| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said quietly [quietly]" |
| | dialogueSentences | 37 | | tagDensity | 0.351 | | leniency | 0.703 | | rawRatio | 0.077 | | effectiveRatio | 0.054 | |
| 87.22% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1565 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "carefully" | | 1 | "perfectly" | | 2 | "precisely" |
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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) | |
| 87.22% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1565 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "pulsed" | | 1 | "weight" | | 2 | "trembled" |
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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 | 108 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 108 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 131 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 72 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1572 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 1170 | | uniqueNames | 7 | | maxNameDensity | 1.54 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Kowalski | 1 | | Quinn | 18 | | Eva | 11 | | London | 1 | | Devlin | 5 | | Shade | 1 | | Spitalfields | 1 |
| | persons | | 0 | "Kowalski" | | 1 | "Quinn" | | 2 | "Eva" | | 3 | "Devlin" |
| | places | | | globalScore | 0.731 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | 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 | 1572 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 131 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 29.66 | | std | 26.4 | | cv | 0.89 | | sampleLengths | | 0 | 48 | | 1 | 70 | | 2 | 51 | | 3 | 4 | | 4 | 19 | | 5 | 8 | | 6 | 108 | | 7 | 16 | | 8 | 26 | | 9 | 2 | | 10 | 1 | | 11 | 61 | | 12 | 3 | | 13 | 62 | | 14 | 29 | | 15 | 7 | | 16 | 4 | | 17 | 61 | | 18 | 78 | | 19 | 5 | | 20 | 50 | | 21 | 4 | | 22 | 47 | | 23 | 4 | | 24 | 5 | | 25 | 5 | | 26 | 29 | | 27 | 3 | | 28 | 29 | | 29 | 31 | | 30 | 7 | | 31 | 66 | | 32 | 7 | | 33 | 29 | | 34 | 49 | | 35 | 85 | | 36 | 7 | | 37 | 25 | | 38 | 61 | | 39 | 24 | | 40 | 33 | | 41 | 4 | | 42 | 67 | | 43 | 4 | | 44 | 3 | | 45 | 54 | | 46 | 7 | | 47 | 64 | | 48 | 22 | | 49 | 30 |
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| 79.27% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 8 | | totalSentences | 108 | | matches | | 0 | "been stripped" | | 1 | "being drawn" | | 2 | "been swept" | | 3 | "been dropped" | | 4 | "been seized" | | 5 | "been dropped" | | 6 | "been placed" | | 7 | "been scrubbed" |
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| 95.83% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 192 | | matches | | 0 | "was not pointing" | | 1 | "was not pointing" | | 2 | "was pointing" |
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| 77.43% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 1 | | flaggedSentences | 3 | | totalSentences | 131 | | ratio | 0.023 | | matches | | 0 | "But the key on the floor — she tracked the angle." | | 1 | "A Shade artisan had crafted it; it had been seized from a fence in Spitalfields, and Quinn had logged it herself." | | 2 | "A dropped key would have disturbed it — the impact, the skitter, the settling." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1169 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.023952095808383235 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0051325919589392645 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 131 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 131 | | mean | 12 | | std | 10.38 | | cv | 0.865 | | sampleLengths | | 0 | 12 | | 1 | 22 | | 2 | 3 | | 3 | 11 | | 4 | 7 | | 5 | 36 | | 6 | 11 | | 7 | 16 | | 8 | 25 | | 9 | 26 | | 10 | 4 | | 11 | 16 | | 12 | 3 | | 13 | 8 | | 14 | 5 | | 15 | 20 | | 16 | 5 | | 17 | 11 | | 18 | 21 | | 19 | 17 | | 20 | 29 | | 21 | 10 | | 22 | 3 | | 23 | 3 | | 24 | 6 | | 25 | 20 | | 26 | 2 | | 27 | 1 | | 28 | 2 | | 29 | 10 | | 30 | 14 | | 31 | 4 | | 32 | 17 | | 33 | 14 | | 34 | 3 | | 35 | 7 | | 36 | 17 | | 37 | 8 | | 38 | 30 | | 39 | 9 | | 40 | 20 | | 41 | 7 | | 42 | 4 | | 43 | 5 | | 44 | 42 | | 45 | 14 | | 46 | 5 | | 47 | 4 | | 48 | 11 | | 49 | 16 |
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| 54.96% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.366412213740458 | | totalSentences | 131 | | uniqueOpeners | 48 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 95 | | matches | | 0 | "Too far for someone to" | | 1 | "Instead it sat in the" | | 2 | "Then she looked again at" | | 3 | "Then at the compass." |
| | ratio | 0.042 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 95 | | matches | | 0 | "She'd used the bone token" | | 1 | "It sat now in her" | | 2 | "She had her leather satchel" | | 3 | "It sold maps, or had." | | 4 | "His chest was a mess" | | 5 | "She looked at his hands" | | 6 | "His nails were clean." | | 7 | "He gestured at the stall's" | | 8 | "It lay in the middle" | | 9 | "It would have skittered along" | | 10 | "She didn't say that yet." | | 11 | "She looked at the blood" | | 12 | "His jacket was still buttoned." | | 13 | "His shirt hung open at" | | 14 | "She leaned closer and saw" | | 15 | "She spoke now, quiet." | | 16 | "She reached into her satchel" | | 17 | "She hadn't known Eva had" | | 18 | "It spun in slow, uneven" | | 19 | "She knew that compass." |
| | ratio | 0.295 | |
| 28.42% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 95 | | matches | | 0 | "The air in the abandoned" | | 1 | "Quinn felt it against her" | | 2 | "Water dripped somewhere." | | 3 | "A train rumbled far above," | | 4 | "She'd used the bone token" | | 5 | "It sat now in her" | | 6 | "The tile work spelled names" | | 7 | "Eva Kowalski stood by a" | | 8 | "She had her leather satchel" | | 9 | "Quinn pulled leather gloves from" | | 10 | "Eva moved aside, and Quinn" | | 11 | "It sold maps, or had." | | 12 | "Rolls of them lay scattered" | | 13 | "Some showed London above ground." | | 14 | "Others showed things underneath it" | | 15 | "A man lay on his" | | 16 | "His chest was a mess" | | 17 | "The stall was no bigger" | | 18 | "Quinn stepped over the threshold" | | 19 | "The floorboards creaked." |
| | ratio | 0.863 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 95 | | matches | | 0 | "Now it pointed at a" | | 1 | "If a killer opened the" |
| | ratio | 0.021 | |
| 85.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 4 | | matches | | 0 | "Eva Kowalski stood by a shuttered stall, her round glasses catching the low sodium light of a string of bulbs that shouldn't have been working." | | 1 | "She leaned closer and saw the edges around the wound: a neat, deliberate incision, as if someone had removed the cloth before making the wound." | | 2 | "Eva had been watching them both, her fingers working at her earlobe, her satchel creaking as she shifted her weight." | | 3 | "It was pointing at the floor beneath the body's centre, at a spot where the floorboards were darker, cleaner, as if something had been scrubbed away." |
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| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 1 | | matches | | 0 | "She reached, its casing patinaed with verdigris" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 37 | | tagDensity | 0.108 | | leniency | 0.216 | | rawRatio | 0 | | effectiveRatio | 0 | |