| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.447 | | leniency | 0.894 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.37% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1079 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 81.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1079 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "measured" | | 1 | "etched" | | 2 | "scanned" | | 3 | "perfect" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | 0 | "clenched fist" | | 1 | "fist clenched" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 101 | | matches | (empty) | |
| 86.28% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 101 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 128 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1079 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 760 | | uniqueNames | 10 | | maxNameDensity | 2.11 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Veil | 1 | | Market | 2 | | Tube | 1 | | Camden | 1 | | Patel | 8 | | Quinn | 16 | | Eva | 9 | | Kowalski | 1 | | Morris | 1 | | Deptford | 1 |
| | persons | | 0 | "Market" | | 1 | "Patel" | | 2 | "Quinn" | | 3 | "Eva" | | 4 | "Kowalski" | | 5 | "Morris" |
| | places | | | globalScore | 0.447 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.927 | | wordCount | 1079 | | matches | | 0 | "not collapsed, but arranged, feet together, arms tight" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 128 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 19.27 | | std | 15.17 | | cv | 0.787 | | sampleLengths | | 0 | 16 | | 1 | 8 | | 2 | 15 | | 3 | 20 | | 4 | 80 | | 5 | 30 | | 6 | 21 | | 7 | 26 | | 8 | 12 | | 9 | 3 | | 10 | 23 | | 11 | 8 | | 12 | 8 | | 13 | 32 | | 14 | 8 | | 15 | 35 | | 16 | 14 | | 17 | 31 | | 18 | 19 | | 19 | 7 | | 20 | 6 | | 21 | 40 | | 22 | 11 | | 23 | 6 | | 24 | 16 | | 25 | 5 | | 26 | 5 | | 27 | 30 | | 28 | 28 | | 29 | 6 | | 30 | 5 | | 31 | 6 | | 32 | 33 | | 33 | 7 | | 34 | 14 | | 35 | 46 | | 36 | 19 | | 37 | 5 | | 38 | 9 | | 39 | 12 | | 40 | 2 | | 41 | 9 | | 42 | 28 | | 43 | 42 | | 44 | 33 | | 45 | 2 | | 46 | 37 | | 47 | 15 | | 48 | 8 | | 49 | 22 |
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| 94.84% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 101 | | matches | | 0 | "was etched" | | 1 | "been scratched" | | 2 | "been covered" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 151 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 128 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 268 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 4 | | adverbRatio | 0.014925373134328358 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 128 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 128 | | mean | 8.43 | | std | 5.82 | | cv | 0.691 | | sampleLengths | | 0 | 16 | | 1 | 8 | | 2 | 6 | | 3 | 9 | | 4 | 8 | | 5 | 12 | | 6 | 11 | | 7 | 18 | | 8 | 5 | | 9 | 9 | | 10 | 11 | | 11 | 11 | | 12 | 15 | | 13 | 8 | | 14 | 7 | | 15 | 15 | | 16 | 8 | | 17 | 7 | | 18 | 6 | | 19 | 3 | | 20 | 11 | | 21 | 12 | | 22 | 12 | | 23 | 2 | | 24 | 1 | | 25 | 6 | | 26 | 17 | | 27 | 3 | | 28 | 5 | | 29 | 8 | | 30 | 4 | | 31 | 28 | | 32 | 4 | | 33 | 4 | | 34 | 11 | | 35 | 24 | | 36 | 14 | | 37 | 7 | | 38 | 10 | | 39 | 4 | | 40 | 2 | | 41 | 2 | | 42 | 6 | | 43 | 6 | | 44 | 13 | | 45 | 7 | | 46 | 6 | | 47 | 33 | | 48 | 7 | | 49 | 6 |
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| 63.28% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.4453125 | | totalSentences | 128 | | uniqueOpeners | 57 | |
| 41.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 80 | | matches | | 0 | "Then the wall took him." |
| | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 80 | | matches | | 0 | "He crouched with his gloves" | | 1 | "She circled the body with" | | 2 | "Her worn leather watch on" | | 3 | "She pointed without touching" | | 4 | "He shrugged and stood." | | 5 | "Her sharp jaw tightened." | | 6 | "She ignored the last part" | | 7 | "She lifted the lapel." | | 8 | "She did not touch the" | | 9 | "She looked at the clenched" | | 10 | "She pulled her own gloves" | | 11 | "She scanned the platform again." | | 12 | "She stood and walked three" | | 13 | "He handed her his torch." | | 14 | "She clicked it on and" | | 15 | "Her voice dropped." | | 16 | "Her watch ticked loud against" | | 17 | "He had said the wall" | | 18 | "She had not believed it" |
| | ratio | 0.238 | |
| 35.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 80 | | matches | | 0 | "Quinn lifted the tape with" | | 1 | "The constable lowered his cigarette" | | 2 | "Quinn's boots hit the cracked" | | 3 | "The Veil Market sat in" | | 4 | "That should have been impossible," | | 5 | "Stalls of blackened wood leaned" | | 6 | "Strings of bone charms clicked" | | 7 | "The air tasted of iron" | | 8 | "A single strip light buzzed" | | 9 | "A body lay face down" | | 10 | "Blood pooled under his chest" | | 11 | "DC Patel said from beside" | | 12 | "He crouched with his gloves" | | 13 | "Quinn didn't answer." | | 14 | "She circled the body with" | | 15 | "Her worn leather watch on" | | 16 | "She pointed without touching" | | 17 | "Patel leaned in." | | 18 | "He shrugged and stood." | | 19 | "Quinn tilted her head." |
| | ratio | 0.85 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 80 | | matches | (empty) | | ratio | 0 | |
| 93.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 2 | | matches | | 0 | "The beam revealed faint prints, not fingers, something narrower, something that ended in a point." | | 1 | "The air punched out of the Market and the bone chimes screamed all at once and something beneath the platform exhaled, cold and hungry, and reached up with a ha…" |
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| 77.38% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 2 | | matches | | 0 | "the station had, the tunnels flooded, the council poured concrete" | | 1 | "Quinn said, mostly to herself" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 17 | | fancyCount | 1 | | fancyTags | | 0 | "Eva whispered (whisper)" |
| | dialogueSentences | 47 | | tagDensity | 0.362 | | leniency | 0.723 | | rawRatio | 0.059 | | effectiveRatio | 0.043 | |