| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 24 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 58 | | tagDensity | 0.414 | | leniency | 0.828 | | rawRatio | 0.042 | | effectiveRatio | 0.034 | |
| 88.57% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1312 | | totalAiIsmAdverbs | 3 | | 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) | |
| 73.32% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1312 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "weight" | | 2 | "calculating" | | 3 | "scanned" | | 4 | "etched" | | 5 | "footsteps" | | 6 | "mechanical" |
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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 | 90 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 90 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 123 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1304 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 12 | | wordCount | 808 | | uniqueNames | 6 | | maxNameDensity | 0.87 | | worstName | "Silas" | | maxWindowNameDensity | 2 | | worstWindowName | "Silas" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Ice | 1 | | Silas | 7 | | Spymaster | 1 |
| | persons | | | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | 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 | 1304 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 123 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 25.08 | | std | 16.88 | | cv | 0.673 | | sampleLengths | | 0 | 61 | | 1 | 48 | | 2 | 62 | | 3 | 20 | | 4 | 26 | | 5 | 43 | | 6 | 9 | | 7 | 17 | | 8 | 24 | | 9 | 18 | | 10 | 24 | | 11 | 24 | | 12 | 48 | | 13 | 50 | | 14 | 40 | | 15 | 29 | | 16 | 12 | | 17 | 4 | | 18 | 51 | | 19 | 10 | | 20 | 36 | | 21 | 51 | | 22 | 44 | | 23 | 22 | | 24 | 48 | | 25 | 28 | | 26 | 26 | | 27 | 12 | | 28 | 49 | | 29 | 5 | | 30 | 36 | | 31 | 4 | | 32 | 34 | | 33 | 9 | | 34 | 10 | | 35 | 39 | | 36 | 3 | | 37 | 24 | | 38 | 1 | | 39 | 31 | | 40 | 22 | | 41 | 3 | | 42 | 5 | | 43 | 28 | | 44 | 9 | | 45 | 11 | | 46 | 16 | | 47 | 19 | | 48 | 16 | | 49 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 90 | | matches | | |
| 19.82% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 148 | | matches | | 0 | "was polishing" | | 1 | "were yellowing" | | 2 | "wasn't pointing" | | 3 | "was looking" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 123 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 812 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.027093596059113302 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.013546798029556651 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 123 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 123 | | mean | 10.6 | | std | 6.98 | | cv | 0.658 | | sampleLengths | | 0 | 20 | | 1 | 20 | | 2 | 21 | | 3 | 21 | | 4 | 15 | | 5 | 12 | | 6 | 10 | | 7 | 12 | | 8 | 6 | | 9 | 20 | | 10 | 14 | | 11 | 7 | | 12 | 13 | | 13 | 8 | | 14 | 6 | | 15 | 12 | | 16 | 2 | | 17 | 4 | | 18 | 12 | | 19 | 11 | | 20 | 14 | | 21 | 4 | | 22 | 5 | | 23 | 12 | | 24 | 5 | | 25 | 18 | | 26 | 6 | | 27 | 13 | | 28 | 5 | | 29 | 10 | | 30 | 7 | | 31 | 7 | | 32 | 4 | | 33 | 20 | | 34 | 11 | | 35 | 15 | | 36 | 22 | | 37 | 7 | | 38 | 11 | | 39 | 11 | | 40 | 21 | | 41 | 7 | | 42 | 19 | | 43 | 14 | | 44 | 16 | | 45 | 13 | | 46 | 10 | | 47 | 2 | | 48 | 4 | | 49 | 22 |
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| 43.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3089430894308943 | | totalSentences | 123 | | uniqueOpeners | 38 | |
| 42.19% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 79 | | matches | | 0 | "Slowly, he turned, placing the" |
| | ratio | 0.013 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 79 | | matches | | 0 | "I shoved the door open" | | 1 | "It smelled of lemon polish" | | 2 | "I walked to the bar," | | 3 | "He was polishing a tumbler," | | 4 | "He looked smaller than I" | | 5 | "His shoulders, once broad and" | | 6 | "His voice was a low" | | 7 | "I dropped my duffel bag" | | 8 | "It landed with a heavy" | | 9 | "His eyes, once sharp and" | | 10 | "He didn't smile" | | 11 | "I said, leaning against the" | | 12 | "He reached for a bottle" | | 13 | "I watched him pour" | | 14 | "He slid the glass across" | | 15 | "It stopped an inch from" | | 16 | "I ignored the drink." | | 17 | "I scanned the room" | | 18 | "He just stared at me," | | 19 | "He poured himself a drink," |
| | ratio | 0.608 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 77 | | totalSentences | 79 | | matches | | 0 | "The heavy iron key ground" | | 1 | "I shoved the door open" | | 2 | "It smelled of lemon polish" | | 3 | "The Raven's Nest sat empty," | | 4 | "Dust motes danced in the" | | 5 | "I walked to the bar," | | 6 | "Silas stood behind the mahogany" | | 7 | "He was polishing a tumbler," | | 8 | "He looked smaller than I" | | 9 | "His shoulders, once broad and" | | 10 | "The grey in his auburn" | | 11 | "His voice was a low" | | 12 | "I dropped my duffel bag" | | 13 | "It landed with a heavy" | | 14 | "The cloth stopped moving." | | 15 | "His eyes, once sharp and" | | 16 | "A fresh, angry bruise discoloured" | | 17 | "He didn't smile" | | 18 | "I said, leaning against the" | | 19 | "He reached for a bottle" |
| | ratio | 0.975 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 79 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 1 | | matches | | 0 | "He just stared at me, his eyes boring into mine, searching for something I wasn't sure I still had." |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 24 | | uselessAdditionCount | 3 | | matches | | 0 | "He reached, his hand trembling slightly" | | 1 | "He dropped, turning to face me" | | 2 | "Silas gripped, his fingers digging into my skin" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "I lied (lie)" | | 1 | "he roared (roar)" |
| | dialogueSentences | 58 | | tagDensity | 0.086 | | leniency | 0.172 | | rawRatio | 0.4 | | effectiveRatio | 0.069 | |