | "Cardiff" | | 2 | "Prague" |
| | globalScore | 0.175 | | windowScore | 0 | |
| 51.32% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 76 | | glossingSentenceCount | 3 | | matches | | 0 | "felt like the safest dry spot in the wo" | | 1 | "photographs that seemed to stare at her from the gloom" | | 2 | "felt like cold water" |
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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 | 1491 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 238 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 97 | | mean | 15.37 | | std | 16.8 | | cv | 1.093 | | sampleLengths | | 0 | 90 | | 1 | 98 | | 2 | 64 | | 3 | 42 | | 4 | 7 | | 5 | 12 | | 6 | 10 | | 7 | 17 | | 8 | 1 | | 9 | 44 | | 10 | 5 | | 11 | 9 | | 12 | 4 | | 13 | 16 | | 14 | 41 | | 15 | 3 | | 16 | 3 | | 17 | 3 | | 18 | 23 | | 19 | 15 | | 20 | 6 | | 21 | 3 | | 22 | 5 | | 23 | 8 | | 24 | 3 | | 25 | 3 | | 26 | 27 | | 27 | 4 | | 28 | 19 | | 29 | 24 | | 30 | 22 | | 31 | 5 | | 32 | 5 | | 33 | 5 | | 34 | 34 | | 35 | 1 | | 36 | 4 | | 37 | 21 | | 38 | 4 | | 39 | 1 | | 40 | 1 | | 41 | 21 | | 42 | 28 | | 43 | 3 | | 44 | 3 | | 45 | 17 | | 46 | 1 | | 47 | 8 | | 48 | 24 | | 49 | 13 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 170 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 202 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 238 | | ratio | 0.004 | | matches | | 0 | "Her hands had changed too; the knuckles were swollen, the nails bitten down to the quick." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1102 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.020871143375680582 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004537205081669692 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 238 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 238 | | mean | 6.26 | | std | 4.07 | | cv | 0.649 | | sampleLengths | | 0 | 18 | | 1 | 13 | | 2 | 12 | | 3 | 11 | | 4 | 12 | | 5 | 24 | | 6 | 5 | | 7 | 14 | | 8 | 19 | | 9 | 7 | | 10 | 15 | | 11 | 8 | | 12 | 11 | | 13 | 15 | | 14 | 2 | | 15 | 2 | | 16 | 9 | | 17 | 5 | | 18 | 14 | | 19 | 14 | | 20 | 22 | | 21 | 2 | | 22 | 9 | | 23 | 14 | | 24 | 4 | | 25 | 8 | | 26 | 5 | | 27 | 7 | | 28 | 4 | | 29 | 7 | | 30 | 1 | | 31 | 3 | | 32 | 7 | | 33 | 4 | | 34 | 6 | | 35 | 7 | | 36 | 1 | | 37 | 9 | | 38 | 13 | | 39 | 19 | | 40 | 3 | | 41 | 4 | | 42 | 1 | | 43 | 4 | | 44 | 5 | | 45 | 4 | | 46 | 6 | | 47 | 10 | | 48 | 6 | | 49 | 4 |
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| 39.50% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 25 | | diversityRatio | 0.2815126050420168 | | totalSentences | 238 | | uniqueOpeners | 67 | |
| 45.35% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 147 | | matches | | 0 | "Bright blue irises locked onto" | | 1 | "Then he looked at Rory's" |
| | ratio | 0.014 | |
| 67.62% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 56 | | totalSentences | 147 | | matches | | 0 | "She pulled her coat tighter," | | 1 | "Her shoulder-length black hair stuck" | | 2 | "She checked her watch, then" | | 3 | "She was late for a" | | 4 | "She pushed the door open." | | 5 | "His grey-streaked auburn hair caught" | | 6 | "His neat beard framed a" | | 7 | "He spotted her through the" | | 8 | "Her eyes scanned the room." | | 9 | "She set her damp umbrella" | | 10 | "She took a breath." | | 11 | "Her voice was lower than" | | 12 | "She kept her hands in" | | 13 | "His slight limp in his" | | 14 | "He stopped at the counter" | | 15 | "He turned back to the" | | 16 | "Her hands had changed too;" | | 17 | "It was a dry sound." | | 18 | "She took a sip of" | | 19 | "She pointed at the bag" |
| | ratio | 0.381 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 138 | | totalSentences | 147 | | matches | | 0 | "Rain slicked the Soho pavement," | | 1 | "Aurora Carter stepped out of" | | 2 | "She pulled her coat tighter," | | 3 | "Her shoulder-length black hair stuck" | | 4 | "She checked her watch, then" | | 5 | "She was late for a" | | 6 | "She pushed the door open." | | 7 | "The bell chimed, a sharp" | | 8 | "The walls were covered with" | | 9 | "His grey-streaked auburn hair caught" | | 10 | "His neat beard framed a" | | 11 | "He spotted her through the" | | 12 | "Aurora moved to the back" | | 13 | "Her eyes scanned the room." | | 14 | "The stranger held a glass" | | 15 | "She set her damp umbrella" | | 16 | "The scar on her left" | | 17 | "She took a breath." | | 18 | "The air smelled of gin" | | 19 | "The woman turned her head." |
| | ratio | 0.939 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 147 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 1 | | matches | | 0 | "The walls were covered with old maps and black-and-white photographs that seemed to stare at her from the gloom." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 17 | | fancyCount | 2 | | fancyTags | | 0 | "Eva snapped (snap)" | | 1 | "Eva pressed (press)" |
| | dialogueSentences | 90 | | tagDensity | 0.189 | | leniency | 0.378 | | rawRatio | 0.118 | | effectiveRatio | 0.044 | |