| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 353 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 15.01% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 353 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "gloom" | | 1 | "footsteps" | | 2 | "echoed" | | 3 | "churning" | | 4 | "scanning" |
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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 | 25 | | matches | (empty) | |
| 85.71% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 25 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 25 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 352 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 78.98% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 10 | | wordCount | 352 | | uniqueNames | 6 | | maxNameDensity | 1.42 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | High | 1 | | Street | 1 | | Harlow | 1 | | Quinn | 5 | | Tube | 1 |
| | persons | | | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" |
| | globalScore | 0.79 | | windowScore | 1 | |
| 45.83% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 24 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like grinding stones" |
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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 | 352 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 25 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 14 | | mean | 25.14 | | std | 17.69 | | cv | 0.704 | | sampleLengths | | 0 | 19 | | 1 | 6 | | 2 | 46 | | 3 | 17 | | 4 | 37 | | 5 | 12 | | 6 | 10 | | 7 | 47 | | 8 | 13 | | 9 | 12 | | 10 | 41 | | 11 | 65 | | 12 | 10 | | 13 | 17 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 25 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 65 | | matches | (empty) | |
| 28.57% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 25 | | ratio | 0.04 | | matches | | 0 | "Lanterns cast sickly green and purple glows across bizarre wares hung from iron hooks—shriveled roots, jars containing churning violet smoke, and weapons forged from dark, light-absorbing metal." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 356 | | adjectiveStacks | 1 | | stackExamples | | 0 | "over slick concrete steps" |
| | adverbCount | 4 | | adverbRatio | 0.011235955056179775 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0056179775280898875 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 25 | | echoCount | 0 | | echoWords | (empty) | |
| 90.95% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 25 | | mean | 14.08 | | std | 5.31 | | cv | 0.377 | | sampleLengths | | 0 | 19 | | 1 | 6 | | 2 | 22 | | 3 | 5 | | 4 | 19 | | 5 | 17 | | 6 | 8 | | 7 | 10 | | 8 | 19 | | 9 | 12 | | 10 | 10 | | 11 | 16 | | 12 | 8 | | 13 | 23 | | 14 | 13 | | 15 | 12 | | 16 | 14 | | 17 | 16 | | 18 | 11 | | 19 | 12 | | 20 | 12 | | 21 | 27 | | 22 | 14 | | 23 | 10 | | 24 | 17 |
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| 96.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.64 | | totalSentences | 25 | | uniqueOpeners | 16 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 25 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 2 | | totalSentences | 25 | | matches | | 0 | "She reached the top of" | | 1 | "She descended past the rusted" |
| | ratio | 0.08 | |
| 40.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 21 | | totalSentences | 25 | | matches | | 0 | "Rain slicked the asphalt across" | | 1 | "Rubber soles slapped against the" | | 2 | "Detective Harlow Quinn punched her" | | 3 | "A sharp jaw set tight." | | 4 | "The figure ahead rounded the" | | 5 | "Quinn closed the gap, heels" | | 6 | "Water soaked through her trench" | | 7 | "She reached the top of" | | 8 | "A rusted iron gate hung" | | 9 | "A jagged piece of bone" | | 10 | "Quinn paused at the threshold," | | 11 | "Shadows stretched weirdly down the" | | 12 | "Footsteps echoed ahead, splashing through" | | 13 | "Quinn gripped the butt of" | | 14 | "She descended past the rusted" | | 15 | "The tunnel walls wept black" | | 16 | "A market carved out of" | | 17 | "Stalls fashioned from rotting timber" | | 18 | "Lanterns cast sickly green and" | | 19 | "The target slipped between two" |
| | ratio | 0.84 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 25 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 1 | | matches | | 0 | "Beneath the street level, the air grew thick, humming with an invisible static charge that made the hairs on her arms stand upright." |
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| 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 | |