| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 149 | | tagDensity | 0.013 | | leniency | 0.027 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1966 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 94.91% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1966 | | totalAiIsms | 2 | | found | | | highlights | | |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 122 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 122 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 269 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1966 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 1174 | | uniqueNames | 5 | | maxNameDensity | 1.45 | | worstName | "Marian" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Marian" | | discoveredNames | | Baltic | 1 | | Silas | 10 | | Marian | 17 | | Rory | 8 | | Ellen | 2 |
| | persons | | 0 | "Baltic" | | 1 | "Silas" | | 2 | "Marian" | | 3 | "Rory" | | 4 | "Ellen" |
| | places | (empty) | | globalScore | 0.776 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 92 | | glossingSentenceCount | 1 | | matches | | 0 | "shirts that seemed to survive heat, dust, twelve-hour flights" |
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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 | 1966 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 269 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 215 | | mean | 9.14 | | std | 10.67 | | cv | 1.167 | | sampleLengths | | 0 | 51 | | 1 | 19 | | 2 | 6 | | 3 | 9 | | 4 | 9 | | 5 | 26 | | 6 | 18 | | 7 | 1 | | 8 | 4 | | 9 | 6 | | 10 | 22 | | 11 | 1 | | 12 | 5 | | 13 | 11 | | 14 | 18 | | 15 | 5 | | 16 | 7 | | 17 | 56 | | 18 | 9 | | 19 | 2 | | 20 | 4 | | 21 | 13 | | 22 | 5 | | 23 | 5 | | 24 | 5 | | 25 | 6 | | 26 | 4 | | 27 | 3 | | 28 | 35 | | 29 | 7 | | 30 | 2 | | 31 | 7 | | 32 | 18 | | 33 | 63 | | 34 | 7 | | 35 | 3 | | 36 | 2 | | 37 | 5 | | 38 | 7 | | 39 | 2 | | 40 | 1 | | 41 | 23 | | 42 | 5 | | 43 | 5 | | 44 | 13 | | 45 | 18 | | 46 | 5 | | 47 | 22 | | 48 | 5 | | 49 | 1 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 122 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 203 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 269 | | ratio | 0.004 | | matches | | 0 | "A drop remained on her lower lip; she caught it with the napkin." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1175 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.01957446808510638 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 269 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 269 | | mean | 7.31 | | std | 5.84 | | cv | 0.799 | | sampleLengths | | 0 | 18 | | 1 | 8 | | 2 | 25 | | 3 | 19 | | 4 | 4 | | 5 | 2 | | 6 | 9 | | 7 | 9 | | 8 | 7 | | 9 | 14 | | 10 | 5 | | 11 | 12 | | 12 | 6 | | 13 | 1 | | 14 | 4 | | 15 | 6 | | 16 | 6 | | 17 | 5 | | 18 | 11 | | 19 | 1 | | 20 | 5 | | 21 | 11 | | 22 | 15 | | 23 | 3 | | 24 | 5 | | 25 | 7 | | 26 | 9 | | 27 | 16 | | 28 | 13 | | 29 | 11 | | 30 | 7 | | 31 | 9 | | 32 | 2 | | 33 | 4 | | 34 | 13 | | 35 | 5 | | 36 | 5 | | 37 | 5 | | 38 | 6 | | 39 | 4 | | 40 | 3 | | 41 | 9 | | 42 | 4 | | 43 | 22 | | 44 | 7 | | 45 | 2 | | 46 | 7 | | 47 | 7 | | 48 | 5 | | 49 | 6 |
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| 45.17% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.2788104089219331 | | totalSentences | 269 | | uniqueOpeners | 75 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 115 | | matches | | 0 | "Then she looked at Silas." | | 1 | "Once, in a hotel without" | | 2 | "Once she would have sat" | | 3 | "Then one side of her" |
| | ratio | 0.035 | |
| 4.35% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 62 | | totalSentences | 115 | | matches | | 0 | "She carried a shopping bag" | | 1 | "She looked at the row" | | 2 | "He held a stack of" | | 3 | "She unbuttoned her coat." | | 4 | "She took them from him" | | 5 | "He chose another." | | 6 | "Her coat had a broken" | | 7 | "Her hair, once black and" | | 8 | "She had gathered it at" | | 9 | "He put the soda water" | | 10 | "He picked up the scoop." | | 11 | "She carried it through the" | | 12 | "She squeezed the lemon into" | | 13 | "She wiped them on her" | | 14 | "She had worn pale shirts" | | 15 | "He had laughed at her." | | 16 | "She had made him take" | | 17 | "He offered her a folded" | | 18 | "She took it." | | 19 | "She looked along the bar" |
| | ratio | 0.539 | |
| 7.83% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 104 | | totalSentences | 115 | | matches | | 0 | "Silas had pulled the till" | | 1 | "Rain darkened the shoulders of" | | 2 | "She carried a shopping bag" | | 3 | "Rory stood on a chair" | | 4 | "The woman put the bag" | | 5 | "She looked at the row" | | 6 | "He held a stack of" | | 7 | "She unbuttoned her coat." | | 8 | "Rory climbed down from the" | | 9 | "Silas still held the coins." | | 10 | "She took them from him" | | 11 | "Marian’s eyes moved to her." | | 12 | "Silas reached for a glass," | | 13 | "He chose another." | | 14 | "Her coat had a broken" | | 15 | "Her hair, once black and" | | 16 | "She had gathered it at" | | 17 | "He put the soda water" | | 18 | "He picked up the scoop." | | 19 | "Rory lifted the till drawer." |
| | ratio | 0.904 | |
| 43.48% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 115 | | matches | | | ratio | 0.009 | |
| 98.21% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 3 | | matches | | 0 | "She had worn pale shirts that seemed to survive heat, dust, twelve-hour flights." | | 1 | "Then one side of her mouth lifted, and for a moment he saw the woman who had stood beside him at a departure gate, both of them carrying passports in names thei…" | | 2 | "He looked at her yellow coat hanging from the hook, its sleeves dripping onto the floor." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 149 | | tagDensity | 0.007 | | leniency | 0.013 | | rawRatio | 0 | | effectiveRatio | 0 | |