| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 18 | | tagDensity | 0.278 | | leniency | 0.556 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.50% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1579 | | totalAiIsmAdverbs | 3 | | found | | 0 | | adverb | "reluctantly" | | count | 1 |
| | 1 | |
| | highlights | | |
| 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) | |
| 77.83% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1579 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "familiar" | | 1 | "pulsed" | | 2 | "jaw clenched" | | 3 | "glistening" | | 4 | "footsteps" | | 5 | "echoed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 143 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 143 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 157 | | 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 | 1579 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 80.65% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1442 | | uniqueNames | 12 | | maxNameDensity | 1.39 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Herrera" | | discoveredNames | | Camden | 3 | | High | 1 | | Street | 1 | | Veil | 1 | | Market | 1 | | Morris | 4 | | Raven | 1 | | Nest | 1 | | Tube | 1 | | Herrera | 4 | | Quinn | 20 | | Seville | 1 |
| | persons | | 0 | "Market" | | 1 | "Morris" | | 2 | "Herrera" | | 3 | "Quinn" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Veil" | | 4 | "Raven" | | 5 | "Seville" |
| | globalScore | 0.807 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 104 | | glossingSentenceCount | 2 | | matches | | 0 | "from reacting visibly" | | 1 | "looked like dried blood" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.633 | | wordCount | 1579 | | matches | | 0 | "Not the paramedic himself, but someone connected" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 157 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 51 | | mean | 30.96 | | std | 19.36 | | cv | 0.625 | | sampleLengths | | 0 | 52 | | 1 | 4 | | 2 | 63 | | 3 | 52 | | 4 | 1 | | 5 | 55 | | 6 | 49 | | 7 | 47 | | 8 | 8 | | 9 | 62 | | 10 | 43 | | 11 | 8 | | 12 | 41 | | 13 | 44 | | 14 | 68 | | 15 | 1 | | 16 | 50 | | 17 | 11 | | 18 | 53 | | 19 | 26 | | 20 | 2 | | 21 | 39 | | 22 | 8 | | 23 | 30 | | 24 | 2 | | 25 | 16 | | 26 | 44 | | 27 | 4 | | 28 | 45 | | 29 | 33 | | 30 | 50 | | 31 | 39 | | 32 | 17 | | 33 | 29 | | 34 | 31 | | 35 | 4 | | 36 | 21 | | 37 | 53 | | 38 | 4 | | 39 | 48 | | 40 | 47 | | 41 | 48 | | 42 | 34 | | 43 | 38 | | 44 | 29 | | 45 | 33 | | 46 | 10 | | 47 | 6 | | 48 | 27 | | 49 | 17 |
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| 97.90% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 143 | | matches | | 0 | "been seen" | | 1 | "been converted" | | 2 | "was, ducked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 254 | | matches | | 0 | "was heading" | | 1 | "weren't looking" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 157 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 548 | | adjectiveStacks | 1 | | stackExamples | | 0 | "Below, faint green light pulsed" |
| | adverbCount | 17 | | adverbRatio | 0.03102189781021898 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.005474452554744526 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 157 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 157 | | mean | 10.06 | | std | 5.88 | | cv | 0.585 | | sampleLengths | | 0 | 6 | | 1 | 15 | | 2 | 15 | | 3 | 13 | | 4 | 3 | | 5 | 4 | | 6 | 11 | | 7 | 2 | | 8 | 24 | | 9 | 15 | | 10 | 11 | | 11 | 7 | | 12 | 3 | | 13 | 2 | | 14 | 1 | | 15 | 24 | | 16 | 2 | | 17 | 13 | | 18 | 1 | | 19 | 9 | | 20 | 4 | | 21 | 23 | | 22 | 12 | | 23 | 7 | | 24 | 8 | | 25 | 15 | | 26 | 3 | | 27 | 14 | | 28 | 9 | | 29 | 8 | | 30 | 6 | | 31 | 3 | | 32 | 3 | | 33 | 10 | | 34 | 17 | | 35 | 8 | | 36 | 15 | | 37 | 1 | | 38 | 1 | | 39 | 1 | | 40 | 9 | | 41 | 12 | | 42 | 9 | | 43 | 14 | | 44 | 9 | | 45 | 13 | | 46 | 21 | | 47 | 8 | | 48 | 9 | | 49 | 16 |
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| 71.76% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.445859872611465 | | totalSentences | 157 | | uniqueOpeners | 70 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 131 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 131 | | matches | | 0 | "She powered forward, boots slapping" | | 1 | "He clutched a small canvas" | | 2 | "Her worn leather watch bounced" | | 3 | "He was fast, but she" | | 4 | "She saw the scar on" | | 5 | "She had seen that mark" | | 6 | "He was heading for the" | | 7 | "She knew the rumours about" | | 8 | "Her gut tightened." | | 9 | "She took the steps two" | | 10 | "Their canvas awnings hung heavy," | | 11 | "She had spotted him leaving" | | 12 | "Their eyes met across twenty" | | 13 | "He looked younger close up," | | 14 | "she snapped at a cluster" | | 15 | "They did, but slowly, their" | | 16 | "She rounded the stall and" | | 17 | "His hands shook as he" | | 18 | "She grabbed his shoulder and" | | 19 | "His warm brown eyes darted" |
| | ratio | 0.282 | |
| 47.79% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 108 | | totalSentences | 131 | | matches | | 0 | "Quinn's hand closed on empty" | | 1 | "The suspect twisted left, slamming" | | 2 | "She powered forward, boots slapping" | | 3 | "This one had." | | 4 | "The man glanced back, eyes" | | 5 | "He clutched a small canvas" | | 6 | "Quinn followed, years of drills" | | 7 | "Her worn leather watch bounced" | | 8 | "He was fast, but she" | | 9 | "The gap narrowed." | | 10 | "She saw the scar on" | | 11 | "She had seen that mark" | | 12 | "The name rose unbidden, but" | | 13 | "The suspect ducked into a" | | 14 | "Quinn took the corner tight," | | 15 | "A rat skittered away from" | | 16 | "He was heading for the" | | 17 | "She knew the rumours about" | | 18 | "Her gut tightened." | | 19 | "The man disappeared down a" |
| | ratio | 0.824 | |
| 38.17% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 131 | | matches | | 0 | "Now this man, this connected" |
| | ratio | 0.008 | |
| 90.34% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 68 | | technicalSentenceCount | 5 | | matches | | 0 | "The suspect twisted left, slamming a shoulder into a pedestrian who cursed and stumbled aside." | | 1 | "His voice carried traces of Seville, soft consonants that didn't match the panic in his face." | | 2 | "Quinn's grip tightened, her military bearing the only thing keeping her from reacting visibly." | | 3 | "Something inside called to the part of her that had never accepted Morris's official cause of death." | | 4 | "Her boots pounded ancient concrete as she climbed a spiraling metal staircase that hadn't seen proper maintenance since the war." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 2 | | matches | | 0 | "She had, his movements too furtive to ignore" | | 1 | "she said, voice steady with military precision" |
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| 38.89% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "she snapped (snap)" | | 1 | "he hissed (hiss)" |
| | dialogueSentences | 18 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0.667 | | effectiveRatio | 0.222 | |