| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.11% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1286 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 41.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1286 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoing" | | 2 | "scanning" | | 3 | "vibrated" | | 4 | "rhythmic" | | 5 | "velvet" | | 6 | "porcelain" | | 7 | "silk" | | 8 | "echoed" | | 9 | "resonated" | | 10 | "silence" | | 11 | "hulking" | | 12 | "flicker" |
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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 | 108 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 108 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 116 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1285 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.52% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 1138 | | uniqueNames | 10 | | maxNameDensity | 1.67 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 19 | | Tube | 1 | | Camden | 1 | | Veil | 1 | | Market | 2 | | Saint | 1 | | Christopher | 1 | | Herrera | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Herrera" |
| | places | | | globalScore | 0.665 | | windowScore | 0.667 | |
| 63.79% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | glossingSentenceCount | 3 | | matches | | 0 | "daggers that seemed to swallow the light" | | 1 | "looked like cracked parchment" | | 2 | "sounded like two stones grinding together" |
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| 44.36% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.556 | | wordCount | 1285 | | matches | | 0 | "Not opening, but erasing themselves from existence" | | 1 | "not in her ears, but directly in her skull" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 116 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 24.71 | | std | 15.59 | | cv | 0.631 | | sampleLengths | | 0 | 48 | | 1 | 53 | | 2 | 45 | | 3 | 40 | | 4 | 38 | | 5 | 14 | | 6 | 43 | | 7 | 8 | | 8 | 27 | | 9 | 39 | | 10 | 15 | | 11 | 65 | | 12 | 5 | | 13 | 39 | | 14 | 33 | | 15 | 16 | | 16 | 14 | | 17 | 20 | | 18 | 7 | | 19 | 49 | | 20 | 20 | | 21 | 8 | | 22 | 13 | | 23 | 9 | | 24 | 32 | | 25 | 12 | | 26 | 19 | | 27 | 12 | | 28 | 31 | | 29 | 8 | | 30 | 13 | | 31 | 13 | | 32 | 40 | | 33 | 11 | | 34 | 36 | | 35 | 28 | | 36 | 39 | | 37 | 40 | | 38 | 20 | | 39 | 24 | | 40 | 7 | | 41 | 40 | | 42 | 27 | | 43 | 4 | | 44 | 26 | | 45 | 43 | | 46 | 12 | | 47 | 4 | | 48 | 16 | | 49 | 49 |
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| 98.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 108 | | matches | | 0 | "were lined" | | 1 | "been overturned" |
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| 71.18% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 207 | | matches | | 0 | "was weaving" | | 1 | "was climbing" | | 2 | "was standing" | | 3 | "were hulking" |
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| 68.97% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 2 | | flaggedSentences | 3 | | totalSentences | 116 | | ratio | 0.026 | | matches | | 0 | "A vendor with three fingers on his left hand hawked vials of shimmering silver liquid; another polished a set of obsidian daggers that seemed to swallow the light." | | 1 | "His eyes weren't human; they glowed with a pale, sickly luminescence that pierced the fog." | | 2 | "The air around her grew frigid, and for a second, she saw a flicker of a man standing beside her—a man in a police uniform with a kind smile and a badge that read 'Morris'." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1129 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.01771479185119575 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005314437555358724 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 116 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 116 | | mean | 11.08 | | std | 6.35 | | cv | 0.574 | | sampleLengths | | 0 | 17 | | 1 | 10 | | 2 | 21 | | 3 | 3 | | 4 | 3 | | 5 | 8 | | 6 | 19 | | 7 | 20 | | 8 | 17 | | 9 | 11 | | 10 | 5 | | 11 | 12 | | 12 | 15 | | 13 | 7 | | 14 | 6 | | 15 | 6 | | 16 | 6 | | 17 | 9 | | 18 | 8 | | 19 | 9 | | 20 | 12 | | 21 | 10 | | 22 | 4 | | 23 | 7 | | 24 | 9 | | 25 | 11 | | 26 | 16 | | 27 | 8 | | 28 | 3 | | 29 | 7 | | 30 | 17 | | 31 | 18 | | 32 | 12 | | 33 | 9 | | 34 | 15 | | 35 | 12 | | 36 | 16 | | 37 | 9 | | 38 | 28 | | 39 | 5 | | 40 | 16 | | 41 | 11 | | 42 | 12 | | 43 | 14 | | 44 | 19 | | 45 | 5 | | 46 | 11 | | 47 | 6 | | 48 | 8 | | 49 | 9 |
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| 39.66% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.3103448275862069 | | totalSentences | 116 | | uniqueOpeners | 36 | |
| 93.46% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 107 | | matches | | 0 | "Just a solid wall of" | | 1 | "Instead, she found herself in" | | 2 | "Then, from the shadows of" |
| | ratio | 0.028 | |
| 74.21% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 107 | | matches | | 0 | "She didn't slow." | | 1 | "Her gaze locked on the" | | 2 | "She vaulted over a pile" | | 3 | "He slid behind a rusted" | | 4 | "He didn't use a key." | | 5 | "He simply vanished through the" | | 6 | "She stepped forward and gripped" | | 7 | "She leaned in, her brown" | | 8 | "She reached down and plucked" | | 9 | "It was a piece of" | | 10 | "She pressed the bone token" | | 11 | "She had entered an abandoned" | | 12 | "She was a jagged piece" | | 13 | "He stopped at a stall" | | 14 | "She shouldered past a man" | | 15 | "His voice sounded like two" | | 16 | "He turned a corner, disappearing" | | 17 | "She surged forward, ripping the" | | 18 | "He had olive skin and" | | 19 | "He noticed the badge on" |
| | ratio | 0.364 | |
| 25.42% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 107 | | matches | | 0 | "Detective Harlow Quinn sprinted, her" | | 1 | "Quinn’s lungs burned." | | 2 | "She didn't slow." | | 3 | "Her gaze locked on the" | | 4 | "She vaulted over a pile" | | 5 | "A spray of cold water" | | 6 | "The man bolted toward a" | | 7 | "He slid behind a rusted" | | 8 | "He didn't use a key." | | 9 | "He simply vanished through the" | | 10 | "Quinn skidded to a halt," | | 11 | "She stepped forward and gripped" | | 12 | "She leaned in, her brown" | | 13 | "A small, bleached object lay" | | 14 | "She reached down and plucked" | | 15 | "It was a piece of" | | 16 | "A low hum vibrated through" | | 17 | "The iron bars shivered." | | 18 | "Quinn looked back at the" | | 19 | "The rain blurred the world" |
| | ratio | 0.869 | |
| 93.46% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 107 | | matches | | 0 | "If she called for backup" | | 1 | "If she waited, she might" |
| | ratio | 0.019 | |
| 90.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 4 | | matches | | 0 | "Quinn stepped through the threshold and descended a flight of concrete stairs that spiraled deep into the earth." | | 1 | "A vendor with three fingers on his left hand hawked vials of shimmering silver liquid; another polished a set of obsidian daggers that seemed to swallow the lig…" | | 2 | "He shifted his arm, revealing a jagged scar that ran the length of his left forearm." | | 3 | "He was climbing a rusted iron ladder that led to a maintenance catwalk overlooking the market." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 59.09% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 11 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0.5 | | effectiveRatio | 0.182 | |