| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.96% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1330 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slightly" | | 1 | "truly" | | 2 | "slowly" | | 3 | "perfectly" |
| |
| 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) | |
| 13.53% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1330 | | totalAiIsms | 23 | | found | | | highlights | | 0 | "flickered" | | 1 | "stomach" | | 2 | "chill" | | 3 | "weight" | | 4 | "silence" | | 5 | "pulsed" | | 6 | "warmth" | | 7 | "comforting" | | 8 | "whisper" | | 9 | "calculate" | | 10 | "familiar" | | 11 | "oppressive" | | 12 | "rhythmic" | | 13 | "searing" | | 14 | "gloom" | | 15 | "glint" | | 16 | "echoed" |
| |
| 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 | 1 | | narrationSentences | 122 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 122 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 122 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1330 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 2 | | matches | | 0 | "Focus, she told herself." | | 1 | "Who is there, she called out." |
| |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 1315 | | uniqueNames | 14 | | maxNameDensity | 0.91 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 2 | | Park | 2 | | Fae | 2 | | Grove | 1 | | Rory | 12 | | Earth | 1 | | Heartstone | 4 | | Golden | 1 | | Empress | 1 | | Yu-Fei | 1 | | Cheung | 1 | | London | 1 | | Hel | 2 | | You | 3 |
| | persons | | 0 | "Rory" | | 1 | "Heartstone" | | 2 | "Empress" | | 3 | "Yu-Fei" | | 4 | "Cheung" | | 5 | "You" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Fae" | | 3 | "Grove" | | 4 | "Golden" | | 5 | "London" | | 6 | "Hel" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 92 | | glossingSentenceCount | 1 | | matches | | 0 | "tasted like crushed mint and ozone" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1330 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 122 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 44.33 | | std | 35.81 | | cv | 0.808 | | sampleLengths | | 0 | 136 | | 1 | 111 | | 2 | 63 | | 3 | 95 | | 4 | 4 | | 5 | 74 | | 6 | 3 | | 7 | 77 | | 8 | 57 | | 9 | 6 | | 10 | 65 | | 11 | 6 | | 12 | 96 | | 13 | 40 | | 14 | 46 | | 15 | 19 | | 16 | 32 | | 17 | 8 | | 18 | 3 | | 19 | 6 | | 20 | 64 | | 21 | 45 | | 22 | 29 | | 23 | 9 | | 24 | 50 | | 25 | 56 | | 26 | 1 | | 27 | 10 | | 28 | 46 | | 29 | 73 |
| |
| 90.88% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 122 | | matches | | 0 | "was bathed" | | 1 | "was supposed" | | 2 | "being circled" | | 3 | "was obscured" | | 4 | "was gone" |
| |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 207 | | matches | | 0 | "was stretching" | | 1 | "was seeping" | | 2 | "was playing" | | 3 | "was testing" | | 4 | "was rippling" | | 5 | "were withering" | | 6 | "was opening" | | 7 | "was cooling" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 122 | | ratio | 0 | | matches | (empty) | |
| 84.80% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 122 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 7 | | adverbRatio | 0.05737704918032787 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.01639344262295082 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 122 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 122 | | mean | 10.9 | | std | 6.65 | | cv | 0.61 | | sampleLengths | | 0 | 17 | | 1 | 13 | | 2 | 16 | | 3 | 16 | | 4 | 2 | | 5 | 22 | | 6 | 7 | | 7 | 18 | | 8 | 25 | | 9 | 6 | | 10 | 10 | | 11 | 13 | | 12 | 20 | | 13 | 8 | | 14 | 18 | | 15 | 17 | | 16 | 9 | | 17 | 10 | | 18 | 7 | | 19 | 16 | | 20 | 24 | | 21 | 8 | | 22 | 2 | | 23 | 6 | | 24 | 14 | | 25 | 25 | | 26 | 10 | | 27 | 6 | | 28 | 24 | | 29 | 5 | | 30 | 11 | | 31 | 4 | | 32 | 16 | | 33 | 7 | | 34 | 6 | | 35 | 19 | | 36 | 10 | | 37 | 5 | | 38 | 11 | | 39 | 3 | | 40 | 2 | | 41 | 26 | | 42 | 11 | | 43 | 2 | | 44 | 7 | | 45 | 19 | | 46 | 10 | | 47 | 5 | | 48 | 16 | | 49 | 17 |
| |
| 31.97% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 22 | | diversityRatio | 0.27049180327868855 | | totalSentences | 122 | | uniqueOpeners | 33 | |
| 59.52% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 112 | | matches | | 0 | "Then, the pendant shifted." | | 1 | "Just the oppressive silence, and" |
| | ratio | 0.018 | |
| 84.29% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 112 | | matches | | 0 | "It was well past midnight," | | 1 | "She pushed a strand of" | | 2 | "She had known that before" | | 3 | "She would much rather be" | | 4 | "She stepped fully into the" | | 5 | "She was supposed to be" | | 6 | "She had come because of" | | 7 | "Her bright blue eyes, usually" | | 8 | "It was a heavy, suffocating" | | 9 | "It started as a faint" | | 10 | "She swallowed hard, the sound" | | 11 | "She turned her head slowly," | | 12 | "She told herself it was" | | 13 | "She took another step forward." | | 14 | "She slipped her fingers beneath" | | 15 | "It was not a word," | | 16 | "She had only walked twenty" | | 17 | "She picked up a smooth" | | 18 | "It landed with a dull" | | 19 | "You made mistakes." |
| | ratio | 0.339 | |
| 18.04% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 99 | | totalSentences | 112 | | matches | | 0 | "The air inside the boundary" | | 1 | "Rory paused, her boots sinking" | | 2 | "It was well past midnight," | | 3 | "She pushed a strand of" | | 4 | "The clock read two fourteen" | | 5 | "Time moved differently in the" | | 6 | "She had known that before" | | 7 | "She would much rather be" | | 8 | "She stepped fully into the" | | 9 | "Wildflowers bloomed in aggressive, impossible" | | 10 | "Rory rubbed the small, crescent-shaped" | | 11 | "She was supposed to be" | | 12 | "Eva always said Rory could" | | 13 | "Here, beneath the towering oaks," | | 14 | "She had come because of" | | 15 | "The Heartstone rested against her" | | 16 | "An unknown benefactor had left" | | 17 | "Tonight, it had begun to" | | 18 | "Rory walked deeper into the" | | 19 | "Her bright blue eyes, usually" |
| | ratio | 0.884 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 112 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 2 | | matches | | 0 | "The stone was hot, almost too hot to hold, vibrating with a low, sub-audible frequency that rattled her teeth." | | 1 | "It was testing the boundaries of her perception, slipping into the blind spots of her vision." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |