| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 27 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.98% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1497 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "completely" | | 1 | "perfectly" |
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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) | |
| 19.84% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1497 | | totalAiIsms | 24 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "roaring" | | 1 | "silence" | | 2 | "pulsed" | | 3 | "weight" | | 4 | "gloom" | | 5 | "intricate" | | 6 | "shattered" | | 7 | "long shadow" | | 8 | "calculated" | | 9 | "rhythmic" | | 10 | "whisper" | | 11 | "scanning" | | 12 | "treacherous" | | 13 | "perfect" | | 14 | "echoed" | | 15 | "predator" | | 16 | "anticipation" | | 17 | "throbbed" | | 18 | "footsteps" | | 19 | "methodical" |
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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 | 165 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 165 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 186 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1488 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 1346 | | uniqueNames | 13 | | maxNameDensity | 0.59 | | worstName | "Fae" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Fae" | | discoveredNames | | London | 1 | | Fae | 8 | | Grove | 4 | | Heartstone | 4 | | Park | 1 | | Earth | 1 | | Yu-Fei | 1 | | Golden | 1 | | Empress | 1 | | Hel | 3 | | Evan | 2 | | Black | 3 | | Clack | 3 |
| | persons | | 0 | "Heartstone" | | 1 | "Yu-Fei" | | 2 | "Empress" | | 3 | "Evan" |
| | places | | 0 | "London" | | 1 | "Fae" | | 2 | "Grove" | | 3 | "Park" | | 4 | "Golden" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 112 | | glossingSentenceCount | 1 | | matches | | 0 | "tasted like ash in my mouth" |
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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 | 1488 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 186 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 74 | | mean | 20.11 | | std | 15.87 | | cv | 0.789 | | sampleLengths | | 0 | 39 | | 1 | 47 | | 2 | 34 | | 3 | 43 | | 4 | 37 | | 5 | 4 | | 6 | 57 | | 7 | 8 | | 8 | 6 | | 9 | 39 | | 10 | 4 | | 11 | 54 | | 12 | 12 | | 13 | 33 | | 14 | 58 | | 15 | 20 | | 16 | 10 | | 17 | 3 | | 18 | 18 | | 19 | 19 | | 20 | 4 | | 21 | 26 | | 22 | 17 | | 23 | 7 | | 24 | 22 | | 25 | 8 | | 26 | 4 | | 27 | 27 | | 28 | 37 | | 29 | 26 | | 30 | 50 | | 31 | 12 | | 32 | 30 | | 33 | 16 | | 34 | 4 | | 35 | 11 | | 36 | 10 | | 37 | 5 | | 38 | 4 | | 39 | 9 | | 40 | 38 | | 41 | 27 | | 42 | 29 | | 43 | 21 | | 44 | 13 | | 45 | 9 | | 46 | 8 | | 47 | 6 | | 48 | 3 | | 49 | 60 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 165 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 207 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 186 | | ratio | 0 | | matches | (empty) | |
| 82.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1354 | | adjectiveStacks | 3 | | stackExamples | | 0 | "angry, bruised purple-red, casting" | | 1 | "small crescent-shaped scar" | | 2 | "terrifying huge ancient twisted grey Fae" |
| | adverbCount | 37 | | adverbRatio | 0.027326440177252585 | | lyAdverbCount | 23 | | lyAdverbRatio | 0.016986706056129987 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 186 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 186 | | mean | 8 | | std | 4.57 | | cv | 0.571 | | sampleLengths | | 0 | 17 | | 1 | 5 | | 2 | 17 | | 3 | 13 | | 4 | 6 | | 5 | 10 | | 6 | 10 | | 7 | 8 | | 8 | 16 | | 9 | 4 | | 10 | 4 | | 11 | 10 | | 12 | 4 | | 13 | 9 | | 14 | 5 | | 15 | 19 | | 16 | 6 | | 17 | 6 | | 18 | 8 | | 19 | 14 | | 20 | 9 | | 21 | 4 | | 22 | 8 | | 23 | 8 | | 24 | 6 | | 25 | 7 | | 26 | 28 | | 27 | 8 | | 28 | 6 | | 29 | 10 | | 30 | 8 | | 31 | 4 | | 32 | 9 | | 33 | 8 | | 34 | 4 | | 35 | 7 | | 36 | 7 | | 37 | 3 | | 38 | 21 | | 39 | 3 | | 40 | 3 | | 41 | 10 | | 42 | 12 | | 43 | 8 | | 44 | 1 | | 45 | 11 | | 46 | 10 | | 47 | 3 | | 48 | 6 | | 49 | 10 |
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| 40.86% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 24 | | diversityRatio | 0.3225806451612903 | | totalSentences | 186 | | uniqueOpeners | 60 | |
| 86.58% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 154 | | matches | | 0 | "Then, the stag flinched." | | 1 | "Only a specific sect of" | | 2 | "Even the magical hum of" | | 3 | "Just jagged, exposed teeth snapping" |
| | ratio | 0.026 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 46 | | totalSentences | 154 | | matches | | 0 | "I twisted my shoulder away" | | 1 | "I caught my balance and" | | 2 | "It pulsed with a dull" | | 3 | "I checked my watch." | | 4 | "I needed to finish this" | | 5 | "I marched deeper into the" | | 6 | "My mysterious benefactor made certain" | | 7 | "I gripped the heavy delivery" | | 8 | "Its antlers branched into intricate," | | 9 | "It radiated an aura of" | | 10 | "It didn't bleed." | | 11 | "It simply collapsed into a" | | 12 | "I pulled the collar of" | | 13 | "I tracked the ash cloud's" | | 14 | "It moved without disturbing a" | | 15 | "It slipped through the undergrowth" | | 16 | "It sounded exactly like long" | | 17 | "I adjusted my grip on" | | 18 | "I projected my voice toward" | | 19 | "It drifted from the canopy" |
| | ratio | 0.299 | |
| 24.94% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 134 | | totalSentences | 154 | | matches | | 0 | "I twisted my shoulder away" | | 1 | "Mud splattered against my calves." | | 2 | "The roaring hum of London" | | 3 | "I caught my balance and" | | 4 | "The Heartstone rested against my" | | 5 | "A faint inner glow radiated" | | 6 | "It pulsed with a dull" | | 7 | "A steady thump, thump, thump" | | 8 | "Richmond Park lay behind the" | | 9 | "Copper stung my tongue." | | 10 | "Ozone prickled my arms." | | 11 | "The atmosphere pressed down with" | | 12 | "I checked my watch." | | 13 | "The second hand ticked backwards," | | 14 | "Time held no authority here." | | 15 | "A single hour wandering these" | | 16 | "I needed to finish this" | | 17 | "I marched deeper into the" | | 18 | "Foxgloves and bluebells thrived in" | | 19 | "The pendant grew warmer." |
| | ratio | 0.87 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 154 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 2 | | matches | | 0 | "A job required doing, and Yu-Fei's hazard pay at the Golden Empress barely covered the cost of new boots, let alone risking my life investigating localized unna…" | | 1 | "The Fae Grove screamed, emitting a high-pitched frequency that rattled my teeth." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "The voice hissed (hiss)" |
| | dialogueSentences | 27 | | tagDensity | 0.037 | | leniency | 0.074 | | rawRatio | 1 | | effectiveRatio | 0.074 | |