| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said slowly [slowly]" |
| | dialogueSentences | 10 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.2 | | effectiveRatio | 0.2 | |
| 80.35% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1018 | | totalAiIsmAdverbs | 4 | | found | | 0 | | adverb | "deliberately" | | count | 1 |
| | 1 | | | 2 | |
| | highlights | | 0 | "deliberately" | | 1 | "slightly" | | 2 | "slowly" |
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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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1018 | | totalAiIsms | 29 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | | | 23 | |
| | highlights | | 0 | "electric" | | 1 | "calculating" | | 2 | "scanned" | | 3 | "flicker" | | 4 | "familiar" | | 5 | "loomed" | | 6 | "comforting" | | 7 | "weight" | | 8 | "resolve" | | 9 | "echoes" | | 10 | "glistening" | | 11 | "scanning" | | 12 | "tapestry" | | 13 | "sense of" | | 14 | "tension" | | 15 | "intrigue" | | 16 | "jaw clenched" | | 17 | "flicked" | | 18 | "depths" | | 19 | "intricate" | | 20 | "complex" | | 21 | "intriguing" | | 22 | "whisper" | | 23 | "dance" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 57 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 57 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 61 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1006 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 91.43% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 939 | | uniqueNames | 14 | | maxNameDensity | 1.17 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | London | 1 | | Harlow | 2 | | Quinn | 11 | | Veil | 2 | | Market | 6 | | Tomás | 2 | | Herrera | 8 | | Raven | 1 | | Nest | 1 | | Camden | 1 | | Morris | 3 | | Tube | 1 | | Saint | 1 | | Christopher | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Raven" | | 5 | "Morris" | | 6 | "Saint" | | 7 | "Christopher" |
| | places | | 0 | "London" | | 1 | "Veil" | | 2 | "Market" | | 3 | "Camden" |
| | globalScore | 0.914 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 1 | | matches | | 0 | "not quite meeting his warm brown eyes that told a story of their own" |
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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 | 1006 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 61 | | matches | (empty) | |
| 77.80% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 24 | | mean | 41.92 | | std | 17.7 | | cv | 0.422 | | sampleLengths | | 0 | 57 | | 1 | 40 | | 2 | 73 | | 3 | 53 | | 4 | 82 | | 5 | 57 | | 6 | 31 | | 7 | 64 | | 8 | 61 | | 9 | 28 | | 10 | 18 | | 11 | 52 | | 12 | 49 | | 13 | 38 | | 14 | 14 | | 15 | 32 | | 16 | 20 | | 17 | 24 | | 18 | 41 | | 19 | 37 | | 20 | 19 | | 21 | 31 | | 22 | 50 | | 23 | 35 |
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| 92.95% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 57 | | matches | | 0 | "were swallowed" | | 1 | "were pursued" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 153 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 61 | | ratio | 0.164 | | matches | | 0 | "Ahead, the suspect—a slippery figure she’d come to connect with a series of robberies tied to the Veil Market—darted around a corner." | | 1 | "She pounded forward, gaining ground, her worn leather watch dampened against her wrist, marking the moments of this chase—a tide she refused to let turn." | | 2 | "But the suspect veered off before reaching the door, disappearing into a narrow grate in the street—an entrance to the underground, a portal to where she’d never ventured." | | 3 | "Below lay whispers of the forbidden—a labyrinth known as the Veil Market." | | 4 | "Her steps became deliberately soft, the sounds of commerce trilling around her—a haunting melody in the darkness." | | 5 | "Yet, she couldn’t shake the sense of purpose here, the lines of her life leading here tonight—a feral truth beneath the city's skin." | | 6 | "Herrera froze momentarily, then turned slowly, a familiar half-smile playing on his lips—not quite meeting his warm brown eyes that told a story of their own." | | 7 | "Quinn's eyes flicked back to the suspect, who tossed a glance—part defiant, part desperate—between them before trying to bolt into the Market's depths again." | | 8 | "Her instincts, though, whispered the truth—that she now straddled a world more complex than any she'd left to chance." | | 9 | "As they climbed toward the surface, rain pelting down once more, she knew the path from here would meander between the lines—warped and intriguing, a whisper beyond the rain's dance in the earthbound city above." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 958 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.024008350730688934 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.008350730688935281 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 61 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 61 | | mean | 16.49 | | std | 7.44 | | cv | 0.451 | | sampleLengths | | 0 | 19 | | 1 | 22 | | 2 | 16 | | 3 | 22 | | 4 | 18 | | 5 | 19 | | 6 | 12 | | 7 | 17 | | 8 | 6 | | 9 | 19 | | 10 | 12 | | 11 | 16 | | 12 | 25 | | 13 | 30 | | 14 | 24 | | 15 | 28 | | 16 | 13 | | 17 | 12 | | 18 | 11 | | 19 | 21 | | 20 | 13 | | 21 | 18 | | 22 | 19 | | 23 | 16 | | 24 | 12 | | 25 | 17 | | 26 | 15 | | 27 | 29 | | 28 | 17 | | 29 | 6 | | 30 | 22 | | 31 | 6 | | 32 | 9 | | 33 | 3 | | 34 | 26 | | 35 | 26 | | 36 | 26 | | 37 | 23 | | 38 | 20 | | 39 | 18 | | 40 | 11 | | 41 | 3 | | 42 | 6 | | 43 | 26 | | 44 | 5 | | 45 | 15 | | 46 | 11 | | 47 | 8 | | 48 | 5 | | 49 | 29 |
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| 80.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.4918032786885246 | | totalSentences | 61 | | uniqueOpeners | 30 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 70.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 56 | | matches | | 0 | "Her brown eyes, sharp and" | | 1 | "She'd been watching him for" | | 2 | "Her breath came steady despite" | | 3 | "She pounded forward, gaining ground," | | 4 | "She knew the place well" | | 5 | "It shifted like sea foam" | | 6 | "Her jaw tightened with resolve," | | 7 | "She kicked the grate wider" | | 8 | "Her steps became deliberately soft," | | 9 | "He moved with purpose, scanning" | | 10 | "She moved forward." | | 11 | "She kept her distance, her" | | 12 | "She stepped out, firm, her" | | 13 | "he smoothly replied" | | 14 | "Her jaw clenched at the" | | 15 | "He took a step back," | | 16 | "he said slowly" | | 17 | "she told the suspect, her" | | 18 | "Her instincts, though, whispered the" | | 19 | "She had chosen the chase." |
| | ratio | 0.375 | |
| 85.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 42 | | totalSentences | 56 | | matches | | 0 | "The rain poured down in" | | 1 | "Detective Harlow Quinn moved with" | | 2 | "Her brown eyes, sharp and" | | 3 | "Quinn sped up, her lean" | | 4 | "The day had begun with" | | 5 | "The presence of Tomás Herrera," | | 6 | "She'd been watching him for" | | 7 | "Tonight, he'd made contact with" | | 8 | "Her breath came steady despite" | | 9 | "The suspect was fast but" | | 10 | "She pounded forward, gaining ground," | | 11 | "She knew the place well" | | 12 | "Quinn skidded to a halt" | | 13 | "It shifted like sea foam" | | 14 | "Her jaw tightened with resolve," | | 15 | "She kicked the grate wider" | | 16 | "The echoes of her boots" | | 17 | "Her steps became deliberately soft," | | 18 | "Tomás Herrera, his olive skin" | | 19 | "He moved with purpose, scanning" |
| | ratio | 0.75 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 56 | | matches | | 0 | "Now, with the evening swallowing" | | 1 | "Yet, she couldn’t shake the" |
| | ratio | 0.036 | |
| 93.02% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 3 | | matches | | 0 | "The suspect was fast but Quinn noticed the falter, the occasional glance back that screamed uncertainty." | | 1 | "She pounded forward, gaining ground, her worn leather watch dampened against her wrist, marking the moments of this chase—a tide she refused to let turn." | | 2 | "Herrera froze momentarily, then turned slowly, a familiar half-smile playing on his lips—not quite meeting his warm brown eyes that told a story of their own." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 1 | | matches | | 0 | "she told, her voice calm, belying the tempest swirling inside" |
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| 50.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | 0 | "Herrera murmured (murmur)" |
| | dialogueSentences | 10 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.25 | | effectiveRatio | 0.2 | |