| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 60.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 500 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "suddenly" | | 1 | "perfectly" | | 2 | "completely" |
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| 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) | |
| 40.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 500 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "gleaming" | | 1 | "measured" | | 2 | "etched" | | 3 | "chill" | | 4 | "electric" | | 5 | "silk" |
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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 | 49 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 49 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 49 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 22 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 489 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 57.98% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 489 | | uniqueNames | 10 | | maxNameDensity | 1.84 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 9 | | Morris | 2 | | Victorian-era | 1 | | Tube | 1 | | Veil | 1 | | Market | 1 | | Go | 1 | | London | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" |
| | places | | | globalScore | 0.58 | | windowScore | 0.833 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 39 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like an old brass token from his p" | | 1 | "e liquid, some seemingly in motion even when" | | 2 | "quite look human" |
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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 | 489 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 49 | | matches | (empty) | |
| 94.88% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 17 | | mean | 28.76 | | std | 13.87 | | cv | 0.482 | | sampleLengths | | 0 | 46 | | 1 | 53 | | 2 | 37 | | 3 | 20 | | 4 | 39 | | 5 | 7 | | 6 | 37 | | 7 | 28 | | 8 | 27 | | 9 | 17 | | 10 | 17 | | 11 | 32 | | 12 | 6 | | 13 | 42 | | 14 | 37 | | 15 | 37 | | 16 | 7 |
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| 98.10% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 49 | | matches | | |
| 33.33% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 80 | | matches | | 0 | "wasn't losing" | | 1 | "was already swinging" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 49 | | ratio | 0.143 | | matches | | 0 | "She hadn't planned on a foot chase tonight—she'd been tracking this lead for weeks, and now, suddenly, everything was moving fast." | | 1 | "The suspect—a thin, wiry man in a dark coat—moved with unexpected agility." | | 2 | "He struck a section of tiled wall—Quinn realized they were near an old Tube entrance—and something shifted." | | 3 | "Her instinct—the same instinct that had solved impossible cases, that had tracked supernatural anomalies others ignored—said: Go." | | 4 | "The token her suspect had used glimmered briefly—bone-white, etched with symbols she didn't recognize." | | 5 | "Soft light came from sources she couldn't identify—not electric, not flame, something else entirely." | | 6 | "Objects gleamed—some metallic, some liquid, some seemingly in motion even when stationary." |
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| 97.02% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 504 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.041666666666666664 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.021825396825396824 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 49 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 49 | | mean | 9.98 | | std | 5 | | cv | 0.501 | | sampleLengths | | 0 | 14 | | 1 | 12 | | 2 | 20 | | 3 | 6 | | 4 | 12 | | 5 | 14 | | 6 | 21 | | 7 | 12 | | 8 | 6 | | 9 | 5 | | 10 | 2 | | 11 | 12 | | 12 | 13 | | 13 | 5 | | 14 | 2 | | 15 | 17 | | 16 | 10 | | 17 | 12 | | 18 | 6 | | 19 | 1 | | 20 | 13 | | 21 | 8 | | 22 | 16 | | 23 | 17 | | 24 | 11 | | 25 | 3 | | 26 | 9 | | 27 | 15 | | 28 | 4 | | 29 | 9 | | 30 | 2 | | 31 | 2 | | 32 | 17 | | 33 | 7 | | 34 | 11 | | 35 | 14 | | 36 | 6 | | 37 | 4 | | 38 | 17 | | 39 | 7 | | 40 | 14 | | 41 | 15 | | 42 | 12 | | 43 | 10 | | 44 | 7 | | 45 | 9 | | 46 | 11 | | 47 | 10 | | 48 | 7 |
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| 96.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5918367346938775 | | totalSentences | 49 | | uniqueOpeners | 29 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 44 | | matches | | 0 | "Then he was moving again," | | 1 | "No longer London's damp chill," |
| | ratio | 0.045 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 8 | | totalSentences | 44 | | matches | | 0 | "Her salt-and-pepper hair was plastered" | | 1 | "She hadn't planned on a" | | 2 | "Her worn leather watch caught" | | 3 | "She wasn't losing this one." | | 4 | "He struck a section of" | | 5 | "Her training screamed warning." | | 6 | "Her instinct—the same instinct that" | | 7 | "She knew she was massively" |
| | ratio | 0.182 | |
| 85.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 33 | | totalSentences | 44 | | matches | | 0 | "The rain sliced sideways, cutting" | | 1 | "Detective Harlow Quinn's boots splashed" | | 2 | "Quinn's hand instinctively brushed her" | | 3 | "Her salt-and-pepper hair was plastered" | | 4 | "She hadn't planned on a" | | 5 | "The suspect—a thin, wiry man" | | 6 | "Quinn recognized his movement: practiced," | | 7 | "Something connected to the case" | | 8 | "Her worn leather watch caught" | | 9 | "She wasn't losing this one." | | 10 | "The suspect ducked down a" | | 11 | "Quinn followed, her breathing controlled," | | 12 | "The alley narrowed, trash bins" | | 13 | "Halfway down, the suspect suddenly" | | 14 | "A reflection, a depth, something" | | 15 | "He struck a section of" | | 16 | "A hidden door, camouflaged perfectly" | | 17 | "The Veil Market." | | 18 | "Quinn had heard whispers, fragments" | | 19 | "An underground marketplace that moved" |
| | ratio | 0.75 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 44 | | matches | | | ratio | 0.023 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 3 | | matches | | 0 | "For a split second, Quinn saw something in his eyes that wasn't human." | | 1 | "An underground marketplace that moved with each full moon, trafficking in things beyond normal comprehension." | | 2 | "Her instinct—the same instinct that had solved impossible cases, that had tracked supernatural anomalies others ignored—said: Go." |
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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 | |