| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.393 | | leniency | 0.786 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 75.67% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1233 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "sharply" | | 1 | "very" | | 2 | "suddenly" | | 3 | "lightly" | | 4 | "quickly" |
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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) | |
| 2.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1233 | | totalAiIsms | 24 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | word | "sent shivers down" | | count | 1 |
| | 20 | |
| | highlights | | 0 | "echoed" | | 1 | "raced" | | 2 | "determined" | | 3 | "gloom" | | 4 | "scanned" | | 5 | "velvet" | | 6 | "navigated" | | 7 | "quickened" | | 8 | "silk" | | 9 | "encounter" | | 10 | "chilling" | | 11 | "weight" | | 12 | "disrupt" | | 13 | "unreadable" | | 14 | "intriguing" | | 15 | "ensure" | | 16 | "eyebrow" | | 17 | "trembled" | | 18 | "gleaming" | | 19 | "sent shivers down" | | 20 | "could feel" |
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| 0.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 4 | | maxInWindow | 4 | | found | | 0 | | label | "heart pounded in chest" | | count | 1 |
| | 1 | | label | "eyes widened/narrowed" | | count | 2 |
| | 2 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "heart hammered in her chest" | | 1 | "eyes narrowed" | | 2 | "eyes widened" | | 3 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 78 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 78 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 96 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 10 | | totalWords | 1229 | | ratio | 0.008 | | matches | | 0 | "Keep going, Harlow. For Morris" | | 1 | "A market for monsters? Wonderful" |
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| 97.22% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 1 | | matches | | 0 | "For a moment, Harlow faltered." |
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| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 909 | | uniqueNames | 9 | | maxNameDensity | 1.54 | | worstName | "Harlow" | | maxWindowNameDensity | 4 | | worstWindowName | "Silas" | | discoveredNames | | Detective | 1 | | Harlow | 14 | | Quinn | 7 | | Soho | 1 | | Nest | 2 | | London | 1 | | Veil | 1 | | Market | 1 | | Silas | 9 |
| | persons | | 0 | "Detective" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Nest" | | 4 | "Market" | | 5 | "Silas" |
| | places | | | globalScore | 0.73 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | 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 | 1229 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 96 | | matches | | |
| 99.13% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 35.11 | | std | 17.45 | | cv | 0.497 | | sampleLengths | | 0 | 51 | | 1 | 65 | | 2 | 49 | | 3 | 53 | | 4 | 5 | | 5 | 41 | | 6 | 45 | | 7 | 33 | | 8 | 58 | | 9 | 65 | | 10 | 68 | | 11 | 6 | | 12 | 27 | | 13 | 3 | | 14 | 38 | | 15 | 16 | | 16 | 25 | | 17 | 41 | | 18 | 9 | | 19 | 49 | | 20 | 35 | | 21 | 38 | | 22 | 33 | | 23 | 21 | | 24 | 20 | | 25 | 25 | | 26 | 32 | | 27 | 44 | | 28 | 16 | | 29 | 24 | | 30 | 41 | | 31 | 45 | | 32 | 26 | | 33 | 22 | | 34 | 60 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 78 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 154 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 96 | | ratio | 0.01 | | matches | | 0 | "Harlow bit her lip; she hadn't anticipated this turn of events." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 389 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 9 | | adverbRatio | 0.02313624678663239 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.007712082262210797 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 96 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 96 | | mean | 12.8 | | std | 6.22 | | cv | 0.486 | | sampleLengths | | 0 | 20 | | 1 | 18 | | 2 | 13 | | 3 | 21 | | 4 | 14 | | 5 | 20 | | 6 | 10 | | 7 | 17 | | 8 | 12 | | 9 | 20 | | 10 | 7 | | 11 | 16 | | 12 | 5 | | 13 | 9 | | 14 | 16 | | 15 | 3 | | 16 | 2 | | 17 | 11 | | 18 | 12 | | 19 | 18 | | 20 | 3 | | 21 | 6 | | 22 | 14 | | 23 | 11 | | 24 | 11 | | 25 | 4 | | 26 | 1 | | 27 | 11 | | 28 | 7 | | 29 | 10 | | 30 | 12 | | 31 | 12 | | 32 | 22 | | 33 | 12 | | 34 | 8 | | 35 | 28 | | 36 | 13 | | 37 | 16 | | 38 | 17 | | 39 | 21 | | 40 | 6 | | 41 | 17 | | 42 | 7 | | 43 | 6 | | 44 | 12 | | 45 | 15 | | 46 | 3 | | 47 | 12 | | 48 | 15 | | 49 | 11 |
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| 57.29% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.375 | | totalSentences | 96 | | uniqueOpeners | 36 | |
| 44.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 75 | | matches | | 0 | "Then, suddenly, he laughed, a" |
| | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 75 | | matches | | 0 | "Her voice echoed off the" | | 1 | "She had been so close," | | 2 | "She needed an edge, something" | | 3 | "Her hand instinctively touched the" | | 4 | "She recognised it from her" | | 5 | "She felt her grip tighten" | | 6 | "She had no jurisdiction here," | | 7 | "She scanned the market, searching" | | 8 | "Her eyes narrowed as she" | | 9 | "she whispered, her breath creating" | | 10 | "Her boots squeaked on the" | | 11 | "Her mind raced, considering her" | | 12 | "She had to make her" | | 13 | "she said, her voice strong" | | 14 | "She had no proof, no" |
| | ratio | 0.2 | |
| 73.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 75 | | matches | | 0 | "The cold rain stung her" | | 1 | "The cobblestones glistened under the" | | 2 | "Harlow knew this chase might" | | 3 | "Her voice echoed off the" | | 4 | "Harlow's heart raced as she" | | 5 | "The chase had begun at" | | 6 | "This suspect was her last" | | 7 | "She had been so close," | | 8 | "Harlow cursed under her breath" | | 9 | "The rain-slicked streets threatened to" | | 10 | "The suspect was younger, faster." | | 11 | "She needed an edge, something" | | 12 | "Her hand instinctively touched the" | | 13 | "Harlow skidded to a stop," | | 14 | "The Veil Market." | | 15 | "She recognised it from her" | | 16 | "An underground supernatural hub that" | | 17 | "The very place where she" | | 18 | "Harlow bit her lip; she" | | 19 | "*A market for monsters?" |
| | ratio | 0.773 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 5 | | totalSentences | 75 | | matches | | 0 | "Now, she was determined not" | | 1 | "Yet, her instincts screamed that" | | 2 | "If she called for backup," | | 3 | "Just as he was about" | | 4 | "Before Quinn could respond, Silas" |
| | ratio | 0.067 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 1 | | matches | | 0 | "She had been so close, yet now he was slipping away into the night, his steps quickening with every second." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 3 | | matches | | 0 | "she whispered, her breath creating a small cloud in the cold air" | | 1 | "she said, her voice strong and steady" | | 2 | "Silas raised, his hand still outstretched towards the captive suspect" |
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| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 4 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "Quinn muttered (mutter)" | | 2 | "Silas announced (announce)" | | 3 | "Silas whispered (whisper)" |
| | dialogueSentences | 28 | | tagDensity | 0.179 | | leniency | 0.357 | | rawRatio | 0.8 | | effectiveRatio | 0.286 | |