| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 51 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 123 | | tagDensity | 0.415 | | leniency | 0.829 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.69% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2148 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "gently" | | 1 | "slightly" | | 2 | "completely" | | 3 | "slowly" |
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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) | |
| 53.45% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2148 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "flickered" | | 1 | "vibrated" | | 2 | "scanned" | | 3 | "etched" | | 4 | "echoed" | | 5 | "standard" | | 6 | "whisper" | | 7 | "pulse" | | 8 | "pulsed" | | 9 | "silence" | | 10 | "etching" | | 11 | "trembled" | | 12 | "could feel" | | 13 | "loomed" |
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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 | 274 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 5 | | narrationSentences | 274 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 346 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 21 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2148 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 45 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 115 | | wordCount | 1592 | | uniqueNames | 10 | | maxNameDensity | 3.96 | | worstName | "Quinn" | | maxWindowNameDensity | 6 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 63 | | Kowalski | 1 | | Eva | 41 | | Veil | 3 | | Market | 1 | | Camden | 1 | | Compass | 2 | | Tube | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 123 | | 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 | 2148 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 346 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 147 | | mean | 14.61 | | std | 12.11 | | cv | 0.829 | | sampleLengths | | 0 | 71 | | 1 | 40 | | 2 | 17 | | 3 | 46 | | 4 | 18 | | 5 | 27 | | 6 | 44 | | 7 | 31 | | 8 | 13 | | 9 | 46 | | 10 | 10 | | 11 | 37 | | 12 | 8 | | 13 | 32 | | 14 | 43 | | 15 | 15 | | 16 | 9 | | 17 | 9 | | 18 | 20 | | 19 | 31 | | 20 | 25 | | 21 | 8 | | 22 | 43 | | 23 | 5 | | 24 | 4 | | 25 | 2 | | 26 | 30 | | 27 | 15 | | 28 | 26 | | 29 | 17 | | 30 | 26 | | 31 | 7 | | 32 | 38 | | 33 | 16 | | 34 | 13 | | 35 | 14 | | 36 | 8 | | 37 | 21 | | 38 | 33 | | 39 | 36 | | 40 | 33 | | 41 | 1 | | 42 | 5 | | 43 | 12 | | 44 | 35 | | 45 | 11 | | 46 | 3 | | 47 | 4 | | 48 | 31 | | 49 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 274 | | matches | | 0 | "was supposed" | | 1 | "was supposed" | | 2 | "was gone" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 10 | | totalVerbs | 330 | | matches | | 0 | "were breathing" | | 1 | "wasn’t sealing" | | 2 | "was opening" | | 3 | "was pointing" | | 4 | "was staring" | | 5 | "was spinning" | | 6 | "were shifting" | | 7 | "was running" | | 8 | "was pulling" | | 9 | "was pointing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 346 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1596 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.021929824561403508 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.006265664160401002 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 346 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 346 | | mean | 6.21 | | std | 3.63 | | cv | 0.585 | | sampleLengths | | 0 | 21 | | 1 | 15 | | 2 | 6 | | 3 | 1 | | 4 | 8 | | 5 | 20 | | 6 | 18 | | 7 | 15 | | 8 | 7 | | 9 | 7 | | 10 | 10 | | 11 | 5 | | 12 | 5 | | 13 | 8 | | 14 | 15 | | 15 | 13 | | 16 | 8 | | 17 | 10 | | 18 | 4 | | 19 | 11 | | 20 | 12 | | 21 | 4 | | 22 | 12 | | 23 | 10 | | 24 | 18 | | 25 | 5 | | 26 | 6 | | 27 | 4 | | 28 | 4 | | 29 | 2 | | 30 | 10 | | 31 | 13 | | 32 | 4 | | 33 | 17 | | 34 | 6 | | 35 | 4 | | 36 | 4 | | 37 | 5 | | 38 | 6 | | 39 | 7 | | 40 | 3 | | 41 | 3 | | 42 | 4 | | 43 | 7 | | 44 | 18 | | 45 | 5 | | 46 | 8 | | 47 | 15 | | 48 | 9 | | 49 | 8 |
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| 38.08% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 41 | | diversityRatio | 0.21220930232558138 | | totalSentences | 344 | | uniqueOpeners | 73 | |
| 15.36% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 217 | | matches | | 0 | "Just a hollow cavity filled" |
| | ratio | 0.005 | |
| 87.28% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 72 | | totalSentences | 217 | | matches | | 0 | "She checked her worn leather" | | 1 | "It was supposed to be" | | 2 | "Her voice cut through the" | | 3 | "She pulled back the sheet" | | 4 | "She tucked a stray curl" | | 5 | "She scanned the neck." | | 6 | "She reached into her satchel" | | 7 | "She pulled the hand open" | | 8 | "It was a compass." | | 9 | "She recognized the craft from" | | 10 | "She tapped the compass face" | | 11 | "It was a steady thrum." | | 12 | "She stood up." | | 13 | "Her bearing shifted, military precision" | | 14 | "She began pacing the length" | | 15 | "She stopped pacing." | | 16 | "She stood up, brushing dust" | | 17 | "She looked past the sheet" | | 18 | "He pulled the sheet back." | | 19 | "Her glasses fogged slightly." |
| | ratio | 0.332 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 206 | | totalSentences | 217 | | matches | | 0 | "The damp air of the" | | 1 | "Salt-and-pepper strands of her closely" | | 2 | "She checked her worn leather" | | 3 | "The metal face was cool" | | 4 | "Eva Kowalski stood near the" | | 5 | "Books shifted inside the worn" | | 6 | "The forensics team hovered at" | | 7 | "None of them stepped past" | | 8 | "Quinn walked through the tape." | | 9 | "Rubber soles crunched on debris." | | 10 | "The location smelled of ozone" | | 11 | "It was supposed to be" | | 12 | "The Veil Market was supposed" | | 13 | "Her voice cut through the" | | 14 | "Eva didn’t look up." | | 15 | "She pulled back the sheet" | | 16 | "A pale hand lay exposed," | | 17 | "She tucked a stray curl" | | 18 | "The gesture was habitual, a" | | 19 | "Quinn crouched beside her partner." |
| | ratio | 0.949 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 217 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 51 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn said, her voice steady" |
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| 84.96% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 45 | | fancyCount | 8 | | fancyTags | | 0 | "Eva corrected (correct)" | | 1 | "officer shouted (shout)" | | 2 | "Quinn snapped (snap)" | | 3 | "Quinn ordered (order)" | | 4 | "Eva warned (warn)" | | 5 | "Eva shouted (shout)" | | 6 | "Quinn ordered (order)" | | 7 | "Quinn yelled (yell)" |
| | dialogueSentences | 123 | | tagDensity | 0.366 | | leniency | 0.732 | | rawRatio | 0.178 | | effectiveRatio | 0.13 | |