| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 35 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1263 | | 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) | |
| 64.37% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1263 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "perfect" | | 1 | "standard" | | 2 | "etched" | | 3 | "trembled" | | 4 | "silence" | | 5 | "echoed" | | 6 | "whisper" | | 7 | "traced" |
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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 | 109 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 109 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 130 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1259 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 832 | | uniqueNames | 7 | | maxNameDensity | 2.04 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Camden | 1 | | Quinn | 17 | | Kowalski | 1 | | Eva | 8 | | Market | 1 | | Silence | 1 |
| | persons | | 0 | "Camden" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" | | 4 | "Market" | | 5 | "Silence" |
| | places | (empty) | | globalScore | 0.478 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared freshly dead yet rigor had locked his limbs solid" |
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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 | 1259 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 130 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 33.13 | | std | 21.58 | | cv | 0.651 | | sampleLengths | | 0 | 68 | | 1 | 28 | | 2 | 39 | | 3 | 42 | | 4 | 50 | | 5 | 52 | | 6 | 36 | | 7 | 39 | | 8 | 17 | | 9 | 87 | | 10 | 63 | | 11 | 5 | | 12 | 6 | | 13 | 57 | | 14 | 9 | | 15 | 35 | | 16 | 20 | | 17 | 50 | | 18 | 23 | | 19 | 4 | | 20 | 10 | | 21 | 58 | | 22 | 21 | | 23 | 32 | | 24 | 39 | | 25 | 12 | | 26 | 24 | | 27 | 8 | | 28 | 63 | | 29 | 14 | | 30 | 68 | | 31 | 23 | | 32 | 51 | | 33 | 19 | | 34 | 14 | | 35 | 54 | | 36 | 10 | | 37 | 9 |
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| 98.83% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 109 | | matches | | 0 | "were folded" | | 1 | "were manicured" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 148 | | matches | (empty) | |
| 76.92% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 130 | | ratio | 0.023 | | matches | | 0 | "The abandoned Tube station beneath Camden opened its throat, exhaling rust and stale water and something else—something copper-sweet that clung to the back of the teeth." | | 1 | "The platform dust lay thick and undisturbed—except for the perfect circle of bare concrete where the body rested." | | 2 | "It coated everything—the rails, the discarded ticket machine, the fire extinguishers—except the circle." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 841 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.015457788347205707 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.005945303210463734 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 130 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 130 | | mean | 9.68 | | std | 6.89 | | cv | 0.711 | | sampleLengths | | 0 | 6 | | 1 | 26 | | 2 | 2 | | 3 | 13 | | 4 | 8 | | 5 | 13 | | 6 | 9 | | 7 | 8 | | 8 | 11 | | 9 | 13 | | 10 | 14 | | 11 | 7 | | 12 | 5 | | 13 | 14 | | 14 | 9 | | 15 | 4 | | 16 | 15 | | 17 | 16 | | 18 | 20 | | 19 | 14 | | 20 | 3 | | 21 | 4 | | 22 | 4 | | 23 | 7 | | 24 | 8 | | 25 | 18 | | 26 | 5 | | 27 | 3 | | 28 | 12 | | 29 | 24 | | 30 | 10 | | 31 | 4 | | 32 | 13 | | 33 | 12 | | 34 | 8 | | 35 | 9 | | 36 | 4 | | 37 | 2 | | 38 | 17 | | 39 | 4 | | 40 | 2 | | 41 | 2 | | 42 | 2 | | 43 | 6 | | 44 | 5 | | 45 | 17 | | 46 | 4 | | 47 | 11 | | 48 | 11 | | 49 | 4 |
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| 47.95% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3384615384615385 | | totalSentences | 130 | | uniqueOpeners | 44 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 96 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 96 | | matches | | 0 | "Her closely cropped salt-and-pepper hair" | | 1 | "Her round glasses had slipped" | | 2 | "She didn't look up." | | 3 | "Her worn leather satchel gaped" | | 4 | "Her voice carried the flat" | | 5 | "She examined his shoes." | | 6 | "She examined the wall behind" | | 7 | "They were gouges in the" | | 8 | "She examined his eyes." | | 9 | "He appeared freshly dead, yet" | | 10 | "She touched the floor." | | 11 | "It coated everything—the rails, the" | | 12 | "She ran her finger across" | | 13 | "It felt smooth as glass," | | 14 | "It trembled, angling toward the" | | 15 | "She turned, tracking its tug." | | 16 | "She looked up." | | 17 | "She held the compass at" | | 18 | "She looked back at the" | | 19 | "She pointed the compass toward" |
| | ratio | 0.271 | |
| 32.92% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 96 | | matches | | 0 | "Quinn's boot found the platform" | | 1 | "The abandoned Tube station beneath" | | 2 | "Her closely cropped salt-and-pepper hair" | | 3 | "The leather watch on her" | | 4 | "Crime scene tape flapped at" | | 5 | "A constable pointed his torch" | | 6 | "The body sat against the" | | 7 | "A man, mid-thirties, wore a" | | 8 | "Eva Kowalski crouched beside the" | | 9 | "Her round glasses had slipped" | | 10 | "She didn't look up." | | 11 | "Her worn leather satchel gaped" | | 12 | "Eva tucked a coil of" | | 13 | "Her voice carried the flat" | | 14 | "Quinn stepped closer." | | 15 | "The victim's throat gaped." | | 16 | "A single, deep incision." | | 17 | "The platform dust lay thick" | | 18 | "A forensic technician gestured with" | | 19 | "Eva lifted the small brass" |
| | ratio | 0.854 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 96 | | matches | (empty) | | ratio | 0 | |
| 98.21% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 2 | | matches | | 0 | "Her voice carried the flat precision of someone who had catalogued the impossible and moved on to the next page." | | 1 | "A warehouse that had been empty for decades, yet the forensics showed signs of fresh occupancy." |
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| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn walked, her torch beam stripping the darkness back" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "The technician snapped (snap)" |
| | dialogueSentences | 35 | | tagDensity | 0.057 | | leniency | 0.114 | | rawRatio | 0.5 | | effectiveRatio | 0.057 | |