| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 1 | | adverbTags | | 0 | "Aurora said softly [softly]" |
| | dialogueSentences | 37 | | tagDensity | 0.378 | | leniency | 0.757 | | rawRatio | 0.071 | | effectiveRatio | 0.054 | |
| 89.78% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1467 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | |
| 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) | |
| 45.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1467 | | totalAiIsms | 16 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | word | "calloused fingers" | | count | 1 |
| | 7 | | word | "practiced ease" | | count | 1 |
| | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | |
| | highlights | | 0 | "pulsed" | | 1 | "mechanical" | | 2 | "footsteps" | | 3 | "echoed" | | 4 | "etching" | | 5 | "crystal" | | 6 | "calloused fingers" | | 7 | "practiced ease" | | 8 | "looming" | | 9 | "chaotic" | | 10 | "navigate" | | 11 | "profound" | | 12 | "whisper" | | 13 | "stark" | | 14 | "weight" | | 15 | "sentinel" |
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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 | 91 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 91 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 114 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1461 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 1165 | | uniqueNames | 11 | | maxNameDensity | 1.46 | | worstName | "Silas" | | maxWindowNameDensity | 4 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Carter | 1 | | Golden | 2 | | Empress | 2 | | Silas | 17 | | Blackwood | 1 | | Aurora | 15 | | London | 2 | | Cardiff | 1 | | Eva | 3 |
| | persons | | 0 | "Raven" | | 1 | "Carter" | | 2 | "Silas" | | 3 | "Blackwood" | | 4 | "Aurora" | | 5 | "Eva" |
| | places | | 0 | "Golden" | | 1 | "London" | | 2 | "Cardiff" |
| | globalScore | 0.77 | | windowScore | 0.333 | |
| 45.83% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 3 | | matches | | 0 | "felt like a thunderstorm" | | 1 | "looked like a man carrying a satchel full" | | 2 | "looked like a man who had sold his soul f" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.684 | | wordCount | 1461 | | matches | | 0 | "not looking at her but at the map of the world taped to the wall behind her" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 114 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 33.2 | | std | 32.86 | | cv | 0.99 | | sampleLengths | | 0 | 131 | | 1 | 8 | | 2 | 16 | | 3 | 2 | | 4 | 10 | | 5 | 24 | | 6 | 140 | | 7 | 18 | | 8 | 31 | | 9 | 40 | | 10 | 28 | | 11 | 2 | | 12 | 69 | | 13 | 21 | | 14 | 32 | | 15 | 16 | | 16 | 7 | | 17 | 34 | | 18 | 10 | | 19 | 4 | | 20 | 61 | | 21 | 12 | | 22 | 18 | | 23 | 24 | | 24 | 29 | | 25 | 31 | | 26 | 6 | | 27 | 55 | | 28 | 11 | | 29 | 45 | | 30 | 55 | | 31 | 119 | | 32 | 10 | | 33 | 9 | | 34 | 45 | | 35 | 51 | | 36 | 2 | | 37 | 6 | | 38 | 78 | | 39 | 11 | | 40 | 27 | | 41 | 4 | | 42 | 48 | | 43 | 61 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 91 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 196 | | matches | | 0 | "was standing was, watching" |
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| 17.54% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 4 | | flaggedSentences | 5 | | totalSentences | 114 | | ratio | 0.044 | | matches | | 0 | "The years hadn't just accumulated on him; they had settled into the lines of his face, etching deep maps into a forehead that had once been smooth." | | 1 | "\"Prague was a mess.\" He rubbed his thumb over the engraving on the ring—a cipher Aurora hadn't learned to read yet." | | 2 | "He was a statue of guilt; she was a hurricane of survival." | | 3 | "She was no longer the quiet girl with the crescent-shaped scar; she was a piece of debris floating in a river she didn't understand." | | 4 | "It wasn't pity; it was regret so heavy it seemed to pull at the floorboards of the bar." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1168 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.030821917808219176 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.011986301369863013 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 12.82 | | std | 8.11 | | cv | 0.633 | | sampleLengths | | 0 | 27 | | 1 | 19 | | 2 | 18 | | 3 | 19 | | 4 | 23 | | 5 | 25 | | 6 | 6 | | 7 | 1 | | 8 | 1 | | 9 | 12 | | 10 | 4 | | 11 | 2 | | 12 | 10 | | 13 | 4 | | 14 | 20 | | 15 | 16 | | 16 | 4 | | 17 | 22 | | 18 | 27 | | 19 | 18 | | 20 | 22 | | 21 | 31 | | 22 | 10 | | 23 | 8 | | 24 | 21 | | 25 | 10 | | 26 | 13 | | 27 | 14 | | 28 | 4 | | 29 | 9 | | 30 | 16 | | 31 | 12 | | 32 | 2 | | 33 | 15 | | 34 | 7 | | 35 | 17 | | 36 | 18 | | 37 | 12 | | 38 | 11 | | 39 | 10 | | 40 | 24 | | 41 | 8 | | 42 | 2 | | 43 | 9 | | 44 | 5 | | 45 | 7 | | 46 | 22 | | 47 | 12 | | 48 | 7 | | 49 | 3 |
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| 32.46% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.21052631578947367 | | totalSentences | 114 | | uniqueOpeners | 24 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 10.70% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 86 | | matches | | 0 | "Her knuckles brushed against a" | | 1 | "She was thirty minutes past" | | 2 | "She didn't turn around." | | 3 | "She recognized the cadence." | | 4 | "She turned, bracing herself." | | 5 | "His auburn hair was now" | | 6 | "He wore his usual suit," | | 7 | "He signaled to the empty" | | 8 | "She poured two fingers into" | | 9 | "He didn't drink it." | | 10 | "He just stared at the" | | 11 | "They were a dull hazel" | | 12 | "She leaned against the counter," | | 13 | "He looked smaller in person," | | 14 | "He used to tower over" | | 15 | "She twisted the cap off" | | 16 | "He reached for the glass" | | 17 | "He picked up the silver" | | 18 | "He rubbed his thumb over" | | 19 | "He turned fully to face" |
| | ratio | 0.523 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 86 | | matches | | 0 | "The neon green buzz of" | | 1 | "Aurora Carter swiped a damp" | | 2 | "Her knuckles brushed against a" | | 3 | "She was thirty minutes past" | | 4 | "The bags of takeout food" | | 5 | "Footsteps echoed on the worn" | | 6 | "Aurora paused, her hand hovering" | | 7 | "She didn't turn around." | | 8 | "The voice was gravel vibrating" | | 9 | "She recognized the cadence." | | 10 | "The way the consonants pulled" | | 11 | "Aurora straightened her spine, dropping" | | 12 | "She turned, bracing herself." | | 13 | "Silas stood in the doorway," | | 14 | "The years hadn't just accumulated" | | 15 | "His auburn hair was now" | | 16 | "The left leg of his" | | 17 | "He wore his usual suit," | | 18 | "Silas said, limping toward the" | | 19 | "He signaled to the empty" |
| | ratio | 0.977 | |
| 58.14% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 86 | | matches | | | ratio | 0.012 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 2 | | matches | | 0 | "He looked like a man who had sold his soul for survival, piece by piece, trade by trade." | | 1 | "She had learned to survive by shutting down the parts of herself that felt, by leaving the abusive boyfriend who told her she was a burden, by learning how to n…" |
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| 53.57% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 2 | | matches | | 0 | "She twisted, the plastic cracking with a sharp snap" | | 1 | "Aurora said, her voice flat" |
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| 95.95% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 2 | | fancyTags | | 0 | "Silas murmured (murmur)" | | 1 | "Silas confessed (confess)" |
| | dialogueSentences | 37 | | tagDensity | 0.243 | | leniency | 0.486 | | rawRatio | 0.222 | | effectiveRatio | 0.108 | |