| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 24 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said quietly [quietly]" |
| | dialogueSentences | 44 | | tagDensity | 0.545 | | leniency | 1 | | rawRatio | 0.042 | | effectiveRatio | 0.042 | |
| 86.01% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1072 | | 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) | |
| 44.03% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1072 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "glinting" | | 1 | "silence" | | 2 | "traced" | | 3 | "calculated" | | 4 | "echoed" | | 5 | "mechanical" | | 6 | "whisper" | | 7 | "echoing" | | 8 | "footsteps" | | 9 | "thundered" | | 10 | "familiar" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 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 | 112 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1072 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 27 | | unquotedAttributions | 0 | | matches | (empty) | |
| 43.62% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 752 | | uniqueNames | 9 | | maxNameDensity | 2.13 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Golden | 1 | | Empress | 1 | | Raven | 1 | | Nest | 1 | | Cardiff | 1 | | Rory | 16 | | Eva | 1 | | Evan | 3 | | Silas | 13 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Eva" | | 4 | "Evan" | | 5 | "Silas" |
| | places | | | globalScore | 0.436 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.799 | | wordCount | 1072 | | matches | | 0 | "not to surprise, but to something colder, more calculated" | | 1 | "not food, but papers" | | 2 | "not to restrain, but to pull her toward the open secret room" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 112 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 64 | | mean | 16.75 | | std | 13.66 | | cv | 0.815 | | sampleLengths | | 0 | 17 | | 1 | 65 | | 2 | 7 | | 3 | 2 | | 4 | 41 | | 5 | 62 | | 6 | 26 | | 7 | 13 | | 8 | 6 | | 9 | 44 | | 10 | 26 | | 11 | 8 | | 12 | 45 | | 13 | 23 | | 14 | 6 | | 15 | 24 | | 16 | 6 | | 17 | 5 | | 18 | 30 | | 19 | 20 | | 20 | 15 | | 21 | 8 | | 22 | 8 | | 23 | 19 | | 24 | 7 | | 25 | 9 | | 26 | 5 | | 27 | 3 | | 28 | 25 | | 29 | 10 | | 30 | 38 | | 31 | 9 | | 32 | 8 | | 33 | 17 | | 34 | 18 | | 35 | 16 | | 36 | 4 | | 37 | 14 | | 38 | 20 | | 39 | 21 | | 40 | 10 | | 41 | 7 | | 42 | 22 | | 43 | 22 | | 44 | 3 | | 45 | 9 | | 46 | 8 | | 47 | 35 | | 48 | 15 | | 49 | 14 |
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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 | 0 | | totalVerbs | 139 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 112 | | ratio | 0 | | matches | (empty) | |
| 97.60% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 655 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.042748091603053436 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.010687022900763359 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 112 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 112 | | mean | 9.57 | | std | 7.18 | | cv | 0.75 | | sampleLengths | | 0 | 11 | | 1 | 6 | | 2 | 5 | | 3 | 24 | | 4 | 21 | | 5 | 15 | | 6 | 7 | | 7 | 2 | | 8 | 21 | | 9 | 20 | | 10 | 5 | | 11 | 29 | | 12 | 9 | | 13 | 19 | | 14 | 9 | | 15 | 17 | | 16 | 7 | | 17 | 6 | | 18 | 6 | | 19 | 4 | | 20 | 16 | | 21 | 4 | | 22 | 20 | | 23 | 7 | | 24 | 19 | | 25 | 8 | | 26 | 31 | | 27 | 14 | | 28 | 3 | | 29 | 20 | | 30 | 6 | | 31 | 11 | | 32 | 13 | | 33 | 6 | | 34 | 5 | | 35 | 3 | | 36 | 14 | | 37 | 13 | | 38 | 6 | | 39 | 14 | | 40 | 4 | | 41 | 11 | | 42 | 8 | | 43 | 8 | | 44 | 11 | | 45 | 2 | | 46 | 6 | | 47 | 7 | | 48 | 9 | | 49 | 5 |
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| 58.93% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.375 | | totalSentences | 112 | | uniqueOpeners | 42 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 67 | | matches | | 0 | "Instead, she pulled the container" | | 1 | "Then he reached across the" | | 2 | "Then a click echoed from" | | 3 | "Then the front door crashed" |
| | ratio | 0.06 | |
| 76.72% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 67 | | matches | | 0 | "He polished an empty glass" | | 1 | "She stepped back, letting her" | | 2 | "Her delivery uniform hung loose," | | 3 | "His neatly trimmed grey-streaked auburn" | | 4 | "She looked up then." | | 5 | "Her face, once round with" | | 6 | "His hazel eyes traced the" | | 7 | "She hadn't heard Eva's name" | | 8 | "He leaned closer" | | 9 | "She didn't answer." | | 10 | "She pressed them flat against" | | 11 | "His thumb brushed near the" | | 12 | "he said quietly" | | 13 | "They stood in the thick" | | 14 | "she said, turning the accusation" | | 15 | "Her voice dropped." | | 16 | "His expression shifted, not to" | | 17 | "She pointed to the envelope" | | 18 | "His jaw tightened." | | 19 | "He moved with surprising speed," |
| | ratio | 0.358 | |
| 57.01% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 67 | | matches | | 0 | "Rory set the Golden Empress" | | 1 | "The plastic rustled like dry" | | 2 | "Silas didn't turn at first." | | 3 | "He polished an empty glass" | | 4 | "The Raven's Nest smelled of" | | 5 | "She stepped back, letting her" | | 6 | "Her delivery uniform hung loose," | | 7 | "Silas set the glass down." | | 8 | "The slight limp in his" | | 9 | "His neatly trimmed grey-streaked auburn" | | 10 | "Rory's fingers tightened around the" | | 11 | "She looked up then." | | 12 | "Her face, once round with" | | 13 | "The crescent-shaped scar on her" | | 14 | "His hazel eyes traced the" | | 15 | "Rory's breath caught." | | 16 | "She hadn't heard Eva's name" | | 17 | "He leaned closer" | | 18 | "She didn't answer." | | 19 | "The smell of ginger and" |
| | ratio | 0.806 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 67 | | matches | (empty) | | ratio | 0 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 2 | | matches | | 0 | "The Raven's Nest smelled of old wood, stale tobacco, and something sharper, whiskey that had soaked into the floorboards over decades." | | 1 | "At six feet one, he carried quiet authority, the kind that made strangers straighten their shoulders without knowing why." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 24 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 81.82% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 22 | | fancyCount | 3 | | fancyTags | | 0 | "she lied (lie)" | | 1 | "Rory corrected (correct)" | | 2 | "he shouted (shout)" |
| | dialogueSentences | 44 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.136 | | effectiveRatio | 0.136 | |