| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 58 | | tagDensity | 0.034 | | leniency | 0.069 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 80.05% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1253 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "really" | | 2 | "suddenly" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 44.13% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1253 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "weight" | | 1 | "crystal" | | 2 | "methodical" | | 3 | "scanning" | | 4 | "throbbed" | | 5 | "silence" | | 6 | "warmth" | | 7 | "predator" | | 8 | "flicker" | | 9 | "synchronized" | | 10 | "scanned" | | 11 | "fleeting" |
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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 | 75 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 75 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 131 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1253 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 92.26% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 866 | | uniqueNames | 13 | | maxNameDensity | 1.15 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Soho | 1 | | Blackwood | 1 | | Aurora | 10 | | Marcus | 6 | | Cardiff | 1 | | University | 1 | | Silas | 3 | | Thames | 1 | | Severn | 1 | | Bridge | 1 | | Keats | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Blackwood" | | 3 | "Aurora" | | 4 | "Marcus" | | 5 | "Silas" | | 6 | "Keats" |
| | places | | 0 | "Soho" | | 1 | "Cardiff" | | 2 | "University" | | 3 | "Thames" | | 4 | "Severn" | | 5 | "Bridge" |
| | globalScore | 0.923 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 1 | | matches | | 0 | "coat that seemed to swallow the 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 | 1253 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 131 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 84 | | mean | 14.92 | | std | 15.76 | | cv | 1.056 | | sampleLengths | | 0 | 54 | | 1 | 47 | | 2 | 2 | | 3 | 3 | | 4 | 47 | | 5 | 8 | | 6 | 5 | | 7 | 22 | | 8 | 3 | | 9 | 4 | | 10 | 4 | | 11 | 56 | | 12 | 3 | | 13 | 10 | | 14 | 54 | | 15 | 1 | | 16 | 10 | | 17 | 59 | | 18 | 45 | | 19 | 1 | | 20 | 11 | | 21 | 8 | | 22 | 7 | | 23 | 6 | | 24 | 3 | | 25 | 5 | | 26 | 5 | | 27 | 40 | | 28 | 24 | | 29 | 12 | | 30 | 37 | | 31 | 4 | | 32 | 10 | | 33 | 4 | | 34 | 4 | | 35 | 34 | | 36 | 6 | | 37 | 15 | | 38 | 5 | | 39 | 4 | | 40 | 5 | | 41 | 9 | | 42 | 61 | | 43 | 9 | | 44 | 10 | | 45 | 4 | | 46 | 3 | | 47 | 20 | | 48 | 16 | | 49 | 11 |
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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 | 1 | | totalVerbs | 138 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 131 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 870 | | adjectiveStacks | 2 | | stackExamples | | 0 | "tight over high cheekbones," | | 1 | "dull purple against his" |
| | adverbCount | 23 | | adverbRatio | 0.026436781609195402 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.011494252873563218 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 131 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 131 | | mean | 9.56 | | std | 5.93 | | cv | 0.62 | | sampleLengths | | 0 | 18 | | 1 | 10 | | 2 | 4 | | 3 | 22 | | 4 | 19 | | 5 | 10 | | 6 | 18 | | 7 | 2 | | 8 | 3 | | 9 | 11 | | 10 | 14 | | 11 | 13 | | 12 | 9 | | 13 | 8 | | 14 | 5 | | 15 | 9 | | 16 | 13 | | 17 | 3 | | 18 | 4 | | 19 | 4 | | 20 | 11 | | 21 | 4 | | 22 | 12 | | 23 | 13 | | 24 | 5 | | 25 | 11 | | 26 | 3 | | 27 | 10 | | 28 | 11 | | 29 | 19 | | 30 | 5 | | 31 | 19 | | 32 | 1 | | 33 | 10 | | 34 | 8 | | 35 | 5 | | 36 | 8 | | 37 | 14 | | 38 | 24 | | 39 | 8 | | 40 | 20 | | 41 | 17 | | 42 | 1 | | 43 | 11 | | 44 | 8 | | 45 | 3 | | 46 | 4 | | 47 | 6 | | 48 | 3 | | 49 | 5 |
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| 40.84% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.2900763358778626 | | totalSentences | 131 | | uniqueOpeners | 38 | |
| 45.05% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 74 | | matches | | 0 | "Suddenly, the front door of" |
| | ratio | 0.014 | |
| 25.41% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 74 | | matches | | 0 | "She didn't look up." | | 1 | "He moved toward the far" | | 2 | "He polished a heavy crystal" | | 3 | "He leaned forward, his hazel" | | 4 | "He paused, his gaze drifting" | | 5 | "He wore a heavy, dark" | | 6 | "He didn't order a drink." | | 7 | "He just sat, his hands" | | 8 | "She stared at the man." | | 9 | "His face was gaunt, the" | | 10 | "His voice was a low" | | 11 | "He didn't smile." | | 12 | "He didn't even blink." | | 13 | "She stood, her legs feeling" | | 14 | "She walked toward the corner," | | 15 | "she said, sliding into the" | | 16 | "He reached for a glass" | | 17 | "His hands were steady, but" | | 18 | "He leaned forward, the movement" | | 19 | "His eyes, once a vibrant" |
| | ratio | 0.486 | |
| 0.54% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 74 | | matches | | 0 | "The heavy oak door of" | | 1 | "Aurora gripped her glass, the" | | 2 | "She didn't look up." | | 3 | "The scent of stale hops" | | 4 | "A man stumbled slightly, his" | | 5 | "He moved toward the far" | | 6 | "Aurora turned on her stool," | | 7 | "Silas Blackwood stood behind the" | | 8 | "He polished a heavy crystal" | | 9 | "The silver signet ring on" | | 10 | "Silas set the glass down" | | 11 | "He leaned forward, his hazel" | | 12 | "He paused, his gaze drifting" | | 13 | "Aurora followed his eyes." | | 14 | "The stranger sat in the" | | 15 | "He wore a heavy, dark" | | 16 | "He didn't order a drink." | | 17 | "He just sat, his hands" | | 18 | "Aurora felt a cold prickle" | | 19 | "The crescent-shaped scar on her" |
| | ratio | 0.919 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 96.27% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 3 | | matches | | 0 | "He moved toward the far corner, avoiding the sickly green neon light that bled through the front window." | | 1 | "That Marcus had possessed a bright, infectious energy, a boy with ink-stained fingers and a laugh that could puncture even the most academic silence." | | 2 | "As she approached, the smell of him hit her, a sharp, metallic scent that reminded her of rain on hot pavement." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "Aurora whispered, her voice trembling" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "Aurora whispered (whisper)" |
| | dialogueSentences | 58 | | tagDensity | 0.034 | | leniency | 0.069 | | rawRatio | 0.5 | | effectiveRatio | 0.034 | |