| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 75.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1241 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "suddenly" | | 1 | "slowly" | | 2 | "completely" | | 3 | "utterly" |
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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) | |
| 3.30% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1241 | | totalAiIsms | 24 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | |
| | highlights | | 0 | "chill" | | 1 | "warmth" | | 2 | "pulse" | | 3 | "pulsed" | | 4 | "familiar" | | 5 | "velvet" | | 6 | "navigated" | | 7 | "chaotic" | | 8 | "rhythmic" | | 9 | "silk" | | 10 | "echo" | | 11 | "measured" | | 12 | "flickered" | | 13 | "parameters" | | 14 | "comforting" | | 15 | "footsteps" | | 16 | "weight" | | 17 | "silence" | | 18 | "could feel" | | 19 | "structure" | | 20 | "fractured" | | 21 | "aligned" |
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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 | 141 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 141 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 141 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1241 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 14 | | wordCount | 1241 | | uniqueNames | 9 | | maxNameDensity | 0.24 | | worstName | "London" | | maxWindowNameDensity | 1 | | worstWindowName | "London" | | discoveredNames | | Carter | 2 | | Park | 1 | | Heartstone | 1 | | Yu-Fei | 1 | | Soho | 1 | | London | 3 | | Hel | 1 | | Thames | 1 | | Aurora | 3 |
| | persons | | 0 | "Carter" | | 1 | "Yu-Fei" | | 2 | "Aurora" |
| | places | | 0 | "Park" | | 1 | "Soho" | | 2 | "London" | | 3 | "Thames" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | glossingSentenceCount | 1 | | matches | | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 4 | | per1kWords | 3.223 | | wordCount | 1241 | | matches | | 0 | "not a believer in doorways, but she was a believer in patterns" | | 1 | "not with heat, but with a strange, localized humidity" | | 2 | "not to strike, not to speak, but to witness" | | 3 | "not to speak, but to witness" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 141 | | matches | (empty) | |
| 58.35% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 13 | | mean | 95.46 | | std | 33.82 | | cv | 0.354 | | sampleLengths | | 0 | 93 | | 1 | 143 | | 2 | 112 | | 3 | 74 | | 4 | 4 | | 5 | 109 | | 6 | 124 | | 7 | 129 | | 8 | 68 | | 9 | 99 | | 10 | 76 | | 11 | 100 | | 12 | 110 |
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| 90.33% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 141 | | matches | | 0 | "being pulled" | | 1 | "was plastered" | | 2 | "been suspended" | | 3 | "was accompanied" | | 4 | "been called" | | 5 | "were named" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 208 | | matches | | 0 | "was already stirring" | | 1 | "was marking" | | 2 | "was staying" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 141 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1248 | | adjectiveStacks | 1 | | stackExamples | | 0 | "sudden, ice-cold clarity." |
| | adverbCount | 48 | | adverbRatio | 0.038461538461538464 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.008814102564102564 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 141 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 141 | | mean | 8.8 | | std | 7.88 | | cv | 0.895 | | sampleLengths | | 0 | 29 | | 1 | 12 | | 2 | 15 | | 3 | 10 | | 4 | 27 | | 5 | 4 | | 6 | 2 | | 7 | 14 | | 8 | 4 | | 9 | 1 | | 10 | 3 | | 11 | 11 | | 12 | 9 | | 13 | 15 | | 14 | 33 | | 15 | 9 | | 16 | 4 | | 17 | 34 | | 18 | 6 | | 19 | 4 | | 20 | 23 | | 21 | 18 | | 22 | 6 | | 23 | 10 | | 24 | 9 | | 25 | 15 | | 26 | 3 | | 27 | 2 | | 28 | 16 | | 29 | 3 | | 30 | 7 | | 31 | 2 | | 32 | 1 | | 33 | 12 | | 34 | 16 | | 35 | 5 | | 36 | 22 | | 37 | 4 | | 38 | 2 | | 39 | 4 | | 40 | 5 | | 41 | 6 | | 42 | 14 | | 43 | 2 | | 44 | 1 | | 45 | 1 | | 46 | 1 | | 47 | 13 | | 48 | 2 | | 49 | 1 |
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| 45.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.3475177304964539 | | totalSentences | 141 | | uniqueOpeners | 49 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 119 | | matches | | 0 | "Instead, the clearing beyond the" | | 1 | "Then the sound came." | | 2 | "Completely, utterly silent." | | 3 | "Even the pendant had gone" | | 4 | "Then she felt it." | | 5 | "Just the distinct, undeniable certainty" |
| | ratio | 0.05 | |
| 38.49% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 54 | | totalSentences | 119 | | matches | | 0 | "She checked her phone." | | 1 | "She tucked it away." | | 2 | "She had followed the trail" | | 3 | "She was not a believer" | | 4 | "She stepped past the first" | | 5 | "It grew heavy, thick with" | | 6 | "Her coat felt suddenly too" | | 7 | "She had never said the" | | 8 | "Her boots sank into the" | | 9 | "She told herself it was" | | 10 | "She was twenty-five, worked late" | | 11 | "She did not panic." | | 12 | "It was not an animal." | | 13 | "It was too rhythmic, too" | | 14 | "It circulated the clearing, staying" | | 15 | "She turned her head slowly." | | 16 | "It was not empty." | | 17 | "It was attentive." | | 18 | "Her voice came out steady," | | 19 | "She should not have spoken." |
| | ratio | 0.454 | |
| 69.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 119 | | matches | | 0 | "The ancient oaks rose like" | | 1 | "Aurora Carter paused at the" | | 2 | "Richmond Park should have been" | | 3 | "Wildflowers spilled across the moss" | | 4 | "She checked her phone." | | 5 | "The time read 11:47, but" | | 6 | "She tucked it away." | | 7 | "The Heartstone, resting against her" | | 8 | "A faint warmth spread beneath" | | 9 | "She had followed the trail" | | 10 | "The door is open." | | 11 | "She was not a believer" | | 12 | "She stepped past the first" | | 13 | "The air changed instantly." | | 14 | "It grew heavy, thick with" | | 15 | "The temperature shifted upward, not" | | 16 | "Her coat felt suddenly too" | | 17 | "The warmth seeped into her" | | 18 | "She had never said the" | | 19 | "A Hel portal." |
| | ratio | 0.782 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 119 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 1 | | matches | | 0 | "The crescent-shaped scar from a childhood accident stung against the rough air, a sharp, grounding ache that anchored her to her own body." |
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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 | |