| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 42 | | tagDensity | 0.381 | | leniency | 0.762 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1004 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | 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 | 1004 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "scanned" | | 1 | "glinting" | | 2 | "measured" | | 3 | "flicked" | | 4 | "traced" | | 5 | "echoed" | | 6 | "shattered" | | 7 | "pulse" | | 8 | "silence" | | 9 | "throbbed" | | 10 | "unspoken" | | 11 | "etched" | | 12 | "whisper" | | 13 | "warmth" | | 14 | "loomed" | | 15 | "echoes" | | 16 | "charged" |
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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 | 86 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 86 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 11 | | totalWords | 995 | | ratio | 0.011 | | matches | | 0 | "Straighten up, Aurora. Worlds wait for thinkers." | | 1 | "Evan's fists. My silence." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 97.60% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 668 | | uniqueNames | 16 | | maxNameDensity | 1.05 | | worstName | "Silas" | | maxWindowNameDensity | 2 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 2 | | Blackwood | 1 | | Cardiff | 2 | | Soho | 2 | | Dad | 1 | | Safe | 1 | | Silas | 7 | | Evan | 4 | | Ellis-Carter | 1 | | Aurora | 1 | | Worlds | 1 | | Waited | 1 | | Knife | 1 | | Glass | 1 | | Rory | 4 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Blackwood" | | 3 | "Silas" | | 4 | "Evan" | | 5 | "Ellis-Carter" | | 6 | "Knife" | | 7 | "Glass" | | 8 | "Rory" |
| | places | | | globalScore | 0.976 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 995 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 25.51 | | std | 14.84 | | cv | 0.582 | | sampleLengths | | 0 | 68 | | 1 | 39 | | 2 | 2 | | 3 | 29 | | 4 | 14 | | 5 | 28 | | 6 | 14 | | 7 | 50 | | 8 | 37 | | 9 | 43 | | 10 | 50 | | 11 | 46 | | 12 | 46 | | 13 | 30 | | 14 | 33 | | 15 | 9 | | 16 | 15 | | 17 | 23 | | 18 | 31 | | 19 | 22 | | 20 | 25 | | 21 | 27 | | 22 | 28 | | 23 | 44 | | 24 | 23 | | 25 | 11 | | 26 | 40 | | 27 | 6 | | 28 | 13 | | 29 | 15 | | 30 | 12 | | 31 | 11 | | 32 | 16 | | 33 | 17 | | 34 | 8 | | 35 | 20 | | 36 | 7 | | 37 | 15 | | 38 | 28 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 86 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 127 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 110 | | ratio | 0.009 | | matches | | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 680 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 12 | | adverbRatio | 0.01764705882352941 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0014705882352941176 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 9.05 | | std | 5.59 | | cv | 0.618 | | sampleLengths | | 0 | 16 | | 1 | 26 | | 2 | 17 | | 3 | 9 | | 4 | 12 | | 5 | 12 | | 6 | 15 | | 7 | 2 | | 8 | 7 | | 9 | 11 | | 10 | 11 | | 11 | 7 | | 12 | 7 | | 13 | 15 | | 14 | 7 | | 15 | 6 | | 16 | 14 | | 17 | 8 | | 18 | 3 | | 19 | 9 | | 20 | 23 | | 21 | 7 | | 22 | 8 | | 23 | 17 | | 24 | 12 | | 25 | 1 | | 26 | 9 | | 27 | 22 | | 28 | 11 | | 29 | 9 | | 30 | 18 | | 31 | 6 | | 32 | 17 | | 33 | 10 | | 34 | 6 | | 35 | 18 | | 36 | 5 | | 37 | 7 | | 38 | 12 | | 39 | 22 | | 40 | 12 | | 41 | 4 | | 42 | 7 | | 43 | 11 | | 44 | 8 | | 45 | 8 | | 46 | 1 | | 47 | 24 | | 48 | 3 | | 49 | 5 |
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| 95.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.5727272727272728 | | totalSentences | 110 | | uniqueOpeners | 63 | |
| 42.74% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 78 | | matches | | 0 | "Always the barrister, parading her" |
| | ratio | 0.013 | |
| 45.64% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 78 | | matches | | 0 | "She wiped her hand on" | | 1 | "He limped forward, each step" | | 2 | "She froze, fingers tightening on" | | 3 | "She slid cash across the" | | 4 | "He poured without breaking gaze," | | 5 | "He leaned in, elbows planted" | | 6 | "She sipped, the bitter hop" | | 7 | "Her blue eyes flicked to" | | 8 | "His laugh scraped low, like" | | 9 | "She traced the crescent scar" | | 10 | "He slid a bowl of" | | 11 | "His gaze sharpened, probing the" | | 12 | "She shrugged, but the motion" | | 13 | "He flexed his left knee" | | 14 | "His finger traced a seam" | | 15 | "Her glass paused mid-air." | | 16 | "She set it down slow," | | 17 | "Her pulse kicked." | | 18 | "She leaned forward, voice level." | | 19 | "He met her stare" |
| | ratio | 0.436 | |
| 11.28% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 78 | | matches | | 0 | "Rory's pint glass cracked against" | | 1 | "She wiped her hand on" | | 2 | "Maps curled at the edges" | | 3 | "A couple in the corner" | | 4 | "Hazel eyes locked on hers" | | 5 | "Silas Blackwood straightened, his silver" | | 6 | "He limped forward, each step" | | 7 | "She froze, fingers tightening on" | | 8 | "The voice cut clean, like" | | 9 | "Years stripped away in that" | | 10 | "She slid cash across the" | | 11 | "He poured without breaking gaze," | | 12 | "The pint landed precise, no" | | 13 | "He leaned in, elbows planted" | | 14 | "She sipped, the bitter hop" | | 15 | "Her blue eyes flicked to" | | 16 | "His laugh scraped low, like" | | 17 | "The signet ring tapped the" | | 18 | "She traced the crescent scar" | | 19 | "He slid a bowl of" |
| | ratio | 0.897 | |
| 64.10% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 78 | | matches | | 0 | "As if she'd chosen this" |
| | ratio | 0.013 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 5 | | matches | | 0 | "The signet ring tapped, deliberate" | | 1 | "He flexed, unseen" | | 2 | "She set, foam settling" | | 3 | "Truth clawed, unspoken" | | 4 | "His voice iced, spymaster resurfacing" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "His voice slurred (slur)" | | 1 | "Silas barked (bark)" |
| | dialogueSentences | 42 | | tagDensity | 0.048 | | leniency | 0.095 | | rawRatio | 1 | | effectiveRatio | 0.095 | |