| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 27 | | tagDensity | 0.259 | | leniency | 0.519 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.16% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1302 | | totalAiIsmAdverbs | 1 | | found | | | 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) | |
| 84.64% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1302 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "jaw clenched" | | 1 | "weight" | | 2 | "electric" | | 3 | "pulse" |
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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 | 94 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 94 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 113 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1302 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 1083 | | uniqueNames | 13 | | maxNameDensity | 0.92 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | Parkway | 1 | | Raven | 1 | | Nest | 2 | | Road | 1 | | Seville | 1 | | Saturday | 1 | | Quinn | 10 | | Saint | 1 | | Christopher | 1 | | Deptford | 1 | | Tomás | 7 | | Christmas | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Saint" | | 2 | "Christopher" | | 3 | "Tomás" |
| | places | | 0 | "Camden" | | 1 | "Parkway" | | 2 | "Raven" | | 3 | "Road" | | 4 | "Seville" | | 5 | "Deptford" |
| | globalScore | 1 | | windowScore | 1 | |
| 75.37% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like gravel poured slowly into a b" | | 1 | "looked like sailcloth" |
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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 | 1302 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 113 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 24.57 | | std | 21.16 | | cv | 0.861 | | sampleLengths | | 0 | 55 | | 1 | 5 | | 2 | 54 | | 3 | 46 | | 4 | 60 | | 5 | 35 | | 6 | 5 | | 7 | 32 | | 8 | 16 | | 9 | 45 | | 10 | 62 | | 11 | 16 | | 12 | 14 | | 13 | 13 | | 14 | 21 | | 15 | 4 | | 16 | 28 | | 17 | 9 | | 18 | 11 | | 19 | 41 | | 20 | 12 | | 21 | 5 | | 22 | 10 | | 23 | 83 | | 24 | 21 | | 25 | 66 | | 26 | 46 | | 27 | 16 | | 28 | 1 | | 29 | 10 | | 30 | 47 | | 31 | 4 | | 32 | 29 | | 33 | 31 | | 34 | 13 | | 35 | 2 | | 36 | 1 | | 37 | 65 | | 38 | 24 | | 39 | 64 | | 40 | 7 | | 41 | 13 | | 42 | 6 | | 43 | 2 | | 44 | 48 | | 45 | 5 | | 46 | 13 | | 47 | 11 | | 48 | 24 | | 49 | 25 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 94 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 176 | | matches | | 0 | "wasn't shouting" | | 1 | "was backing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 113 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1089 | | adjectiveStacks | 1 | | stackExamples | | 0 | "warm, diesel-sour gust" |
| | adverbCount | 24 | | adverbRatio | 0.02203856749311295 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0027548209366391185 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 113 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 113 | | mean | 11.52 | | std | 8.48 | | cv | 0.736 | | sampleLengths | | 0 | 16 | | 1 | 39 | | 2 | 5 | | 3 | 2 | | 4 | 21 | | 5 | 6 | | 6 | 25 | | 7 | 6 | | 8 | 3 | | 9 | 33 | | 10 | 4 | | 11 | 9 | | 12 | 5 | | 13 | 22 | | 14 | 24 | | 15 | 4 | | 16 | 31 | | 17 | 5 | | 18 | 3 | | 19 | 16 | | 20 | 4 | | 21 | 9 | | 22 | 16 | | 23 | 3 | | 24 | 33 | | 25 | 9 | | 26 | 1 | | 27 | 8 | | 28 | 23 | | 29 | 17 | | 30 | 3 | | 31 | 10 | | 32 | 16 | | 33 | 2 | | 34 | 12 | | 35 | 13 | | 36 | 18 | | 37 | 3 | | 38 | 4 | | 39 | 10 | | 40 | 18 | | 41 | 9 | | 42 | 11 | | 43 | 16 | | 44 | 25 | | 45 | 12 | | 46 | 5 | | 47 | 10 | | 48 | 4 | | 49 | 18 |
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| 61.06% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.39823008849557523 | | totalSentences | 113 | | uniqueOpeners | 45 | |
| 77.52% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 86 | | matches | | 0 | "Then he turned down a" | | 1 | "Somewhere ahead, voices." |
| | ratio | 0.023 | |
| 99.07% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 86 | | matches | | 0 | "He vaulted a bollard, cut" | | 1 | "Her radio crackled against her" | | 2 | "She ignored it." | | 3 | "She rounded the bus." | | 4 | "He was on the far" | | 5 | "He glanced back." | | 6 | "She pushed through it and" | | 7 | "She let him see her" | | 8 | "His accent had thickened with" | | 9 | "He looked down at his" | | 10 | "He took a step backwards," | | 11 | "He turned and took the" | | 12 | "He laid it in the" | | 13 | "He stopped on the other" | | 14 | "He wasn't shouting now" | | 15 | "He wiped rain from his" | | 16 | "They fixed on Quinn and" | | 17 | "She could see stalls down" | | 18 | "She'd seal the entrance and" | | 19 | "She knew that the way" |
| | ratio | 0.302 | |
| 47.21% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 86 | | matches | | 0 | "Rain came off the Camden" | | 1 | "Quinn took the corner at" | | 2 | "He vaulted a bollard, cut" | | 3 | "A driver leaned on his" | | 4 | "Quinn went around the back" | | 5 | "Her radio crackled against her" | | 6 | "She ignored it." | | 7 | "Backup meant a van, a" | | 8 | "Backup meant losing him." | | 9 | "Tomás had been easy to" | | 10 | "A former paramedic, struck off," | | 11 | "Tonight he'd come out of" | | 12 | "She rounded the bus." | | 13 | "He was on the far" | | 14 | "He glanced back." | | 15 | "Quinn's lungs burned." | | 16 | "She pushed through it and" | | 17 | "A fire escape dripping like" | | 18 | "Victorian lettering had been painted" | | 19 | "A station entrance." |
| | ratio | 0.826 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 1 | | matches | | 0 | "He was on the far side of the high street, running along the shuttered fronts of the lock market, trainers slapping through puddles that held the orange smear o…" |
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| 53.57% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 1 | | matches | | 0 | "His accent had, the Seville vowels rounding everything off" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 27 | | tagDensity | 0.148 | | leniency | 0.296 | | rawRatio | 0 | | effectiveRatio | 0 | |