| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.31 | | leniency | 0.621 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 79.25% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1205 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "suddenly" | | 1 | "slowly" | | 2 | "really" |
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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) | |
| 58.51% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1205 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoing" | | 2 | "quickened" | | 3 | "otherworldly" | | 4 | "raced" | | 5 | "pounding" | | 6 | "jaw clenched" | | 7 | "racing" | | 8 | "could feel" | | 9 | "weight" |
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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 | 0 | | narrationSentences | 75 | | matches | (empty) | |
| 85.71% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 75 | | filterMatches | (empty) | | hedgeMatches | | 0 | "happened to" | | 1 | "begin to" | | 2 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1189 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 896 | | uniqueNames | 11 | | maxNameDensity | 2.34 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 2 | | Quinn | 21 | | Soho | 1 | | Raven | 1 | | Nest | 1 | | London | 1 | | Veil | 1 | | Market | 1 | | Morris | 2 | | Met | 1 | | Detective | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" |
| | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "London" | | 3 | "Market" |
| | globalScore | 0.328 | | windowScore | 0.167 | |
| 74.24% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 2 | | matches | | 0 | "as if recognizing his authority" | | 1 | "hum that seemed to resonate with something deep within her" |
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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 | 1189 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 95 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 29 | | std | 14.97 | | cv | 0.516 | | sampleLengths | | 0 | 40 | | 1 | 65 | | 2 | 46 | | 3 | 55 | | 4 | 70 | | 5 | 3 | | 6 | 35 | | 7 | 36 | | 8 | 43 | | 9 | 19 | | 10 | 6 | | 11 | 30 | | 12 | 22 | | 13 | 16 | | 14 | 20 | | 15 | 21 | | 16 | 13 | | 17 | 31 | | 18 | 17 | | 19 | 24 | | 20 | 8 | | 21 | 27 | | 22 | 12 | | 23 | 39 | | 24 | 32 | | 25 | 18 | | 26 | 33 | | 27 | 8 | | 28 | 45 | | 29 | 16 | | 30 | 53 | | 31 | 23 | | 32 | 36 | | 33 | 32 | | 34 | 21 | | 35 | 32 | | 36 | 28 | | 37 | 28 | | 38 | 23 | | 39 | 39 | | 40 | 24 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 75 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 160 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 95 | | ratio | 0.063 | | matches | | 0 | "The suspect—a wiry man in a dark hoodie—darted ahead, his silhouette barely visible in the sodium-vapor glow of the streetlights." | | 1 | "The air smelled of mildew and something else—something sharp and metallic that made the fine hairs on her arms stand up." | | 2 | "Quinn recognized some of the items from her years on the force—enchanted weapons, banned alchemical substances, grimoires bound in human skin." | | 3 | "She noted the way the market's patrons—humans and creatures she couldn't begin to identify—parted before him, as if recognizing his authority." | | 4 | "The suspect exchanged a few words with the proprietor—a woman with eyes that reflected light like a cat's—and received a small, bone-white token in return." | | 5 | "The suspect was right—she was out of her depth here." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 911 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, bone-white token" |
| | adverbCount | 19 | | adverbRatio | 0.020856201975850714 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.009879253567508232 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 12.52 | | std | 6.98 | | cv | 0.558 | | sampleLengths | | 0 | 20 | | 1 | 20 | | 2 | 15 | | 3 | 21 | | 4 | 2 | | 5 | 27 | | 6 | 19 | | 7 | 10 | | 8 | 11 | | 9 | 6 | | 10 | 15 | | 11 | 8 | | 12 | 11 | | 13 | 21 | | 14 | 15 | | 15 | 10 | | 16 | 13 | | 17 | 11 | | 18 | 21 | | 19 | 3 | | 20 | 9 | | 21 | 11 | | 22 | 15 | | 23 | 9 | | 24 | 6 | | 25 | 21 | | 26 | 18 | | 27 | 25 | | 28 | 8 | | 29 | 11 | | 30 | 6 | | 31 | 10 | | 32 | 9 | | 33 | 4 | | 34 | 7 | | 35 | 12 | | 36 | 10 | | 37 | 13 | | 38 | 3 | | 39 | 9 | | 40 | 11 | | 41 | 13 | | 42 | 8 | | 43 | 6 | | 44 | 7 | | 45 | 16 | | 46 | 15 | | 47 | 8 | | 48 | 9 | | 49 | 4 |
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| 65.96% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.42105263157894735 | | totalSentences | 95 | | uniqueOpeners | 40 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 74 | | matches | | 0 | "Slowly, he turned to face" | | 1 | "Slowly, she lowered her weapon." | | 2 | "Then, with a deep breath," |
| | ratio | 0.041 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 74 | | matches | | 0 | "She'd been tailing him for" | | 1 | "She paused at the threshold," | | 2 | "Her heart raced as she" | | 3 | "She noted the way the" | | 4 | "They reached a stall at" | | 5 | "She needed that token." | | 6 | "She stepped out from her" | | 7 | "she called out, her voice" | | 8 | "he said, his voice calm" | | 9 | "she said, her voice low" | | 10 | "He nodded towards the stall" | | 11 | "She knew accepting the token" | | 12 | "she said, her voice tight" | | 13 | "She could feel a faint" | | 14 | "She turned back to the" | | 15 | "she called out" | | 16 | "She looked around the market" |
| | ratio | 0.23 | |
| 54.59% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 74 | | matches | | 0 | "Detective Harlow Quinn's boots splashed" | | 1 | "The suspect—a wiry man in" | | 2 | "She'd been tailing him for" | | 3 | "The man had been making" | | 4 | "Quinn's instincts told her he" | | 5 | "The suspect suddenly veered left," | | 6 | "Quinn followed, her hand instinctively" | | 7 | "The door opened into a" | | 8 | "She paused at the threshold," | | 9 | "The air smelled of mildew" | | 10 | "The suspect was already moving" | | 11 | "Quinn quickened her pace, her" | | 12 | "The tunnel opened into a" | | 13 | "Stalls lined the perimeter, their" | | 14 | "Quinn recognized some of the" | | 15 | "The Veil Market." | | 16 | "Her heart raced as she" | | 17 | "This was the place Morris" | | 18 | "The place where he'd told" | | 19 | "The suspect wove through the" |
| | ratio | 0.811 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 55.75% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 5 | | matches | | 0 | "Quinn's instincts told her he was involved in something bigger than petty crime, something that might finally explain what had happened to her partner three yea…" | | 1 | "The suspect was already moving down the tunnel, his footsteps echoing off the concrete walls." | | 2 | "She noted the way the market's patrons—humans and creatures she couldn't begin to identify—parted before him, as if recognizing his authority." | | 3 | "The suspect exchanged a few words with the proprietor—a woman with eyes that reflected light like a cat's—and received a small, bone-white token in return." | | 4 | "She could feel a faint vibration emanating from it, a hum that seemed to resonate with something deep within her." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 3 | | matches | | 0 | "she called out, her voice cutting through the market's ambient noise" | | 1 | "she said, her voice low and dangerous" | | 2 | "she said, her voice tight" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | 0 | "she called out (call out)" |
| | dialogueSentences | 29 | | tagDensity | 0.207 | | leniency | 0.414 | | rawRatio | 0.167 | | effectiveRatio | 0.069 | |