| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 36 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1189 | | 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) | |
| 70.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1189 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "weight" | | 1 | "pulse" | | 2 | "charm" | | 3 | "etched" | | 4 | "quivered" | | 5 | "warmth" |
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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 | 81 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 81 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 105 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1201 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 699 | | uniqueNames | 8 | | maxNameDensity | 1.57 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Pryce" | | discoveredNames | | Harlow | 1 | | Quinn | 11 | | Tube | 1 | | Pryce | 10 | | Young | 1 | | Council | 1 | | Italian | 1 | | Morris | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Pryce" | | 3 | "Council" | | 4 | "Morris" |
| | places | (empty) | | globalScore | 0.713 | | windowScore | 0.667 | |
| 93.18% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | glossingSentenceCount | 1 | | matches | | 0 | "something between surprise and recognition, his" |
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| 33.47% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.665 | | wordCount | 1201 | | matches | | 0 | "not the surface, but the lining" | | 1 | "not north, but south-southwest, toward the tunnel mouth, trembling" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 105 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 29.29 | | std | 21.21 | | cv | 0.724 | | sampleLengths | | 0 | 17 | | 1 | 51 | | 2 | 38 | | 3 | 3 | | 4 | 62 | | 5 | 56 | | 6 | 44 | | 7 | 30 | | 8 | 6 | | 9 | 10 | | 10 | 52 | | 11 | 3 | | 12 | 61 | | 13 | 44 | | 14 | 17 | | 15 | 34 | | 16 | 7 | | 17 | 64 | | 18 | 26 | | 19 | 30 | | 20 | 14 | | 21 | 3 | | 22 | 17 | | 23 | 4 | | 24 | 50 | | 25 | 12 | | 26 | 6 | | 27 | 51 | | 28 | 36 | | 29 | 5 | | 30 | 54 | | 31 | 12 | | 32 | 63 | | 33 | 6 | | 34 | 40 | | 35 | 73 | | 36 | 7 | | 37 | 40 | | 38 | 13 | | 39 | 14 | | 40 | 26 |
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| 83.60% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 81 | | matches | | 0 | "been decommissioned" | | 1 | "was frozen" | | 2 | "been torn" | | 3 | "been pulled" | | 4 | "was etched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 112 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 105 | | ratio | 0.057 | | matches | | 0 | "Camden Council had sealed the entrances with concrete and steel grating, but someone had cut through a maintenance hatch on the side street — clean work, plasma cutter, done by someone who knew what they were doing." | | 1 | "His hands were clean — manicured, even — and his pockets contained a single bone token, smooth and white, drilled through the center like a bead." | | 2 | "She'd seen one before — three years ago, in DS Morris's notebook, sketched in his careful architect's hand beside a question mark and the words \"entry fee?\" She'd never found out what he'd meant." | | 3 | "Graffiti covered the lower walls — tags, mostly, old and faded." | | 4 | "This time she examined the overcoat — not the surface, but the lining." | | 5 | "She trained her torch on it and saw the verdigris — green oxidation creeping along the edges like moss." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 695 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.02014388489208633 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0028776978417266188 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 105 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 105 | | mean | 11.44 | | std | 11.04 | | cv | 0.966 | | sampleLengths | | 0 | 17 | | 1 | 35 | | 2 | 8 | | 3 | 8 | | 4 | 19 | | 5 | 1 | | 6 | 1 | | 7 | 17 | | 8 | 3 | | 9 | 7 | | 10 | 37 | | 11 | 12 | | 12 | 3 | | 13 | 3 | | 14 | 18 | | 15 | 6 | | 16 | 6 | | 17 | 26 | | 18 | 5 | | 19 | 3 | | 20 | 2 | | 21 | 34 | | 22 | 10 | | 23 | 20 | | 24 | 6 | | 25 | 10 | | 26 | 10 | | 27 | 1 | | 28 | 1 | | 29 | 34 | | 30 | 6 | | 31 | 3 | | 32 | 4 | | 33 | 57 | | 34 | 30 | | 35 | 14 | | 36 | 17 | | 37 | 20 | | 38 | 14 | | 39 | 4 | | 40 | 3 | | 41 | 16 | | 42 | 19 | | 43 | 11 | | 44 | 18 | | 45 | 2 | | 46 | 16 | | 47 | 4 | | 48 | 4 | | 49 | 13 |
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| 79.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.5047619047619047 | | totalSentences | 105 | | uniqueOpeners | 53 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 65 | | matches | | 0 | "Somewhere deeper in the tunnel," | | 1 | "Still wrote things down by" |
| | ratio | 0.031 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 65 | | matches | | 0 | "His shoes were Italian leather," | | 1 | "His hands were clean —" | | 2 | "She'd seen one before —" | | 3 | "She looked at Pryce" | | 4 | "She didn't touch it." | | 5 | "She walked back to the" | | 6 | "She held the fabric up" | | 7 | "She rolled it between her" | | 8 | "She moved toward the southbound" | | 9 | "She trained her torch on" | | 10 | "She picked it up." | | 11 | "It was warm." | | 12 | "She slipped it into an" |
| | ratio | 0.2 | |
| 60.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 65 | | matches | | 0 | "The body lay at the" | | 1 | "The air tasted of rust" | | 2 | "DS Pryce fell into step" | | 3 | "The station had been decommissioned" | | 4 | "Camden Council had sealed the" | | 5 | "Quinn had noted the precision" | | 6 | "The victim was male, mid-thirties," | | 7 | "His shoes were Italian leather," | | 8 | "His hands were clean —" | | 9 | "Quinn crouched beside the body." | | 10 | "The man's expression was frozen" | | 11 | "Quinn turned the bone token" | | 12 | "She'd seen one before —" | | 13 | "Morris had died two weeks" | | 14 | "Pryce flipped a page." | | 15 | "Quinn stood, her knees protesting" | | 16 | "She looked at Pryce" | | 17 | "Pryce closed his notebook." | | 18 | "Quinn walked the perimeter of" | | 19 | "The forensic team had erected" |
| | ratio | 0.8 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 45.45% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 3 | | matches | | 0 | "Camden Council had sealed the entrances with concrete and steel grating, but someone had cut through a maintenance hatch on the side street — clean work, plasma…" | | 1 | "The victim was male, mid-thirties, dressed in a dark overcoat that had cost more than Pryce's monthly salary." | | 2 | "The man's expression was frozen in something between surprise and recognition, his lips parted, his brown eyes fixed on the arched ceiling as though he'd seen s…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 3 | | matches | | 0 | "DS Pryce fell, his notebook already open" | | 1 | "Quinn stood, her knees protesting" | | 2 | "Quinn walked, her torch sweeping the curved tunnel walls" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |