| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 1 | | adverbTags | | 0 | "A young PC stepped aside [aside]" |
| | dialogueSentences | 36 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0.167 | | effectiveRatio | 0.056 | |
| 90.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1091 | | totalAiIsmAdverbs | 2 | | 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) | |
| 72.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1091 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "perfect" | | 1 | "measured" | | 2 | "etched" | | 3 | "trembled" | | 4 | "magnetic" | | 5 | "pulsed" |
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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 | 68 | | matches | (empty) | |
| 79.83% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 68 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1099 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 72.68% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 776 | | uniqueNames | 10 | | maxNameDensity | 1.55 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 12 | | Camden | 1 | | Town | 1 | | Tube | 1 | | Northern | 1 | | Line | 1 | | Khan | 6 | | Morris | 2 | | Deptford | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tube" | | 3 | "Khan" | | 4 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "Town" | | 2 | "Deptford" |
| | globalScore | 0.727 | | windowScore | 0.833 | |
| 47.96% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like he hadn't slept in a week" | | 1 | "looked like chalk, but the marks absorbed" |
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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 | 1099 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 24.98 | | std | 21.41 | | cv | 0.857 | | sampleLengths | | 0 | 67 | | 1 | 15 | | 2 | 51 | | 3 | 57 | | 4 | 7 | | 5 | 52 | | 6 | 3 | | 7 | 3 | | 8 | 61 | | 9 | 54 | | 10 | 9 | | 11 | 39 | | 12 | 37 | | 13 | 11 | | 14 | 4 | | 15 | 2 | | 16 | 23 | | 17 | 9 | | 18 | 62 | | 19 | 32 | | 20 | 14 | | 21 | 6 | | 22 | 58 | | 23 | 1 | | 24 | 26 | | 25 | 15 | | 26 | 53 | | 27 | 3 | | 28 | 19 | | 29 | 4 | | 30 | 21 | | 31 | 71 | | 32 | 4 | | 33 | 5 | | 34 | 29 | | 35 | 7 | | 36 | 30 | | 37 | 6 | | 38 | 4 | | 39 | 24 | | 40 | 35 | | 41 | 44 | | 42 | 14 | | 43 | 8 |
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| 74.30% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 68 | | matches | | 0 | "been closed" | | 1 | "been sealed" | | 2 | "were polished" | | 3 | "been moved" | | 4 | "was buried" | | 5 | "was obscured" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 122 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 98 | | ratio | 0.051 | | matches | | 0 | "The predawn air carried the mineral bite of old concrete and something else — ozone, sharp as a broken circuit." | | 1 | "Abandoned since the nineties, the old Northern Line spur had been sealed behind concrete barricades until someone — or something — had cracked them open." | | 2 | "The man wore a tweed jacket with leather patches on the elbows — academic, Quinn's brain catalogued — and his shoes were polished to a mirror shine." | | 3 | "They weren't like anything she'd seen before — not the usual satanic panic scratches or wannabe cult graffiti." | | 4 | "Behind it, something pulsed — a faint light, the color of a bruise." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 775 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.027096774193548386 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0064516129032258064 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 11.21 | | std | 7.45 | | cv | 0.664 | | sampleLengths | | 0 | 25 | | 1 | 20 | | 2 | 7 | | 3 | 15 | | 4 | 6 | | 5 | 9 | | 6 | 3 | | 7 | 16 | | 8 | 19 | | 9 | 3 | | 10 | 10 | | 11 | 15 | | 12 | 25 | | 13 | 17 | | 14 | 7 | | 15 | 17 | | 16 | 16 | | 17 | 19 | | 18 | 3 | | 19 | 3 | | 20 | 13 | | 21 | 27 | | 22 | 2 | | 23 | 5 | | 24 | 14 | | 25 | 9 | | 26 | 14 | | 27 | 8 | | 28 | 23 | | 29 | 6 | | 30 | 3 | | 31 | 5 | | 32 | 34 | | 33 | 13 | | 34 | 17 | | 35 | 5 | | 36 | 2 | | 37 | 11 | | 38 | 4 | | 39 | 2 | | 40 | 23 | | 41 | 3 | | 42 | 6 | | 43 | 24 | | 44 | 18 | | 45 | 16 | | 46 | 4 | | 47 | 32 | | 48 | 6 | | 49 | 8 |
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| 88.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.5612244897959183 | | totalSentences | 98 | | uniqueOpeners | 55 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 62 | | matches | | 0 | "She took the stairs two" | | 1 | "He was thirty-two, sharp as" | | 2 | "His face was peaceful, eyes" | | 3 | "It pooled around the body" | | 4 | "They weren't like anything she'd" | | 5 | "She stood, brushing dust from" | | 6 | "Her partner Morris had received" | | 7 | "She lifted it carefully, turning" | | 8 | "It had been old when" | | 9 | "He leaned in." | | 10 | "He'd worked with Quinn long" | | 11 | "He turned and began issuing" | | 12 | "She pulled out her phone" | | 13 | "It rang twice." |
| | ratio | 0.226 | |
| 64.84% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 62 | | matches | | 0 | "Detective Harlow Quinn ducked under" | | 1 | "The predawn air carried the" | | 2 | "The Tube had been closed" | | 3 | "Uniforms milled about the stairwell," | | 4 | "A young PC stepped aside" | | 5 | "Quinn didn't answer." | | 6 | "She took the stairs two" | | 7 | "This one hummed." | | 8 | "A frequency just below hearing," | | 9 | "The platform stretched into darkness" | | 10 | "The rubble lay scattered across" | | 11 | "DS Khan straightened from behind" | | 12 | "He was thirty-two, sharp as" | | 13 | "The body lay in the" | | 14 | "The man wore a tweed" | | 15 | "His face was peaceful, eyes" | | 16 | "It pooled around the body" | | 17 | "Khan swiped at his tablet." | | 18 | "Quinn circled the body at" | | 19 | "The platform stretched fifty meters" |
| | ratio | 0.79 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 62 | | matches | | 0 | "By the time they'd arrived" | | 1 | "If he'd been moved post-mortem," |
| | ratio | 0.032 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 1 | | matches | | 0 | "These were precise, geometric, overlapping in ways that made her eyes want to slide off them." |
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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 | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 36 | | tagDensity | 0.056 | | leniency | 0.111 | | rawRatio | 0 | | effectiveRatio | 0 | |