| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 95.75% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1177 | | totalAiIsmAdverbs | 1 | | 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) | |
| 78.76% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1177 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "traced" | | 1 | "weight" | | 2 | "flickered" | | 3 | "trembled" | | 4 | "pulsed" |
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| 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 | 201 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 1 | | narrationSentences | 201 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 201 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 17 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1177 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 69 | | wordCount | 1177 | | uniqueNames | 8 | | maxNameDensity | 1.95 | | worstName | "You" | | maxWindowNameDensity | 4 | | worstWindowName | "You" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Prague | 3 | | Cardiff | 4 | | Aurora | 21 | | Silas | 15 | | You | 23 |
| | persons | | 0 | "Raven" | | 1 | "Aurora" | | 2 | "Silas" | | 3 | "You" |
| | places | | 0 | "Soho" | | 1 | "Prague" | | 2 | "Cardiff" |
| | globalScore | 0.523 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 98 | | glossingSentenceCount | 1 | | matches | | 0 | "tasted like smoke and copper" |
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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 | 1177 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 201 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 101 | | mean | 11.65 | | std | 10.02 | | cv | 0.859 | | sampleLengths | | 0 | 70 | | 1 | 63 | | 2 | 12 | | 3 | 26 | | 4 | 9 | | 5 | 17 | | 6 | 9 | | 7 | 19 | | 8 | 5 | | 9 | 23 | | 10 | 13 | | 11 | 15 | | 12 | 23 | | 13 | 3 | | 14 | 13 | | 15 | 11 | | 16 | 7 | | 17 | 14 | | 18 | 6 | | 19 | 5 | | 20 | 4 | | 21 | 15 | | 22 | 14 | | 23 | 9 | | 24 | 11 | | 25 | 5 | | 26 | 12 | | 27 | 10 | | 28 | 6 | | 29 | 6 | | 30 | 14 | | 31 | 8 | | 32 | 6 | | 33 | 24 | | 34 | 20 | | 35 | 6 | | 36 | 8 | | 37 | 20 | | 38 | 13 | | 39 | 8 | | 40 | 5 | | 41 | 11 | | 42 | 8 | | 43 | 13 | | 44 | 12 | | 45 | 20 | | 46 | 6 | | 47 | 17 | | 48 | 4 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 201 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 246 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 201 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1178 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.021222410865874362 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.003395585738539898 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 201 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 201 | | mean | 5.86 | | std | 2.9 | | cv | 0.495 | | sampleLengths | | 0 | 17 | | 1 | 11 | | 2 | 10 | | 3 | 15 | | 4 | 17 | | 5 | 15 | | 6 | 6 | | 7 | 17 | | 8 | 13 | | 9 | 12 | | 10 | 2 | | 11 | 10 | | 12 | 4 | | 13 | 6 | | 14 | 4 | | 15 | 12 | | 16 | 9 | | 17 | 3 | | 18 | 6 | | 19 | 8 | | 20 | 3 | | 21 | 6 | | 22 | 7 | | 23 | 5 | | 24 | 7 | | 25 | 1 | | 26 | 4 | | 27 | 5 | | 28 | 8 | | 29 | 10 | | 30 | 7 | | 31 | 6 | | 32 | 5 | | 33 | 10 | | 34 | 10 | | 35 | 6 | | 36 | 7 | | 37 | 3 | | 38 | 7 | | 39 | 6 | | 40 | 3 | | 41 | 8 | | 42 | 5 | | 43 | 2 | | 44 | 3 | | 45 | 6 | | 46 | 5 | | 47 | 6 | | 48 | 5 | | 49 | 4 |
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| 34.08% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 32 | | diversityRatio | 0.14925373134328357 | | totalSentences | 201 | | uniqueOpeners | 30 | |
| 52.63% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 190 | | matches | | 0 | "Then why are we talking?" | | 1 | "Then why are you here?" | | 2 | "Then you are still running." |
| | ratio | 0.016 | |
| 9.47% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 100 | | totalSentences | 190 | | matches | | 0 | "She kept her head down," | | 1 | "She had not stepped foot" | | 2 | "He looked smaller than she" | | 3 | "His left leg rested on" | | 4 | "He traced the rim of" | | 5 | "Her hand hovered over the" | | 6 | "His hazel eyes locked onto" | | 7 | "He did not smile." | | 8 | "He set the glass down" | | 9 | "You look like you haven't" | | 10 | "She stopped at the edge" | | 11 | "I work nights." | | 12 | "His movement was slow, deliberate." | | 13 | "You're blocking the light." | | 14 | "She tucked her left wrist" | | 15 | "I didn't expect you to" | | 16 | "I thought you were in" | | 17 | "I spend my time watching" | | 18 | "He slid it across the" | | 19 | "You look different." |
| | ratio | 0.526 | |
| 2.11% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 174 | | totalSentences | 190 | | matches | | 0 | "The green neon sign buzzed" | | 1 | "Aurora pushed through the heavy" | | 2 | "The air inside smelled of" | | 3 | "She kept her head down," | | 4 | "She had not stepped foot" | | 5 | "Silas sat in the corner" | | 6 | "He looked smaller than she" | | 7 | "The grey streaks in his" | | 8 | "His left leg rested on" | | 9 | "He traced the rim of" | | 10 | "Her hand hovered over the" | | 11 | "Silas lifted his head." | | 12 | "His hazel eyes locked onto" | | 13 | "He did not smile." | | 14 | "He set the glass down" | | 15 | "You look like you haven't" | | 16 | "Aurora walked forward." | | 17 | "The floorboards groaned under her" | | 18 | "She stopped at the edge" | | 19 | "I work nights." |
| | ratio | 0.916 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 190 | | matches | | 0 | "Because you haven't looked me" | | 1 | "Because you're the only one" | | 2 | "If you touched my mail," | | 3 | "Because I can't protect you" |
| | ratio | 0.021 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |