| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 19 | | tagDensity | 0.368 | | leniency | 0.737 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 73.46% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 942 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "softly" | | 1 | "completely" | | 2 | "very" | | 3 | "gently" |
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| 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) | |
| 52.23% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 942 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "throb" | | 1 | "gloom" | | 2 | "footsteps" | | 3 | "warmth" | | 4 | "pulse" | | 5 | "quickened" | | 6 | "whisper" | | 7 | "shimmered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 61 | | matches | (empty) | |
| 72.60% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 61 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 73 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 942 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 99.87% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 798 | | uniqueNames | 10 | | maxNameDensity | 1 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 8 | | Carter | 1 | | Richmond | 1 | | Hill | 1 | | Nyx | 4 | | Isolde | 5 | | Heartstone | 1 | | Hel | 1 | | Fae | 1 | | Veil | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Carter" | | 2 | "Nyx" | | 3 | "Isolde" |
| | places | | | globalScore | 0.999 | | windowScore | 1 | |
| 47.96% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 2 | | matches | | 0 | "hum that seemed to rise from the stones themselves" | | 1 | "seemed loud" |
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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 | 942 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 73 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 29.44 | | std | 23.28 | | cv | 0.791 | | sampleLengths | | 0 | 75 | | 1 | 27 | | 2 | 53 | | 3 | 53 | | 4 | 16 | | 5 | 5 | | 6 | 2 | | 7 | 61 | | 8 | 4 | | 9 | 60 | | 10 | 5 | | 11 | 93 | | 12 | 9 | | 13 | 45 | | 14 | 25 | | 15 | 42 | | 16 | 36 | | 17 | 8 | | 18 | 23 | | 19 | 4 | | 20 | 11 | | 21 | 24 | | 22 | 47 | | 23 | 17 | | 24 | 47 | | 25 | 26 | | 26 | 4 | | 27 | 12 | | 28 | 55 | | 29 | 8 | | 30 | 17 | | 31 | 28 |
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| 93.76% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 61 | | matches | | 0 | "being plucked" | | 1 | "being poured" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 131 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 73 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 801 | | adjectiveStacks | 1 | | stackExamples | | 0 | "beside frost-bright crocuses," |
| | adverbCount | 28 | | adverbRatio | 0.03495630461922597 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.01373283395755306 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 73 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 73 | | mean | 12.9 | | std | 7.75 | | cv | 0.6 | | sampleLengths | | 0 | 34 | | 1 | 9 | | 2 | 3 | | 3 | 6 | | 4 | 23 | | 5 | 9 | | 6 | 10 | | 7 | 8 | | 8 | 22 | | 9 | 24 | | 10 | 7 | | 11 | 22 | | 12 | 22 | | 13 | 9 | | 14 | 4 | | 15 | 12 | | 16 | 5 | | 17 | 2 | | 18 | 12 | | 19 | 20 | | 20 | 8 | | 21 | 21 | | 22 | 4 | | 23 | 9 | | 24 | 14 | | 25 | 15 | | 26 | 22 | | 27 | 5 | | 28 | 17 | | 29 | 6 | | 30 | 19 | | 31 | 14 | | 32 | 37 | | 33 | 9 | | 34 | 16 | | 35 | 13 | | 36 | 16 | | 37 | 8 | | 38 | 17 | | 39 | 6 | | 40 | 14 | | 41 | 22 | | 42 | 14 | | 43 | 9 | | 44 | 13 | | 45 | 8 | | 46 | 9 | | 47 | 14 | | 48 | 4 | | 49 | 11 |
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| 75.80% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.4794520547945205 | | totalSentences | 73 | | uniqueOpeners | 35 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 55 | | matches | | 0 | "Then she saw the flowers." | | 1 | "Only a warmth, faint and" |
| | ratio | 0.036 | |
| 74.55% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 55 | | matches | | 0 | "She had not looked back" | | 1 | "Her left wrist ached where" | | 2 | "She pulled her sleeve down" | | 3 | "Their eyes were faint violet" | | 4 | "She was already walking between" | | 5 | "Her footsteps made no sound" | | 6 | "It was warmer, and it" | | 7 | "She heard her breath, the" | | 8 | "They covered the clearing in" | | 9 | "She had stopped beneath a" | | 10 | "Her fingers found the Heartstone" | | 11 | "It was not a dramatic" | | 12 | "She had felt it twice" | | 13 | "She drew it out of" | | 14 | "Her silver chain was cold" | | 15 | "It rose in pitch, then" | | 16 | "Her skin prickled." | | 17 | "She drew the Fae blade" | | 18 | "She took one step toward" | | 19 | "She glanced back at the" |
| | ratio | 0.364 | |
| 78.18% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 42 | | totalSentences | 55 | | matches | | 0 | "The oak stones stood in" | | 1 | "The traffic on Richmond Hill" | | 2 | "She had not looked back" | | 3 | "Aurora stopped at the boundary," | | 4 | "Her left wrist ached where" | | 5 | "She pulled her sleeve down" | | 6 | "Their eyes were faint violet" | | 7 | "The voice seemed to come" | | 8 | "Isolde laughed softly, and the" | | 9 | "She was already walking between" | | 10 | "Her footsteps made no sound" | | 11 | "Aurora swallowed and followed." | | 12 | "The moment she crossed the" | | 13 | "It was warmer, and it" | | 14 | "The noise of the world" | | 15 | "She heard her breath, the" | | 16 | "They covered the clearing in" | | 17 | "Foxgloves stood taller than her" | | 18 | "Bluebells curled up the trunks" | | 19 | "Butterflies drifted through them, but" |
| | ratio | 0.764 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 55 | | matches | (empty) | | ratio | 0 | |
| 81.63% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 3 | | matches | | 0 | "There was only the wind moving through the bracken, and the faint, almost musical hum that seemed to rise from the stones themselves." | | 1 | "Butterflies drifted through them, but their wings were the colour of stained glass, and when one passed through a shaft of light it left a faint trail that hung…" | | 2 | "Ahead, the clearing narrowed into a path between two trees that leaned together like conspirators, and beyond them the air shimmered faintly, a distortion like …" |
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| 53.57% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 1 | | matches | | 0 | "Isolde said, not unkindly" |
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| 44.74% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 2 | | fancyTags | | 0 | "Nyx whispered (whisper)" | | 1 | "they murmured (murmur)" |
| | dialogueSentences | 19 | | tagDensity | 0.368 | | leniency | 0.737 | | rawRatio | 0.286 | | effectiveRatio | 0.211 | |