| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.375 | | leniency | 0.75 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.65% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 788 | | 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) | |
| 74.62% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 788 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "flicker" | | 1 | "glint" | | 2 | "silence" | | 3 | "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 | 53 | | matches | (empty) | |
| 61.99% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 53 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 63 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 2 | | totalWords | 788 | | ratio | 0.003 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 16 | | wordCount | 650 | | uniqueNames | 11 | | maxNameDensity | 0.62 | | worstName | "Quinn" | | maxWindowNameDensity | 1 | | worstWindowName | "Quinn" | | discoveredNames | | Kentish | 1 | | Town | 1 | | Camden | 1 | | High | 1 | | Street | 2 | | Quinn | 4 | | Herrera | 1 | | Soho | 1 | | Tube | 1 | | Wardour | 1 | | Morris | 2 |
| | persons | | 0 | "Quinn" | | 1 | "Herrera" | | 2 | "Morris" |
| | places | | 0 | "Kentish" | | 1 | "Town" | | 2 | "Camden" | | 3 | "High" | | 4 | "Street" | | 5 | "Soho" | | 6 | "Wardour" |
| | globalScore | 1 | | windowScore | 1 | |
| 87.50% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | glossingSentenceCount | 1 | | matches | | 0 | "dark that seemed to have depth beyond the reach of any torch" |
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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 | 788 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 63 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 23 | | mean | 34.26 | | std | 24.67 | | cv | 0.72 | | sampleLengths | | 0 | 90 | | 1 | 51 | | 2 | 45 | | 3 | 1 | | 4 | 26 | | 5 | 28 | | 6 | 7 | | 7 | 11 | | 8 | 28 | | 9 | 50 | | 10 | 5 | | 11 | 73 | | 12 | 16 | | 13 | 19 | | 14 | 80 | | 15 | 53 | | 16 | 65 | | 17 | 29 | | 18 | 21 | | 19 | 13 | | 20 | 14 | | 21 | 44 | | 22 | 19 |
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| 98.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 53 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 102 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 63 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 651 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.021505376344086023 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0030721966205837174 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 63 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 63 | | mean | 12.51 | | std | 8.5 | | cv | 0.68 | | sampleLengths | | 0 | 33 | | 1 | 14 | | 2 | 11 | | 3 | 19 | | 4 | 4 | | 5 | 9 | | 6 | 2 | | 7 | 14 | | 8 | 35 | | 9 | 19 | | 10 | 7 | | 11 | 7 | | 12 | 12 | | 13 | 1 | | 14 | 6 | | 15 | 20 | | 16 | 15 | | 17 | 13 | | 18 | 7 | | 19 | 11 | | 20 | 17 | | 21 | 11 | | 22 | 6 | | 23 | 6 | | 24 | 24 | | 25 | 2 | | 26 | 12 | | 27 | 5 | | 28 | 15 | | 29 | 27 | | 30 | 6 | | 31 | 25 | | 32 | 16 | | 33 | 5 | | 34 | 4 | | 35 | 10 | | 36 | 2 | | 37 | 28 | | 38 | 23 | | 39 | 7 | | 40 | 20 | | 41 | 19 | | 42 | 19 | | 43 | 4 | | 44 | 11 | | 45 | 38 | | 46 | 14 | | 47 | 7 | | 48 | 6 | | 49 | 8 |
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| 77.78% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.5238095238095238 | | totalSentences | 63 | | uniqueOpeners | 33 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 46 | | matches | (empty) | | ratio | 0 | |
| 37.39% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 46 | | matches | | 0 | "Her watch strap clung cold" | | 1 | "He didn't need to." | | 2 | "He had known she was" | | 3 | "He swung left off the" | | 4 | "She caught herself on an" | | 5 | "She didn't bother lowering her" | | 6 | "He stopped at the mouth" | | 7 | "He held them up, palms" | | 8 | "She didn't look at the" | | 9 | "She kept her eyes on" | | 10 | "Her thumb hovered over the" | | 11 | "He drew his hand from" | | 12 | "It smelled of wet earth," | | 13 | "Her mind went back to" | | 14 | "Her superiors had filed it" | | 15 | "She had filed it under" | | 16 | "He didn't hurry." | | 17 | "He simply waited, the token" | | 18 | "She looked at her wet" | | 19 | "Her pulse slowed into the" |
| | ratio | 0.457 | |
| 57.83% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 37 | | totalSentences | 46 | | matches | | 0 | "The rain had been falling" | | 1 | "Harlow Quinn ran with her" | | 2 | "Her watch strap clung cold" | | 3 | "He didn't need to." | | 4 | "He had known she was" | | 5 | "He swung left off the" | | 6 | "Canal water slapped against the" | | 7 | "Quinn's soles skidded on the" | | 8 | "She caught herself on an" | | 9 | "She didn't bother lowering her" | | 10 | "He stopped at the mouth" | | 11 | "Rain ran off his curls" | | 12 | "He held them up, palms" | | 13 | "She didn't look at the" | | 14 | "She kept her eyes on" | | 15 | "Her thumb hovered over the" | | 16 | "He drew his hand from" | | 17 | "A bone, polished smooth by" | | 18 | "Something moved behind his face." | | 19 | "Quinn moved forward, boots loud" |
| | ratio | 0.804 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 46 | | matches | (empty) | | ratio | 0 | |
| 60.44% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 3 | | matches | | 0 | "Two weeks ago she had watched those hands stitch a man on the floor of a Soho pub, blood running into the grout, the man's eyes rolling towards something that w…" | | 1 | "Between two fingers he held a small pale token on a cord of frayed black thread, carved with a row of notches that caught the sodium light." | | 2 | "She looked at her wet hands, at the watch that had stopped keeping time the night Morris died, at the rain rolling off the arch above her." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0 | | effectiveRatio | 0 | |