| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn said flatly [flatly]" |
| | dialogueSentences | 42 | | tagDensity | 0.405 | | leniency | 0.81 | | rawRatio | 0.059 | | effectiveRatio | 0.048 | |
| 87.87% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1649 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "lazily" | | 1 | "really" | | 2 | "slightly" | | 3 | "suddenly" |
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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) | |
| 81.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1649 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "chill" | | 1 | "scanned" | | 2 | "etched" | | 3 | "weight" | | 4 | "familiar" | | 5 | "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 | 131 | | matches | (empty) | |
| 88.33% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 4 | | narrationSentences | 131 | | filterMatches | | | hedgeMatches | | 0 | "tried to" | | 1 | "happened to" | | 2 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 156 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1650 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 74.87% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 1198 | | uniqueNames | 12 | | maxNameDensity | 1.5 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Quinn | 18 | | King | 1 | | Cross | 1 | | Kowalski | 1 | | Eva | 17 | | Tube | 1 | | Veil | 2 | | Compass | 1 | | Morris | 3 | | Finch | 2 | | Market | 1 |
| | persons | | 0 | "Quinn" | | 1 | "King" | | 2 | "Cross" | | 3 | "Kowalski" | | 4 | "Eva" | | 5 | "Morris" |
| | places | | | globalScore | 0.749 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | glossingSentenceCount | 1 | | matches | | 0 | "tasted like cold iron and old rain" |
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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 | 1650 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 156 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 59 | | mean | 27.97 | | std | 21.33 | | cv | 0.763 | | sampleLengths | | 0 | 17 | | 1 | 68 | | 2 | 13 | | 3 | 31 | | 4 | 40 | | 5 | 11 | | 6 | 21 | | 7 | 8 | | 8 | 25 | | 9 | 57 | | 10 | 1 | | 11 | 16 | | 12 | 75 | | 13 | 14 | | 14 | 6 | | 15 | 38 | | 16 | 68 | | 17 | 3 | | 18 | 58 | | 19 | 5 | | 20 | 23 | | 21 | 7 | | 22 | 64 | | 23 | 43 | | 24 | 28 | | 25 | 27 | | 26 | 15 | | 27 | 20 | | 28 | 1 | | 29 | 68 | | 30 | 5 | | 31 | 62 | | 32 | 24 | | 33 | 5 | | 34 | 6 | | 35 | 15 | | 36 | 18 | | 37 | 7 | | 38 | 31 | | 39 | 7 | | 40 | 32 | | 41 | 3 | | 42 | 22 | | 43 | 17 | | 44 | 29 | | 45 | 57 | | 46 | 76 | | 47 | 64 | | 48 | 33 | | 49 | 18 |
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| 81.16% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 9 | | totalSentences | 131 | | matches | | 0 | "got trampled" | | 1 | "was tucked" | | 2 | "been sealed" | | 3 | "been coated" | | 4 | "was etched" | | 5 | "were staged" | | 6 | "was wedged" | | 7 | "was clenched" | | 8 | "been dragged" | | 9 | "being held" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 207 | | matches | | 0 | "was standing" | | 1 | "was losing" | | 2 | "wasn't pointing" | | 3 | "was spinning" | | 4 | "was watching" | | 5 | "were slotting" | | 6 | "was staring" | | 7 | "were speaking" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 156 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 938 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.03304904051172708 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.013859275053304905 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 156 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 156 | | mean | 10.58 | | std | 8.52 | | cv | 0.806 | | sampleLengths | | 0 | 17 | | 1 | 12 | | 2 | 15 | | 3 | 3 | | 4 | 38 | | 5 | 13 | | 6 | 9 | | 7 | 22 | | 8 | 2 | | 9 | 11 | | 10 | 11 | | 11 | 12 | | 12 | 4 | | 13 | 11 | | 14 | 12 | | 15 | 9 | | 16 | 8 | | 17 | 3 | | 18 | 6 | | 19 | 8 | | 20 | 8 | | 21 | 8 | | 22 | 17 | | 23 | 32 | | 24 | 1 | | 25 | 11 | | 26 | 5 | | 27 | 17 | | 28 | 17 | | 29 | 2 | | 30 | 3 | | 31 | 17 | | 32 | 5 | | 33 | 13 | | 34 | 1 | | 35 | 10 | | 36 | 4 | | 37 | 6 | | 38 | 2 | | 39 | 30 | | 40 | 6 | | 41 | 2 | | 42 | 2 | | 43 | 2 | | 44 | 27 | | 45 | 13 | | 46 | 3 | | 47 | 19 | | 48 | 3 | | 49 | 3 |
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| 61.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3974358974358974 | | totalSentences | 156 | | uniqueOpeners | 62 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 108 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 108 | | matches | | 0 | "She had been on call" | | 1 | "he said, relief making his" | | 2 | "She had put the word" | | 3 | "She'd called her at four" | | 4 | "She hadn't asked Eva to" | | 5 | "Her worn leather satchel was" | | 6 | "He lay on his back" | | 7 | "His coat was good quality," | | 8 | "She scanned the scene in" | | 9 | "She looked closer." | | 10 | "She pulled out a small" | | 11 | "She had thrown it back" | | 12 | "It was spinning lazily, then" | | 13 | "She reached over and took" | | 14 | "She looked again." | | 15 | "She leaned closer." | | 16 | "His lips were slightly parted." | | 17 | "She lifted the token out" | | 18 | "Her voice sounded too low" | | 19 | "She stood, her knees popping." |
| | ratio | 0.213 | |
| 66.48% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 85 | | totalSentences | 108 | | matches | | 0 | "The air at the bottom" | | 1 | "Harlow Quinn pulled her collar" | | 2 | "The worn leather strap on" | | 3 | "She had been on call" | | 4 | "A uniformed constable stood too" | | 5 | "he said, relief making his" | | 6 | "She had put the word" | | 7 | "Anything odd, anything beneath, call" | | 8 | "This one had listened." | | 9 | "The constable hesitated, glancing at" | | 10 | "Eva Kowalski said without looking" | | 11 | "Quinn's jaw tightened." | | 12 | "She'd called her at four" | | 13 | "She hadn't asked Eva to" | | 14 | "Eva looked impossibly out of" | | 15 | "Her worn leather satchel was" | | 16 | "Eva finally glanced up, green" | | 17 | "The body was male, early" | | 18 | "He lay on his back" | | 19 | "This wasn't any of those." |
| | ratio | 0.787 | |
| 92.59% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 108 | | matches | | 0 | "Now Eva held it out" | | 1 | "Whoever had done it had" |
| | ratio | 0.019 | |
| 85.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 4 | | matches | | 0 | "She had been on call for three hours, had already done two hours of paperwork for a domestic that wasn't a domestic, and now she was standing on a platform that…" | | 1 | "Her worn leather satchel was tucked against her knees, bulging with books as always, and she kept tucking a loose curl behind her left ear with a hand that wasn…" | | 2 | "The casing had gone green-black with verdigris at the seams, and the face was etched with tiny protective sigils that caught Quinn's torchlight and threw it bac…" | | 3 | "She took the compass, and finally, as if satisfied, the needle stopped spinning and locked due north." |
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| 95.59% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, relief making his voice too loud" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 2 | | fancyTags | | 0 | "Eva whispered (whisper)" | | 1 | "Eva breathed (breathe)" |
| | dialogueSentences | 42 | | tagDensity | 0.31 | | leniency | 0.619 | | rawRatio | 0.154 | | effectiveRatio | 0.095 | |