| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 72 | | tagDensity | 0.028 | | leniency | 0.056 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1786 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 94.40% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1786 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 157 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 157 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 227 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1787 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 1414 | | uniqueNames | 9 | | maxNameDensity | 2.33 | | worstName | "Quinn" | | maxWindowNameDensity | 5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 33 | | Control | 1 | | Underground | 1 | | Raven | 1 | | Nest | 1 | | London | 1 | | Veil | 1 | | Market | 1 | | Camden | 1 |
| | persons | | | places | | | globalScore | 0.333 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 116 | | 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 | 1787 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 227 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 164 | | mean | 10.9 | | std | 10.79 | | cv | 0.99 | | sampleLengths | | 0 | 12 | | 1 | 24 | | 2 | 8 | | 3 | 22 | | 4 | 2 | | 5 | 6 | | 6 | 4 | | 7 | 19 | | 8 | 19 | | 9 | 14 | | 10 | 5 | | 11 | 5 | | 12 | 48 | | 13 | 2 | | 14 | 12 | | 15 | 26 | | 16 | 7 | | 17 | 20 | | 18 | 6 | | 19 | 3 | | 20 | 9 | | 21 | 2 | | 22 | 38 | | 23 | 7 | | 24 | 5 | | 25 | 45 | | 26 | 15 | | 27 | 2 | | 28 | 5 | | 29 | 10 | | 30 | 3 | | 31 | 24 | | 32 | 4 | | 33 | 31 | | 34 | 14 | | 35 | 15 | | 36 | 1 | | 37 | 6 | | 38 | 5 | | 39 | 8 | | 40 | 1 | | 41 | 1 | | 42 | 41 | | 43 | 5 | | 44 | 9 | | 45 | 4 | | 46 | 20 | | 47 | 8 | | 48 | 6 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 157 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 237 | | matches | (empty) | |
| 92.51% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 3 | | flaggedSentences | 4 | | totalSentences | 227 | | ratio | 0.018 | | matches | | 0 | "On the other side, her heel landed on a flattened drinks can; it shot out from under her, and she caught the gate before she went down." | | 1 | "A row of shuttered workshops filled one side; on the other, plywood covered the entrance to an old station building." | | 2 | "Someone argued over a quantity; someone else laughed and stopped when Quinn moved nearer." | | 3 | "DS MORRIS — PERSONAL EFFECTS." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1417 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.015525758645024701 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0007057163020465773 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 227 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 227 | | mean | 7.87 | | std | 4.76 | | cv | 0.604 | | sampleLengths | | 0 | 12 | | 1 | 5 | | 2 | 12 | | 3 | 7 | | 4 | 8 | | 5 | 10 | | 6 | 12 | | 7 | 2 | | 8 | 6 | | 9 | 4 | | 10 | 7 | | 11 | 3 | | 12 | 9 | | 13 | 10 | | 14 | 9 | | 15 | 14 | | 16 | 5 | | 17 | 5 | | 18 | 6 | | 19 | 23 | | 20 | 7 | | 21 | 12 | | 22 | 2 | | 23 | 3 | | 24 | 9 | | 25 | 5 | | 26 | 12 | | 27 | 9 | | 28 | 7 | | 29 | 20 | | 30 | 6 | | 31 | 3 | | 32 | 9 | | 33 | 2 | | 34 | 9 | | 35 | 12 | | 36 | 17 | | 37 | 7 | | 38 | 5 | | 39 | 14 | | 40 | 4 | | 41 | 27 | | 42 | 15 | | 43 | 2 | | 44 | 5 | | 45 | 10 | | 46 | 3 | | 47 | 7 | | 48 | 7 | | 49 | 10 |
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| 58.88% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.36123348017621143 | | totalSentences | 227 | | uniqueOpeners | 82 | |
| 44.15% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 151 | | matches | | 0 | "Then she went after him." | | 1 | "Then the grey coat appeared" |
| | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 42 | | totalSentences | 151 | | matches | | 0 | "His reflection stopped beside hers." | | 1 | "His right hand went into" | | 2 | "She hadn’t given him her" | | 3 | "He pulled something pale from" | | 4 | "She caught the woman by" | | 5 | "His grey coat flashed between" | | 6 | "He looked back." | | 7 | "His mouth moved, but a" | | 8 | "Her left shoe struck a" | | 9 | "She kept her stride short" | | 10 | "Her radio crackled beneath her" | | 11 | "He dropped out of sight." | | 12 | "She reached the gate, put" | | 13 | "He pointed with the cigarette." | | 14 | "She hit it shoulder-first." | | 15 | "He was tiring." | | 16 | "She could hear his breathing" | | 17 | "she told Control" | | 18 | "She pressed the radio closer" | | 19 | "He stopped at the plywood." |
| | ratio | 0.278 | |
| 32.85% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 129 | | totalSentences | 151 | | matches | | 0 | "The man in the grey" | | 1 | "His reflection stopped beside hers." | | 2 | "Rain ran between them in" | | 3 | "His right hand went into" | | 4 | "Quinn opened her jacket enough" | | 5 | "The man looked at the" | | 6 | "She hadn’t given him her" | | 7 | "He pulled something pale from" | | 8 | "A narrow piece of bone," | | 9 | "A bus swept past, throwing" | | 10 | "The man shoved a pedestrian" | | 11 | "She caught the woman by" | | 12 | "His grey coat flashed between" | | 13 | "Quinn slipped past a couple" | | 14 | "The suspect crossed the road" | | 15 | "A taxi braked hard enough" | | 16 | "He looked back." | | 17 | "His mouth moved, but a" | | 18 | "Quinn crossed behind the taxi." | | 19 | "Her left shoe struck a" |
| | ratio | 0.854 | |
| 33.11% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 151 | | matches | | 0 | "Even at that distance, she" |
| | ratio | 0.007 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 61 | | technicalSentenceCount | 1 | | matches | | 0 | "By then, the grey coat could be anywhere beneath Camden, carrying an item that should have sat in a sealed police store." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 72 | | tagDensity | 0.014 | | leniency | 0.028 | | rawRatio | 0 | | effectiveRatio | 0 | |