| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 2 | | adverbTags | | 0 | "She crouched again [again]" | | 1 | "he said finally [finally]" |
| | dialogueSentences | 45 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.111 | | effectiveRatio | 0.089 | |
| 84.29% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 955 | | totalAiIsmAdverbs | 3 | | 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) | |
| 63.35% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 955 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "silk" | | 1 | "etched" | | 2 | "weight" | | 3 | "flicked" |
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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 | 56 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 56 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 83 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 962 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 87.83% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 563 | | uniqueNames | 7 | | maxNameDensity | 1.24 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 7 | | Tube | 1 | | Bell | 7 | | Young | 1 | | Morris | 3 | | Darkness | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Bell" | | 3 | "Morris" |
| | places | | | globalScore | 0.878 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 33 | | 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 | 962 | | matches | (empty) | |
| 86.35% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 83 | | matches | | 0 | "let that land" | | 1 | "read that file" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 26 | | std | 22.15 | | cv | 0.852 | | sampleLengths | | 0 | 68 | | 1 | 28 | | 2 | 10 | | 3 | 51 | | 4 | 3 | | 5 | 37 | | 6 | 4 | | 7 | 4 | | 8 | 41 | | 9 | 14 | | 10 | 82 | | 11 | 11 | | 12 | 7 | | 13 | 55 | | 14 | 4 | | 15 | 5 | | 16 | 35 | | 17 | 5 | | 18 | 58 | | 19 | 6 | | 20 | 52 | | 21 | 15 | | 22 | 1 | | 23 | 6 | | 24 | 3 | | 25 | 48 | | 26 | 16 | | 27 | 51 | | 28 | 4 | | 29 | 40 | | 30 | 10 | | 31 | 41 | | 32 | 42 | | 33 | 21 | | 34 | 4 | | 35 | 30 | | 36 | 50 |
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| 92.73% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 56 | | matches | | 0 | "been swept" | | 1 | "were clenched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 105 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 1 | | flaggedSentences | 7 | | totalSentences | 83 | | ratio | 0.084 | | matches | | 0 | "The stairs down to the abandoned platform smelled of damp brick and something sharper — burnt sugar, maybe, or incense gone stale." | | 1 | "Male, mid-fifties, well dressed — too well dressed for squatting in a derelict station." | | 2 | "She walked the perimeter slowly, the way DS Morris had taught her — eyes down, then up, then sideways at the things nobody thought to look at." | | 3 | "Not by council workers; the dust along the walls lay undisturbed in thick grey drifts, but the central walkway was clean, almost polished." | | 4 | "She counted the rectangular patches of cleaner concrete — a dozen, maybe more, arranged in rows like a market." | | 5 | "She moved toward the body again and noticed what she'd missed the first time — the victim's left hand, the one folded underneath." | | 6 | "Felt the old cold weight settle behind her ribs — the same weight she'd carried since Morris died three years ago, on a case that had never made sense either." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 558 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.03942652329749104 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.008960573476702509 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 83 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 83 | | mean | 11.59 | | std | 9.18 | | cv | 0.792 | | sampleLengths | | 0 | 22 | | 1 | 26 | | 2 | 20 | | 3 | 10 | | 4 | 13 | | 5 | 5 | | 6 | 10 | | 7 | 5 | | 8 | 14 | | 9 | 10 | | 10 | 6 | | 11 | 16 | | 12 | 3 | | 13 | 8 | | 14 | 29 | | 15 | 3 | | 16 | 1 | | 17 | 4 | | 18 | 28 | | 19 | 13 | | 20 | 3 | | 21 | 11 | | 22 | 2 | | 23 | 27 | | 24 | 6 | | 25 | 23 | | 26 | 5 | | 27 | 19 | | 28 | 6 | | 29 | 5 | | 30 | 4 | | 31 | 3 | | 32 | 28 | | 33 | 11 | | 34 | 16 | | 35 | 4 | | 36 | 5 | | 37 | 23 | | 38 | 8 | | 39 | 4 | | 40 | 5 | | 41 | 13 | | 42 | 30 | | 43 | 5 | | 44 | 10 | | 45 | 6 | | 46 | 7 | | 47 | 12 | | 48 | 3 | | 49 | 30 |
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| 98.80% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.6265060240963856 | | totalSentences | 83 | | uniqueOpeners | 52 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 47 | | matches | (empty) | | ratio | 0 | |
| 58.30% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 47 | | matches | | 0 | "She crouched beside the corpse." | | 1 | "His hands lay folded across" | | 2 | "She stood, brushing grit from" | | 3 | "She walked the perimeter slowly," | | 4 | "She counted the rectangular patches" | | 5 | "She crouched again and ran" | | 6 | "She moved down the row" | | 7 | "She moved toward the body" | | 8 | "She lifted it gently with" | | 9 | "It took a minute of" | | 10 | "It pointed, steady as a" | | 11 | "She dropped it into a" | | 12 | "She let that land" | | 13 | "She turned toward the tunnel" | | 14 | "She softened her voice, the" | | 15 | "His eyes flicked toward the" | | 16 | "he said finally" | | 17 | "She had read that file" | | 18 | "She tucked the bag into" |
| | ratio | 0.404 | |
| 34.47% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 40 | | totalSentences | 47 | | matches | | 0 | "The stairs down to the" | | 1 | "Detective Harlow Quinn ducked under" | | 2 | "Camden's forgotten Tube station, sealed" | | 3 | "Sergeant Bell raised a hand" | | 4 | "She crouched beside the corpse." | | 5 | "Wool coat, silk scarf, shoes" | | 6 | "His hands lay folded across" | | 7 | "Bell flipped open his notebook" | | 8 | "Quinn looked up." | | 9 | "She stood, brushing grit from" | | 10 | "Bell's jaw worked." | | 11 | "She walked the perimeter slowly," | | 12 | "The platform had been swept" | | 13 | "Stalls had stood here once." | | 14 | "She counted the rectangular patches" | | 15 | "She crouched again and ran" | | 16 | "She moved down the row" | | 17 | "She moved toward the body" | | 18 | "She lifted it gently with" | | 19 | "The fingers were clenched." |
| | ratio | 0.851 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 47 | | matches | (empty) | | ratio | 0 | |
| 6.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 4 | | matches | | 0 | "His hands lay folded across his chest as though someone had arranged him for a funeral." | | 1 | "Inside the man's fist sat a small brass compass, green with verdigris, its face crowded with etched symbols that made Quinn's eyes water when she tried to focus…" | | 2 | "Felt the old cold weight settle behind her ribs — the same weight she'd carried since Morris died three years ago, on a case that had never made sense either." | | 3 | "Through the plastic, the needle held its impossible bearing, tugging toward the dark as if the dark were north itself." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 45 | | tagDensity | 0.111 | | leniency | 0.222 | | rawRatio | 0.2 | | effectiveRatio | 0.044 | |