| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn crouched again [again]" |
| | dialogueSentences | 53 | | tagDensity | 0.321 | | leniency | 0.642 | | rawRatio | 0.059 | | effectiveRatio | 0.038 | |
| 93.67% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1581 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 39.91% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1581 | | totalAiIsms | 19 | | found | | | highlights | | 0 | "standard" | | 1 | "weight" | | 2 | "perfect" | | 3 | "echoed" | | 4 | "scanned" | | 5 | "chaotic" | | 6 | "database" | | 7 | "pulse" | | 8 | "etched" | | 9 | "porcelain" | | 10 | "trembled" | | 11 | "footsteps" | | 12 | "echoing" | | 13 | "pulsed" | | 14 | "could feel" |
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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 | 114 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 114 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 150 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1580 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 97.62% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1050 | | uniqueNames | 16 | | maxNameDensity | 1.05 | | worstName | "Patel" | | maxWindowNameDensity | 2 | | worstWindowName | "Patel" | | discoveredNames | | Chapter | 1 | | Four | 1 | | Quinn | 10 | | Patel | 11 | | Victorian | 1 | | Lyons | 1 | | Tea | 1 | | Three | 4 | | Home | 1 | | Office | 1 | | Morris | 2 | | Cashmere | 1 | | Harrods | 1 | | Bermondsey | 1 | | Transport | 1 | | London | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Patel" | | 2 | "Tea" | | 3 | "Three" | | 4 | "Morris" |
| | places | | | globalScore | 0.976 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.633 | | wordCount | 1580 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 150 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 64 | | mean | 24.69 | | std | 21.13 | | cv | 0.856 | | sampleLengths | | 0 | 3 | | 1 | 5 | | 2 | 69 | | 3 | 39 | | 4 | 41 | | 5 | 1 | | 6 | 4 | | 7 | 21 | | 8 | 42 | | 9 | 40 | | 10 | 11 | | 11 | 25 | | 12 | 3 | | 13 | 42 | | 14 | 10 | | 15 | 37 | | 16 | 72 | | 17 | 61 | | 18 | 6 | | 19 | 51 | | 20 | 16 | | 21 | 6 | | 22 | 38 | | 23 | 1 | | 24 | 56 | | 25 | 7 | | 26 | 5 | | 27 | 4 | | 28 | 64 | | 29 | 21 | | 30 | 5 | | 31 | 38 | | 32 | 37 | | 33 | 56 | | 34 | 7 | | 35 | 57 | | 36 | 12 | | 37 | 14 | | 38 | 8 | | 39 | 45 | | 40 | 8 | | 41 | 29 | | 42 | 40 | | 43 | 37 | | 44 | 10 | | 45 | 1 | | 46 | 2 | | 47 | 50 | | 48 | 5 | | 49 | 2 |
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| 89.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 114 | | matches | | 0 | "been removed" | | 1 | "were tiled" | | 2 | "was etched" | | 3 | "been stored" | | 4 | "been open" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 172 | | matches | | 0 | "was staring" | | 1 | "was constructing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 150 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1054 | | adjectiveStacks | 1 | | stackExamples | | 0 | "suggested regular, repeated traffic." |
| | adverbCount | 39 | | adverbRatio | 0.03700189753320683 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.009487666034155597 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 150 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 150 | | mean | 10.53 | | std | 9.16 | | cv | 0.87 | | sampleLengths | | 0 | 8 | | 1 | 29 | | 2 | 22 | | 3 | 18 | | 4 | 24 | | 5 | 15 | | 6 | 3 | | 7 | 7 | | 8 | 2 | | 9 | 4 | | 10 | 8 | | 11 | 12 | | 12 | 2 | | 13 | 3 | | 14 | 1 | | 15 | 4 | | 16 | 3 | | 17 | 18 | | 18 | 13 | | 19 | 23 | | 20 | 6 | | 21 | 26 | | 22 | 14 | | 23 | 11 | | 24 | 3 | | 25 | 13 | | 26 | 9 | | 27 | 3 | | 28 | 15 | | 29 | 14 | | 30 | 13 | | 31 | 10 | | 32 | 16 | | 33 | 12 | | 34 | 9 | | 35 | 26 | | 36 | 8 | | 37 | 23 | | 38 | 15 | | 39 | 6 | | 40 | 10 | | 41 | 23 | | 42 | 12 | | 43 | 10 | | 44 | 6 | | 45 | 13 | | 46 | 38 | | 47 | 16 | | 48 | 6 | | 49 | 24 |
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| 72.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.46 | | totalSentences | 150 | | uniqueOpeners | 69 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 93 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 93 | | matches | | 0 | "She studied the dead man's" | | 1 | "His wallet sat in his" | | 2 | "She shifted her weight, angling" | | 3 | "She looked up at him" | | 4 | "He looked at the pool," | | 5 | "His mouth worked around the" | | 6 | "She turned the wrist toward" | | 7 | "She released the hand and" | | 8 | "She moved to the wall," | | 9 | "She pressed the tile with" | | 10 | "She'd smelled it at scenes" | | 11 | "Her fingers found her watch" | | 12 | "She checked the time." | | 13 | "She worked her fingers into" | | 14 | "It pointed straight down." | | 15 | "She held it up to" | | 16 | "She walked the platform's edge," | | 17 | "He was staring at the" | | 18 | "She crossed back and knelt." | | 19 | "They'd been open when she'd" |
| | ratio | 0.269 | |
| 40.65% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 93 | | matches | | 0 | "# Chapter Four The body" | | 1 | "Quinn crouched beside the dead" | | 2 | "The forensic team's halogen lamps" | | 3 | "Camden's forgotten station, sealed since" | | 4 | "Patel crouched across from her," | | 5 | "Quinn didn't answer." | | 6 | "She studied the dead man's" | | 7 | "A £400 watch on his" | | 8 | "His wallet sat in his" | | 9 | "Patel glanced down." | | 10 | "She shifted her weight, angling" | | 11 | "She looked up at him" | | 12 | "Patel pointed his penlight toward" | | 13 | "Patel's penlight dipped." | | 14 | "He looked at the pool," | | 15 | "His mouth worked around the" | | 16 | "Quinn pulled on a fresh" | | 17 | "The wrist bore a faint" | | 18 | "She turned the wrist toward" | | 19 | "The skin was pale in" |
| | ratio | 0.839 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 93 | | matches | (empty) | | ratio | 0 | |
| 30.08% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 6 | | matches | | 0 | "Quinn crouched beside the dead man, her knees pressing into damp concrete that smelled of mould and rust and something older, something chemical and sweet that …" | | 1 | "She released the hand and it dropped back against the concrete with a soft thud that echoed longer than it should have in the narrow station." | | 2 | "The platform held signs of habitation that didn't belong in a sealed station: footprints in the dust, dozens of them, overlapped and chaotic." | | 3 | "She'd smelled it at scenes before, in basements where ritual groups met, in squats where alchemists cooked substances that didn't appear in any Home Office data…" | | 4 | "Each image was evidence of something that didn't fit the narrative Patel was constructing." | | 5 | "Quinn stood alone with the dead man and his cracked, darkening eyes and the compass that wouldn't point north." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 53 | | tagDensity | 0.019 | | leniency | 0.038 | | rawRatio | 1 | | effectiveRatio | 0.038 | |