| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.90% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1615 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 7.12% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1615 | | totalAiIsms | 30 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "pulse" | | 1 | "scanned" | | 2 | "pulsed" | | 3 | "warmth" | | 4 | "etched" | | 5 | "stark" | | 6 | "traced" | | 7 | "stomach" | | 8 | "loomed" | | 9 | "constructed" | | 10 | "marble" | | 11 | "porcelain" | | 12 | "structure" | | 13 | "echoed" | | 14 | "silence" | | 15 | "trembled" | | 16 | "flickered" | | 17 | "shattered" |
| |
| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "clenched jaw/fists" | | count | 1 |
| | 2 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "clenched her jaw" | | 2 | "hung in the air" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 266 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 266 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 266 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 19 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1615 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 28 | | unquotedAttributions | 26 | | matches | | 0 | "Crossing this threshold binds you to the hunger, Nyx whispered." | | 1 | "The path winds where the appetite grows fat, Isolde said." | | 2 | "The skin itches, Aurora replied." | | 3 | "The roots drink deep, Isolde murmured." | | 4 | "We need to find the rift point, Aurora said." | | 5 | "The Wardens watch the cracks, Nyx replied." | | 6 | "Beauty fades when the appetite wins, Isolde said." | | 7 | "The shadows here taste of ash, Nyx said." | | 8 | "The vintage is old, Isolde said." | | 9 | "The portal is close, Aurora said." | | 10 | "The shadows speak, Nyx said." | | 11 | "Prince Belphegor, Aurora muttered." | | 12 | "The King of Gluttony does not wait for guests, Isolde said." | | 13 | "We need to move, Aurora said." | | 14 | "The path narrows, Nyx said." | | 15 | "One must pay the toll, Isolde said." | | 16 | "With what you carry, Isolde replied." | | 17 | "The lock is old, Nyx said." | | 18 | "We cut through the ward, Aurora said." | | 19 | "Cutting the ward invites the master, Isolde said." | | 20 | "We have no choice, Aurora said." | | 21 | "The hunger wakes, Nyx said." | | 22 | "Open them, Aurora said." | | 23 | "The door opens for the worthy, Isolde said." | | 24 | "We go in, Aurora said." | | 25 | "The meal begins, Isolde said." |
| |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 125 | | wordCount | 1615 | | uniqueNames | 19 | | maxNameDensity | 3.53 | | worstName | "Aurora" | | maxWindowNameDensity | 9 | | worstWindowName | "Aurora" | | discoveredNames | | Fae | 5 | | Grove | 1 | | Heartstone | 1 | | Pendant | 1 | | Shade | 2 | | Nyx | 19 | | Veil | 1 | | Isolde | 23 | | Half-Fae | 2 | | Richmond | 1 | | Park | 1 | | Aurora | 57 | | Fae-Forged | 2 | | Blade | 2 | | Wardens | 2 | | Prince | 2 | | Belphegor | 1 | | King | 1 | | Gluttony | 1 |
| | persons | | 0 | "Pendant" | | 1 | "Shade" | | 2 | "Nyx" | | 3 | "Veil" | | 4 | "Isolde" | | 5 | "Aurora" | | 6 | "Blade" | | 7 | "Wardens" | | 8 | "Prince" | | 9 | "Belphegor" | | 10 | "Gluttony" |
| | places | | 0 | "Fae" | | 1 | "Grove" | | 2 | "Half-Fae" | | 3 | "Richmond" | | 4 | "Park" |
| | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 125 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1615 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 266 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 144 | | mean | 11.22 | | std | 11.78 | | cv | 1.05 | | sampleLengths | | 0 | 68 | | 1 | 38 | | 2 | 19 | | 3 | 16 | | 4 | 31 | | 5 | 29 | | 6 | 53 | | 7 | 33 | | 8 | 21 | | 9 | 24 | | 10 | 36 | | 11 | 14 | | 12 | 40 | | 13 | 14 | | 14 | 16 | | 15 | 39 | | 16 | 27 | | 17 | 19 | | 18 | 14 | | 19 | 8 | | 20 | 37 | | 21 | 8 | | 22 | 36 | | 23 | 23 | | 24 | 14 | | 25 | 20 | | 26 | 6 | | 27 | 45 | | 28 | 17 | | 29 | 10 | | 30 | 4 | | 31 | 19 | | 32 | 15 | | 33 | 16 | | 34 | 21 | | 35 | 18 | | 36 | 9 | | 37 | 36 | | 38 | 14 | | 39 | 7 | | 40 | 4 | | 41 | 6 | | 42 | 17 | | 43 | 26 | | 44 | 13 | | 45 | 10 | | 46 | 24 | | 47 | 7 | | 48 | 13 | | 49 | 8 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 266 | | matches | | 0 | "were sealed" | | 1 | "was gone" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 349 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 266 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1620 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.012345679012345678 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.005555555555555556 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 266 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 266 | | mean | 6.07 | | std | 3.43 | | cv | 0.565 | | sampleLengths | | 0 | 10 | | 1 | 16 | | 2 | 8 | | 3 | 17 | | 4 | 17 | | 5 | 10 | | 6 | 9 | | 7 | 19 | | 8 | 10 | | 9 | 9 | | 10 | 3 | | 11 | 3 | | 12 | 10 | | 13 | 12 | | 14 | 8 | | 15 | 11 | | 16 | 10 | | 17 | 7 | | 18 | 12 | | 19 | 8 | | 20 | 15 | | 21 | 14 | | 22 | 16 | | 23 | 8 | | 24 | 10 | | 25 | 15 | | 26 | 4 | | 27 | 9 | | 28 | 8 | | 29 | 5 | | 30 | 5 | | 31 | 14 | | 32 | 8 | | 33 | 16 | | 34 | 6 | | 35 | 6 | | 36 | 6 | | 37 | 8 | | 38 | 8 | | 39 | 18 | | 40 | 7 | | 41 | 7 | | 42 | 9 | | 43 | 5 | | 44 | 7 | | 45 | 9 | | 46 | 6 | | 47 | 6 | | 48 | 10 | | 49 | 9 |
| |
| 36.47% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 36 | | diversityRatio | 0.14661654135338345 | | totalSentences | 266 | | uniqueOpeners | 39 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 248 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 57 | | totalSentences | 248 | | matches | | 0 | "She adjusted the strap of" | | 1 | "Their violet eyes glowed faintly" | | 2 | "She stepped forward." | | 3 | "She left no footprints on" | | 4 | "Her pale lavender eyes scanned" | | 5 | "Her tone remained level, smooth" | | 6 | "They bore fruit that pulsed" | | 7 | "She pulled her hand back." | | 8 | "They remember the taste of" | | 9 | "She held it low, ready" | | 10 | "We need to find the" | | 11 | "They do not watch the" | | 12 | "They moved deeper into the" | | 13 | "She clenched her jaw, ignoring" | | 14 | "They held plates of empty" | | 15 | "She kept her gaze fixed" | | 16 | "She glanced at Nyx." | | 17 | "Their violet eyes narrowed." | | 18 | "They reached a wide plaza." | | 19 | "Her fingers brushed the surface" |
| | ratio | 0.23 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 232 | | totalSentences | 248 | | matches | | 0 | "The shimmering distortion ahead rippled" | | 1 | "Aurora stopped on the edge" | | 2 | "The air tasted of ozone" | | 3 | "She adjusted the strap of" | | 4 | "The Heartstone Pendant grew warm" | | 5 | "Nyx stood beside her, a" | | 6 | "Their violet eyes glowed faintly" | | 7 | "The Shade shifted, their form" | | 8 | "The voice carried on the" | | 9 | "Aurora didn't flinch." | | 10 | "She stepped forward." | | 11 | "The Veil parted without resistance," | | 12 | "Isolde walked ahead, her silver" | | 13 | "She left no footprints on" | | 14 | "Her pale lavender eyes scanned" | | 15 | "The path winds where the" | | 16 | "Her tone remained level, smooth" | | 17 | "Aurora followed the Half-Fae into" | | 18 | "The sky above shifted from" | | 19 | "The ground beneath her boots" |
| | ratio | 0.935 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 248 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |