| 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 | 1320 | | 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) | |
| 54.55% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1320 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "vibrated" | | 1 | "silence" | | 2 | "whisper" | | 3 | "warmth" | | 4 | "pulsed" | | 5 | "resonance" | | 6 | "weight" | | 7 | "measured" | | 8 | "echoed" | | 9 | "pulse" |
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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 | 95 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 95 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 101 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 5 | | totalWords | 1314 | | ratio | 0.004 | | matches | | 0 | "Clack." | | 1 | "Clack. Shhhk." | | 2 | "Clack." | | 3 | "clack" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 98.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1250 | | uniqueNames | 21 | | maxNameDensity | 1.04 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 13 | | London | 1 | | November | 1 | | Richmond | 2 | | Park | 2 | | Grove | 2 | | Isolde | 1 | | Greenwich | 1 | | Mean | 1 | | Time | 1 | | English | 1 | | Heathrow | 1 | | Yu-Fei | 1 | | Golden | 1 | | Empress | 1 | | Evan | 1 | | Heartstone | 2 | | Hel | 2 | | Fae | 2 | | Roman | 1 | | Iron | 1 |
| | persons | | 0 | "Rory" | | 1 | "November" | | 2 | "Isolde" | | 3 | "Yu-Fei" | | 4 | "Empress" | | 5 | "Evan" | | 6 | "Heartstone" | | 7 | "Roman" | | 8 | "Iron" |
| | places | | 0 | "London" | | 1 | "Richmond" | | 2 | "Park" | | 3 | "Grove" | | 4 | "Greenwich" | | 5 | "Time" | | 6 | "Fae" |
| | globalScore | 0.98 | | windowScore | 1 | |
| 85.90% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 78 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like shouting into a closet packed" | | 1 | "felt like a bead of sweat sliding benea" |
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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 | 1314 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 101 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 51 | | mean | 25.76 | | std | 20.78 | | cv | 0.807 | | sampleLengths | | 0 | 17 | | 1 | 24 | | 2 | 15 | | 3 | 6 | | 4 | 34 | | 5 | 18 | | 6 | 66 | | 7 | 4 | | 8 | 73 | | 9 | 1 | | 10 | 30 | | 11 | 84 | | 12 | 5 | | 13 | 21 | | 14 | 7 | | 15 | 38 | | 16 | 33 | | 17 | 55 | | 18 | 1 | | 19 | 17 | | 20 | 40 | | 21 | 2 | | 22 | 20 | | 23 | 22 | | 24 | 3 | | 25 | 11 | | 26 | 70 | | 27 | 8 | | 28 | 23 | | 29 | 54 | | 30 | 41 | | 31 | 13 | | 32 | 33 | | 33 | 12 | | 34 | 1 | | 35 | 9 | | 36 | 27 | | 37 | 46 | | 38 | 9 | | 39 | 33 | | 40 | 17 | | 41 | 38 | | 42 | 23 | | 43 | 1 | | 44 | 35 | | 45 | 16 | | 46 | 54 | | 47 | 8 | | 48 | 56 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 191 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 3 | | flaggedSentences | 8 | | totalSentences | 101 | | ratio | 0.079 | | matches | | 0 | "Not the dead-battery icon, not the spinning wheel of a lost London network—glass gone dark as slate, cold enough to sting her fingertips." | | 1 | "That shift never bothered her on previous runs; Isolde’s pocket of turf operated on its own calendar, indifferent to Greenwich Mean Time or English winters." | | 2 | "Deliveries for Yu-Fei’s Golden Empress taught a person how to read bad postcodes after midnight; surviving Evan had taught her how to read a room before the first swing landed." | | 3 | "Warmth pulsed against her calloused palm—one beat, pause, another beat, out of sync with her own carotid artery." | | 4 | "It carried the wet, hollow resonance of two heavy billiard balls kissing—or knuckles cracking inside a leather glove." | | 5 | "Predators tracked panic; smart prey used peripheral rods instead of cones." | | 6 | "Warm rot washed over the back of Rory’s neck—stagnant pond water and copper pennies." | | 7 | "Not shadowed—drained to ash, curling inward at the edges where invisible soles had kissed the soil." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1270 | | adjectiveStacks | 1 | | stackExamples | | 0 | "empty, waist-high grass." |
| | adverbCount | 30 | | adverbRatio | 0.023622047244094488 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0015748031496062992 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 101 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 101 | | mean | 13.01 | | std | 8.5 | | cv | 0.654 | | sampleLengths | | 0 | 17 | | 1 | 24 | | 2 | 15 | | 3 | 6 | | 4 | 7 | | 5 | 4 | | 6 | 23 | | 7 | 10 | | 8 | 8 | | 9 | 20 | | 10 | 14 | | 11 | 7 | | 12 | 25 | | 13 | 4 | | 14 | 25 | | 15 | 6 | | 16 | 10 | | 17 | 11 | | 18 | 21 | | 19 | 1 | | 20 | 8 | | 21 | 11 | | 22 | 11 | | 23 | 18 | | 24 | 9 | | 25 | 27 | | 26 | 30 | | 27 | 5 | | 28 | 21 | | 29 | 7 | | 30 | 14 | | 31 | 5 | | 32 | 19 | | 33 | 15 | | 34 | 18 | | 35 | 3 | | 36 | 23 | | 37 | 5 | | 38 | 9 | | 39 | 15 | | 40 | 1 | | 41 | 17 | | 42 | 12 | | 43 | 4 | | 44 | 6 | | 45 | 18 | | 46 | 1 | | 47 | 1 | | 48 | 5 | | 49 | 15 |
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| 99.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.6138613861386139 | | totalSentences | 101 | | uniqueOpeners | 62 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 88 | | matches | | 0 | "Even the distant, permanent bass-note" | | 1 | "Then the metal bit in." | | 2 | "Just the split-crown marker leaning" |
| | ratio | 0.034 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 88 | | matches | | 0 | "She shoved the handset into" | | 1 | "Her boot heels sank into" | | 2 | "Her voice died three feet" | | 3 | "It sounded like shouting into" | | 4 | "She kept her breathing level," | | 5 | "It carried the wet, hollow" | | 6 | "She knew their spacing by" | | 7 | "Her gaze snapped toward ten" | | 8 | "She stared straight at the" | | 9 | "She stared dead ahead at" | | 10 | "It paced the perimeter between" | | 11 | "She set the waxed package" | | 12 | "She thumbed the torch clipped" |
| | ratio | 0.148 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 88 | | matches | | 0 | "Frost crunched under Rory’s boots" | | 1 | "Static chewed through the speaker" | | 2 | "A low pop vibrated against" | | 3 | "The screen went black." | | 4 | "She shoved the handset into" | | 5 | "That shift never bothered her" | | 6 | "The silence bothered her." | | 7 | "Every past visit greeted Rory" | | 8 | "Tonight, the clearing swallowed sound" | | 9 | "Her boot heels sank into" | | 10 | "Her voice died three feet" | | 11 | "It sounded like shouting into" | | 12 | "Rory shifted the waxed-canvas parcel" | | 13 | "She kept her breathing level," | | 14 | "Deliveries for Yu-Fei’s Golden Empress" | | 15 | "This clearing had teeth bared." | | 16 | "Heat pricked the hollow of" | | 17 | "Rory hooked a finger under" | | 18 | "Warmth pulsed against her calloused" | | 19 | "Rory’s jaw tightened." |
| | ratio | 0.534 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 88 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 56 | | technicalSentenceCount | 1 | | matches | | 0 | "Between the twin entrance oaks, blocking the frost-rimmed grass of Richmond Park, stood an eighth monolith that possessed no bark, swaying from side to side in …" |
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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 | |