| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 77.38% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1326 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "quickly" | | 1 | "slowly" | | 2 | "gently" | | 3 | "tightly" | | 4 | "very" | | 5 | "slightly" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 39.67% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1326 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "warmth" | | 1 | "electric" | | 2 | "silence" | | 3 | "measured" | | 4 | "weight" | | 5 | "traced" | | 6 | "sanctuary" | | 7 | "pulse" | | 8 | "flickered" | | 9 | "methodical" | | 10 | "familiar" | | 11 | "porcelain" |
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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) | |
| 99.57% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 5 | | hedgeCount | 0 | | narrationSentences | 165 | | filterMatches | | 0 | "look" | | 1 | "wonder" | | 2 | "think" | | 3 | "realize" |
| | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 165 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1326 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 8 | | matches | | 0 | "Rory, he said." | | 1 | "You survived, Silas said." | | 2 | "Do you ever miss it, she asked quietly." | | 3 | "Every day, he admitted." | | 4 | "I miss the idea of them, she said." | | 5 | "People diverge, Silas said." | | 6 | "Another, Silas asked, nodding to the bottle." | | 7 | "No, she said." |
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| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 1326 | | uniqueNames | 13 | | maxNameDensity | 0.83 | | worstName | "You" | | maxWindowNameDensity | 2.5 | | worstWindowName | "You" | | discoveredNames | | Soho | 1 | | London | 1 | | Empress | 1 | | Tuesday | 1 | | Aurora | 3 | | Evan | 1 | | Westminster | 1 | | Silas | 7 | | Cardiff | 1 | | Bristol | 1 | | Rory | 2 | | Time | 3 | | You | 11 |
| | persons | | 0 | "Aurora" | | 1 | "Evan" | | 2 | "Silas" | | 3 | "Rory" | | 4 | "Time" | | 5 | "You" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Westminster" | | 3 | "Cardiff" | | 4 | "Bristol" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1326 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 165 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 45.72 | | std | 32.18 | | cv | 0.704 | | sampleLengths | | 0 | 96 | | 1 | 86 | | 2 | 123 | | 3 | 16 | | 4 | 13 | | 5 | 27 | | 6 | 37 | | 7 | 21 | | 8 | 37 | | 9 | 6 | | 10 | 74 | | 11 | 11 | | 12 | 36 | | 13 | 75 | | 14 | 25 | | 15 | 56 | | 16 | 20 | | 17 | 24 | | 18 | 95 | | 19 | 15 | | 20 | 46 | | 21 | 67 | | 22 | 36 | | 23 | 43 | | 24 | 50 | | 25 | 78 | | 26 | 7 | | 27 | 8 | | 28 | 98 |
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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 | 1 | | totalVerbs | 269 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 165 | | ratio | 0.006 | | matches | | 0 | "He used to move like a blade drawn slowly from its scabbard; now he moved like a man accounting for every joint." |
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| 96.42% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1338 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 59 | | adverbRatio | 0.044095665171898356 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.01046337817638266 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 165 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 165 | | mean | 8.04 | | std | 6.26 | | cv | 0.78 | | sampleLengths | | 0 | 20 | | 1 | 17 | | 2 | 30 | | 3 | 9 | | 4 | 20 | | 5 | 10 | | 6 | 31 | | 7 | 10 | | 8 | 26 | | 9 | 9 | | 10 | 13 | | 11 | 5 | | 12 | 3 | | 13 | 26 | | 14 | 3 | | 15 | 18 | | 16 | 4 | | 17 | 26 | | 18 | 12 | | 19 | 13 | | 20 | 3 | | 21 | 8 | | 22 | 5 | | 23 | 5 | | 24 | 4 | | 25 | 4 | | 26 | 6 | | 27 | 21 | | 28 | 1 | | 29 | 12 | | 30 | 7 | | 31 | 5 | | 32 | 7 | | 33 | 5 | | 34 | 15 | | 35 | 2 | | 36 | 4 | | 37 | 2 | | 38 | 7 | | 39 | 19 | | 40 | 6 | | 41 | 3 | | 42 | 3 | | 43 | 3 | | 44 | 5 | | 45 | 4 | | 46 | 4 | | 47 | 13 | | 48 | 4 | | 49 | 13 |
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| 68.48% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.45454545454545453 | | totalSentences | 165 | | uniqueOpeners | 75 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 148 | | matches | | 0 | "Just packing a suitcase." | | 1 | "Sometimes I wonder if survival" | | 2 | "Instead, I just learned how" | | 3 | "Just changes shape." | | 4 | "Somewhere behind the bookshelf, a" |
| | ratio | 0.034 | |
| 36.22% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 68 | | totalSentences | 148 | | matches | | 0 | "She shook it off once," | | 1 | "She knew every crack in" | | 2 | "He didn't look up immediately." | | 3 | "He never did." | | 4 | "He was older." | | 5 | "He wore it like a" | | 6 | "Her name came out low," | | 7 | "You're dripping on my floors." | | 8 | "She smiled, thin and habitual." | | 9 | "I'll sweep them tomorrow." | | 10 | "I'm already paying rent." | | 11 | "He nodded toward the nearest" | | 12 | "She climbed onto the stool," | | 13 | "You look tired, Aurora." | | 14 | "She traced the rim of" | | 15 | "Her thumb found the crescent-shaped" | | 16 | "You dropped out." | | 17 | "It wasn't a dramatic exit." | | 18 | "She met his gaze." | | 19 | "Her bright blue eyes, usually" |
| | ratio | 0.459 | |
| 88.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 110 | | totalSentences | 148 | | matches | | 0 | "The green neon sign sputtered" | | 1 | "Aurora pushed through the heavy" | | 2 | "Rain had followed her all" | | 3 | "She shook it off once," | | 4 | "The cold air surrendered quickly" | | 5 | "She knew every crack in" | | 6 | "Maps lined the walls, sprawling" | | 7 | "Tonight, the shelf held nothing" | | 8 | "Silas stood behind the polished" | | 9 | "He didn't look up immediately." | | 10 | "He never did." | | 11 | "He was older." | | 12 | "Time had carved deeper lines" | | 13 | "The limp was worse." | | 14 | "He wore it like a" | | 15 | "Rory, he said." | | 16 | "Her name came out low," | | 17 | "You're dripping on my floors." | | 18 | "She smiled, thin and habitual." | | 19 | "I'll sweep them tomorrow." |
| | ratio | 0.743 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 148 | | matches | | 0 | "Now I'm just running between" | | 1 | "What you're feeling isn't failure." | | 2 | "If it didn't, you'd be" |
| | ratio | 0.02 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 3 | | matches | | 0 | "Beyond it, she knew, stood the heavy oak bookshelf that concealed the back room where men in dark coats whispered over encrypted files and compromised identitie…" | | 1 | "When he finally raised his eyes, they were still hazel, still holding that quiet, measured authority that had anchored her through three terrible winters in Lon…" | | 2 | "She thought of her own wrists, slender and marked by time, by panic attacks, by carrying heavy bags up stairwells that didn't have railings." |
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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 | |