| 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 | 866 | | 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) | |
| 71.13% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 866 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "imposing" | | 1 | "gloom" | | 2 | "echoing" | | 3 | "silence" | | 4 | "traced" |
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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 | 83 | | matches | (empty) | |
| 74.01% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 83 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 85 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 861 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 13 | | wordCount | 847 | | uniqueNames | 6 | | maxNameDensity | 0.83 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 7 | | Tube | 1 | | London | 1 | | Morris | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 1 | | matches | | 0 | "sigils that seemed to shift in the dim light" |
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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 | 861 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 85 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 22 | | mean | 39.14 | | std | 23.84 | | cv | 0.609 | | sampleLengths | | 0 | 60 | | 1 | 7 | | 2 | 74 | | 3 | 49 | | 4 | 42 | | 5 | 62 | | 6 | 59 | | 7 | 22 | | 8 | 88 | | 9 | 35 | | 10 | 11 | | 11 | 52 | | 12 | 55 | | 13 | 4 | | 14 | 63 | | 15 | 16 | | 16 | 43 | | 17 | 38 | | 18 | 16 | | 19 | 13 | | 20 | 4 | | 21 | 48 |
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| 92.58% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 83 | | matches | | 0 | "was pulled" | | 1 | "was filled" | | 2 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 138 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 85 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 852 | | adjectiveStacks | 1 | | stackExamples | | 0 | "against cold, seamless stone" |
| | adverbCount | 30 | | adverbRatio | 0.035211267605633804 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.008215962441314555 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 85 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 85 | | mean | 10.13 | | std | 6.64 | | cv | 0.656 | | sampleLengths | | 0 | 7 | | 1 | 14 | | 2 | 5 | | 3 | 9 | | 4 | 25 | | 5 | 4 | | 6 | 3 | | 7 | 5 | | 8 | 9 | | 9 | 7 | | 10 | 13 | | 11 | 13 | | 12 | 27 | | 13 | 16 | | 14 | 15 | | 15 | 12 | | 16 | 1 | | 17 | 5 | | 18 | 4 | | 19 | 18 | | 20 | 2 | | 21 | 5 | | 22 | 13 | | 23 | 3 | | 24 | 17 | | 25 | 15 | | 26 | 13 | | 27 | 14 | | 28 | 8 | | 29 | 21 | | 30 | 11 | | 31 | 8 | | 32 | 11 | | 33 | 12 | | 34 | 10 | | 35 | 9 | | 36 | 3 | | 37 | 5 | | 38 | 32 | | 39 | 7 | | 40 | 32 | | 41 | 10 | | 42 | 15 | | 43 | 3 | | 44 | 2 | | 45 | 2 | | 46 | 3 | | 47 | 4 | | 48 | 7 | | 49 | 5 |
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| 33.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.3058823529411765 | | totalSentences | 85 | | uniqueOpeners | 26 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 76 | | matches | | 0 | "Only a cold, assessing look." | | 1 | "Then he vaulted over a" | | 2 | "Then he was gone." | | 3 | "Then back at the solid" |
| | ratio | 0.053 | |
| 56.84% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 76 | | matches | | 0 | "It turned the neon signs" | | 1 | "He wasn’t just running." | | 2 | "He was flowing." | | 3 | "Her feet found purchase where" | | 4 | "Her arms pumped, a steady," | | 5 | "He was leading her north." | | 6 | "Her quarry glanced back." | | 7 | "She swung her legs over," | | 8 | "It was just another forgotten" | | 9 | "He pressed his hand against" | | 10 | "Her mind flashed back to" | | 11 | "He turned, and in the" | | 12 | "She sprinted, covering the distance" | | 13 | "She threw a hand out," | | 14 | "She was alone in the" | | 15 | "Her breath plumed in the" | | 16 | "She ran her hands over" | | 17 | "Her fingers brushed against something" | | 18 | "She picked it up." | | 19 | "It was a sliver of" |
| | ratio | 0.408 | |
| 32.37% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 76 | | matches | | 0 | "Rain slicked the cobblestones to" | | 1 | "It turned the neon signs" | | 2 | "Detective Harlow Quinn’s lungs burned." | | 3 | "Each breath was a gulp" | | 4 | "He wasn’t just running." | | 5 | "He was flowing." | | 6 | "Quinn’s military training took over." | | 7 | "Her feet found purchase where" | | 8 | "Her arms pumped, a steady," | | 9 | "The worn leather watch on" | | 10 | "A habit left over from" | | 11 | "This chase had no clear" | | 12 | "The hooded figure ducked left," | | 13 | "Quinn followed, her hand instinctively" | | 14 | "The alley opened onto a" | | 15 | "He was leading her north." | | 16 | "Her quarry glanced back." | | 17 | "Quinn didn't hesitate." | | 18 | "She swung her legs over," | | 19 | "The road was a service" |
| | ratio | 0.855 | |
| 65.79% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 76 | | matches | | 0 | "To find the answers, she" |
| | ratio | 0.013 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 4 | | matches | | 0 | "Fifty yards ahead, her quarry moved with a liquid grace, a hooded figure slipping through the thinning late-night crowd as if they weren’t even there." | | 1 | "She swung her legs over, her boots hitting the tarmac with a thud that jarred her teeth." | | 2 | "It was a sliver of yellowed bone, no longer than her thumb, carved with sharp, angular sigils that seemed to shift in the dim light." | | 3 | "She could retreat back to the world of procedure and paperwork, of answers that made sense." |
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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 | |