| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 27 | | adverbTagCount | 2 | | adverbTags | | 0 | "Silas walked around [around]" | | 1 | "Silas turned away [away]" |
| | dialogueSentences | 67 | | tagDensity | 0.403 | | leniency | 0.806 | | rawRatio | 0.074 | | effectiveRatio | 0.06 | |
| 93.49% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1535 | | 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) | |
| 51.14% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1535 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "shattered" | | 1 | "glinting" | | 2 | "crystal" | | 3 | "warmth" | | 4 | "traced" | | 5 | "calculating" | | 6 | "echoing" | | 7 | "stomach" | | 8 | "churned" | | 9 | "normalcy" | | 10 | "potential" | | 11 | "familiar" | | 12 | "weight" | | 13 | "echoed" | | 14 | "tension" |
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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 | 100 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 100 | | filterMatches | (empty) | | hedgeMatches | | |
| 93.60% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 140 | | gibberishSentences | 2 | | adjustedGibberishSentences | 2 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0.014 | | matches | | 0 | "\"Recognise this?\" Silas pointed to a cluster of pins near the金丝雀 Wharf." | | 1 | "Rory stared at the照片." |
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| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1527 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 54 | | wordCount | 903 | | uniqueNames | 19 | | maxNameDensity | 2.55 | | worstName | "Silas" | | maxWindowNameDensity | 5 | | worstWindowName | "Silas" | | discoveredNames | | Rory | 14 | | Raven | 1 | | Nest | 1 | | Yu-Fei | 1 | | Cheung | 1 | | Golden | 1 | | Empress | 1 | | Blackwood | 1 | | Prague | 1 | | Steady | 1 | | Silas | 23 | | London | 1 | | Wharf | 1 | | Photographs | 1 | | Brendan | 1 | | Carter | 1 | | Evan | 1 | | Russian | 1 | | English | 1 |
| | persons | | 0 | "Rory" | | 1 | "Yu-Fei" | | 2 | "Cheung" | | 3 | "Blackwood" | | 4 | "Silas" | | 5 | "Wharf" | | 6 | "Photographs" | | 7 | "Brendan" | | 8 | "Carter" | | 9 | "Evan" | | 10 | "English" |
| | places | | 0 | "Raven" | | 1 | "Prague" | | 2 | "London" | | 3 | "Russian" |
| | globalScore | 0.226 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 69 | | 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 | 1527 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 140 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 28.81 | | std | 19.77 | | cv | 0.686 | | sampleLengths | | 0 | 69 | | 1 | 69 | | 2 | 27 | | 3 | 26 | | 4 | 61 | | 5 | 25 | | 6 | 9 | | 7 | 55 | | 8 | 21 | | 9 | 39 | | 10 | 57 | | 11 | 29 | | 12 | 37 | | 13 | 63 | | 14 | 37 | | 15 | 1 | | 16 | 61 | | 17 | 4 | | 18 | 36 | | 19 | 2 | | 20 | 44 | | 21 | 54 | | 22 | 12 | | 23 | 6 | | 24 | 30 | | 25 | 12 | | 26 | 47 | | 27 | 32 | | 28 | 54 | | 29 | 5 | | 30 | 53 | | 31 | 2 | | 32 | 49 | | 33 | 5 | | 34 | 35 | | 35 | 4 | | 36 | 47 | | 37 | 4 | | 38 | 37 | | 39 | 33 | | 40 | 39 | | 41 | 13 | | 42 | 6 | | 43 | 15 | | 44 | 20 | | 45 | 8 | | 46 | 12 | | 47 | 20 | | 48 | 25 | | 49 | 20 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 100 | | 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 | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 140 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 910 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 16 | | adverbRatio | 0.017582417582417582 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.004395604395604396 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 140 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 140 | | mean | 10.91 | | std | 8.13 | | cv | 0.745 | | sampleLengths | | 0 | 11 | | 1 | 18 | | 2 | 17 | | 3 | 23 | | 4 | 14 | | 5 | 6 | | 6 | 11 | | 7 | 17 | | 8 | 21 | | 9 | 4 | | 10 | 16 | | 11 | 7 | | 12 | 10 | | 13 | 16 | | 14 | 21 | | 15 | 21 | | 16 | 16 | | 17 | 3 | | 18 | 18 | | 19 | 7 | | 20 | 9 | | 21 | 22 | | 22 | 1 | | 23 | 1 | | 24 | 16 | | 25 | 9 | | 26 | 6 | | 27 | 8 | | 28 | 13 | | 29 | 8 | | 30 | 14 | | 31 | 17 | | 32 | 12 | | 33 | 19 | | 34 | 26 | | 35 | 17 | | 36 | 7 | | 37 | 5 | | 38 | 30 | | 39 | 7 | | 40 | 15 | | 41 | 11 | | 42 | 8 | | 43 | 14 | | 44 | 15 | | 45 | 7 | | 46 | 25 | | 47 | 5 | | 48 | 1 | | 49 | 35 |
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| 67.14% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.42857142857142855 | | totalSentences | 140 | | uniqueOpeners | 60 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 89 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 89 | | matches | | 0 | "She didn't flinch, didn't even" | | 1 | "She dropped the Yu-Fei Cheung's" | | 2 | "His grey-streaked auburn beard caught" | | 3 | "His voice carried that quiet" | | 4 | "He reached for a bottle" | | 5 | "She watched his hands" | | 6 | "She wrapped her fingers around" | | 7 | "She took a sip" | | 8 | "He looked at her, really" | | 9 | "He stopped inches from her." | | 10 | "He ran a hand along" | | 11 | "She slid off the stool" | | 12 | "Her father's face, smiling, clinking" | | 13 | "He checked the chamber, the" | | 14 | "He slid it across the" | | 15 | "It sat there, dark and" | | 16 | "She thought of Evan's fists." | | 17 | "Her father's smiling face in" | | 18 | "She reached out." | | 19 | "Her fingers closed around the" |
| | ratio | 0.281 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 89 | | matches | | 0 | "The glass shattered against the" | | 1 | "She didn't flinch, didn't even" | | 2 | "The distinctive green neon sign" | | 3 | "She dropped the Yu-Fei Cheung's" | | 4 | "Steam curled from the plastic" | | 5 | "The bar was empty save" | | 6 | "Silas Blackwood wiped a tumbler" | | 7 | "His grey-streaked auburn beard caught" | | 8 | "His voice carried that quiet" | | 9 | "Rory brushed a shard of" | | 10 | "Silas set the glass down" | | 11 | "The limp in his left" | | 12 | "He reached for a bottle" | | 13 | "Rory slid onto a stool," | | 14 | "She watched his hands" | | 15 | "The hands of a man" | | 16 | "Silas slid the glass across" | | 17 | "Rory let out a short," | | 18 | "She wrapped her fingers around" | | 19 | "Silas leaned against the back" |
| | ratio | 0.921 | |
| 56.18% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 89 | | matches | | 0 | "Now they poured amber liquid" |
| | ratio | 0.011 | |
| 68.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 3 | | matches | | 0 | "His voice carried that quiet authority that made grown men check their pockets for stolen goods." | | 1 | "The hands of a man who had once dismantled bombs or strangled men in dark rooms." | | 2 | "He looked at her, really looked at her, seeing the bright blue eyes that had lost their innocent sparkle, replaced by a cold, calculating hardness." |
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| 50.93% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 27 | | uselessAdditionCount | 4 | | matches | | 0 | "Silas reached out, his fingers hovering near her wrist, then pulling back" | | 1 | "Silas leaned, his shadow stretching long across the maps" | | 2 | "Silas turned, his expression grim" | | 3 | "she said, her voice cutting through the tension like a knife," |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 67 | | tagDensity | 0.09 | | leniency | 0.179 | | rawRatio | 0 | | effectiveRatio | 0 | |