| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1037 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 46.96% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1037 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "loomed" | | 1 | "familiar" | | 2 | "resonance" | | 3 | "flickered" | | 4 | "vibrated" | | 5 | "scanned" | | 6 | "silence" | | 7 | "weight" | | 8 | "traced" | | 9 | "rhythmic" |
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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 | 82 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 82 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 90 | | 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 | 1034 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.20% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 973 | | uniqueNames | 10 | | maxNameDensity | 1.34 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 1 | | Carter | 1 | | Grove | 1 | | London | 1 | | Heartstone | 2 | | Pendant | 1 | | Fae | 1 | | Hel | 1 | | Cardiff | 1 | | Rory | 13 |
| | persons | | 0 | "Carter" | | 1 | "Heartstone" | | 2 | "Fae" | | 3 | "Rory" |
| | places | | 0 | "Richmond" | | 1 | "Grove" | | 2 | "London" | | 3 | "Cardiff" |
| | globalScore | 0.832 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.901 | | wordCount | 1034 | | matches | | 0 | "neither rain nor" | | 1 | "not a voice, but the wet, sliding noise of raw beef pulled across butcher pap" | | 2 | "not from the trees, but from the darkness behind her heels" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 90 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 23.5 | | std | 15.87 | | cv | 0.675 | | sampleLengths | | 0 | 14 | | 1 | 42 | | 2 | 18 | | 3 | 14 | | 4 | 46 | | 5 | 33 | | 6 | 31 | | 7 | 11 | | 8 | 23 | | 9 | 46 | | 10 | 26 | | 11 | 40 | | 12 | 6 | | 13 | 18 | | 14 | 2 | | 15 | 35 | | 16 | 24 | | 17 | 14 | | 18 | 21 | | 19 | 32 | | 20 | 11 | | 21 | 63 | | 22 | 7 | | 23 | 19 | | 24 | 6 | | 25 | 24 | | 26 | 5 | | 27 | 65 | | 28 | 30 | | 29 | 6 | | 30 | 14 | | 31 | 25 | | 32 | 3 | | 33 | 33 | | 34 | 21 | | 35 | 5 | | 36 | 59 | | 37 | 16 | | 38 | 27 | | 39 | 15 | | 40 | 5 | | 41 | 38 | | 42 | 11 | | 43 | 30 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 82 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 145 | | matches | (empty) | |
| 15.87% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 1 | | flaggedSentences | 4 | | totalSentences | 90 | | ratio | 0.044 | | matches | | 0 | "The scent rolled over her tongue—sugared rot, honey poured over spoiled meat." | | 1 | "It had no distinct face—only two wet, luminous indentations where eyes should have sat, catching light that didn't exist in the grove." | | 2 | "Then the sound of dry leaves scraping the ground began again—not from the trees, but from the darkness behind her heels." | | 3 | "It did not fall; it drifted downward with sickening slowness, its elongated limbs unfolding like the legs of a drowning spider, descending straight toward the moss directly behind her shoulder." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 980 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.02346938775510204 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.006122448979591836 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 90 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 90 | | mean | 11.49 | | std | 7.24 | | cv | 0.63 | | sampleLengths | | 0 | 14 | | 1 | 16 | | 2 | 6 | | 3 | 20 | | 4 | 8 | | 5 | 10 | | 6 | 14 | | 7 | 18 | | 8 | 6 | | 9 | 22 | | 10 | 21 | | 11 | 12 | | 12 | 8 | | 13 | 12 | | 14 | 11 | | 15 | 11 | | 16 | 8 | | 17 | 15 | | 18 | 13 | | 19 | 12 | | 20 | 6 | | 21 | 15 | | 22 | 2 | | 23 | 9 | | 24 | 15 | | 25 | 4 | | 26 | 17 | | 27 | 19 | | 28 | 6 | | 29 | 18 | | 30 | 2 | | 31 | 2 | | 32 | 4 | | 33 | 24 | | 34 | 5 | | 35 | 5 | | 36 | 19 | | 37 | 14 | | 38 | 21 | | 39 | 9 | | 40 | 19 | | 41 | 1 | | 42 | 1 | | 43 | 1 | | 44 | 1 | | 45 | 2 | | 46 | 9 | | 47 | 4 | | 48 | 12 | | 49 | 23 |
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| 44.81% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.32222222222222224 | | totalSentences | 90 | | uniqueOpeners | 29 | |
| 44.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 75 | | matches | | | ratio | 0.013 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 75 | | matches | | 0 | "She spoke into the heavy" | | 1 | "She thumbed the screen off" | | 2 | "She stepped past the first" | | 3 | "Her boots sank an inch" | | 4 | "It vibrated with a faint," | | 5 | "It responded to tears in" | | 6 | "Her thumb traced the small" | | 7 | "She retrieved the sealed brass" | | 8 | "It moved at waist height," | | 9 | "Her bright blue eyes cut" | | 10 | "It lacked the jagged angles" | | 11 | "It possessed the smooth, tapering" | | 12 | "Her Heartstone surged from lukewarm" | | 13 | "It came from above." | | 14 | "It had no distinct face—only" | | 15 | "It hung inverted, knees tucked" | | 16 | "It did not drop." | | 17 | "It did not breathe." | | 18 | "It simply stared down at" | | 19 | "Her heel caught a submerged" |
| | ratio | 0.333 | |
| 40.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 75 | | matches | | 0 | "The ancient oak standing stones" | | 1 | "Aurora Carter ducked beneath a" | | 2 | "The hum of London traffic" | | 3 | "Rory adjusted the strap of" | | 4 | "The leather dug into her" | | 5 | "She spoke into the heavy" | | 6 | "The clearing spread wide under" | | 7 | "Bluebells and winter jasmine choked" | | 8 | "The scent rolled over her" | | 9 | "Rory pulled her phone from" | | 10 | "The screen flickered, the digital" | | 11 | "She thumbed the screen off" | | 12 | "She stepped past the first" | | 13 | "Her boots sank an inch" | | 14 | "Rory slipped two fingers under" | | 15 | "The thumb-sized crimson gem was" | | 16 | "It vibrated with a faint," | | 17 | "The stone did not heat" | | 18 | "It responded to tears in" | | 19 | "Rory scanned the treeline." |
| | ratio | 0.84 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 75 | | matches | (empty) | | ratio | 0 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 3 | | matches | | 0 | "The clearing spread wide under a sky devoid of stars, blanketed by a bruised purple mist that leaked neither rain nor moonlight." | | 1 | "It had no distinct face—only two wet, luminous indentations where eyes should have sat, catching light that didn't exist in the grove." | | 2 | "A low vibration rattled in its throat, humming at a frequency that made Rory's molars ache." |
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| 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 | |