| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 1 | | adverbTags | | 0 | "She crouched again [again]" |
| | dialogueSentences | 31 | | tagDensity | 0.484 | | leniency | 0.968 | | rawRatio | 0.067 | | effectiveRatio | 0.065 | |
| 82.47% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1141 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slowly" | | 1 | "very" | | 2 | "loosely" | | 3 | "gently" |
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| 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) | |
| 73.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1141 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "weight" | | 1 | "tinge" | | 2 | "traced" | | 3 | "etched" | | 4 | "quivered" |
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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 | 58 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 58 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 73 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 8 | | markdownWords | 27 | | totalWords | 1131 | | ratio | 0.024 | | matches | | 0 | "Walk the scene like it's lying to you," | | 1 | "Because it is." | | 2 | "around" | | 3 | "gas leak" | | 4 | "hallucination" | | 5 | "unexplained." | | 6 | "what" | | 7 | "you don't have the vocabulary for what you're investigating, detective." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 832 | | uniqueNames | 10 | | maxNameDensity | 0.84 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Pratt" | | discoveredNames | | Underground | 1 | | Harlow | 1 | | Quinn | 7 | | London | 1 | | Sergeant | 1 | | Aldous | 1 | | Pratt | 7 | | Morris | 2 | | Eva | 1 | | Kowalski | 1 |
| | persons | | 0 | "Underground" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Sergeant" | | 4 | "Pratt" | | 5 | "Morris" | | 6 | "Eva" | | 7 | "Kowalski" |
| | places | | | globalScore | 1 | | windowScore | 0.833 | |
| 94.44% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 45 | | glossingSentenceCount | 1 | | matches | | 0 | "body but not, evidently, looked beneath it" |
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| 23.17% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.768 | | wordCount | 1131 | | matches | | 0 | "neither pinned nor" | | 1 | "not with the cardinal points but with a ring of fine, deliberate sigils, the same family of m" |
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| 29.68% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 73 | | matches | | 0 | "let that sit" | | 1 | "reports that night" | | 2 | "knew that a" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 39 | | std | 31.45 | | cv | 0.806 | | sampleLengths | | 0 | 95 | | 1 | 56 | | 2 | 25 | | 3 | 69 | | 4 | 27 | | 5 | 43 | | 6 | 18 | | 7 | 66 | | 8 | 6 | | 9 | 43 | | 10 | 48 | | 11 | 4 | | 12 | 5 | | 13 | 77 | | 14 | 14 | | 15 | 26 | | 16 | 2 | | 17 | 53 | | 18 | 18 | | 19 | 79 | | 20 | 39 | | 21 | 94 | | 22 | 10 | | 23 | 9 | | 24 | 120 | | 25 | 28 | | 26 | 1 | | 27 | 40 | | 28 | 16 |
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| 87.11% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 58 | | matches | | 0 | "were curled" | | 1 | "was furred" | | 2 | "was etched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 142 | | matches | | 0 | "was not pointing" | | 1 | "was lying" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 73 | | ratio | 0.082 | | matches | | 0 | "Detective Harlow Quinn descended it the way she descended everything—one hand trailing the rail, weight forward, counting steps out of a habit eighteen years of policework had carved into her." | | 1 | "Chalk, yes—but not the careless scrawl of trespassing kids." | | 2 | "\"They do.\" She stood and walked the perimeter once more, and this time something tugged at her—not a thought, a sensation, low in the sternum, a wrongness she had no file for." | | 3 | "The casing was furred with green—verdigris, decades of it, maybe more." | | 4 | "It quivered, swung, settled—and it was not pointing north." | | 5 | "She thought of a name she'd heard whispered twice in eighteen years and dismissed both times—a market that moved with the moon, that traded in things like this." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 840 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.02738095238095238 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.010714285714285714 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 73 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 73 | | mean | 15.49 | | std | 12.33 | | cv | 0.796 | | sampleLengths | | 0 | 30 | | 1 | 30 | | 2 | 2 | | 3 | 33 | | 4 | 18 | | 5 | 8 | | 6 | 30 | | 7 | 9 | | 8 | 11 | | 9 | 5 | | 10 | 3 | | 11 | 9 | | 12 | 22 | | 13 | 16 | | 14 | 19 | | 15 | 27 | | 16 | 14 | | 17 | 16 | | 18 | 13 | | 19 | 14 | | 20 | 4 | | 21 | 10 | | 22 | 56 | | 23 | 3 | | 24 | 3 | | 25 | 20 | | 26 | 20 | | 27 | 3 | | 28 | 7 | | 29 | 15 | | 30 | 11 | | 31 | 15 | | 32 | 4 | | 33 | 2 | | 34 | 3 | | 35 | 10 | | 36 | 33 | | 37 | 34 | | 38 | 6 | | 39 | 8 | | 40 | 21 | | 41 | 5 | | 42 | 2 | | 43 | 12 | | 44 | 38 | | 45 | 3 | | 46 | 6 | | 47 | 4 | | 48 | 8 | | 49 | 32 |
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| 77.63% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.5068493150684932 | | totalSentences | 73 | | uniqueOpeners | 37 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 53 | | matches | (empty) | | ratio | 0 | |
| 61.51% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 53 | | matches | | 0 | "She remembered that detail because" | | 1 | "She crouched at the edge" | | 2 | "He had the satisfied look" | | 3 | "She didn't look up" | | 4 | "She moved around the circle" | | 5 | "His pupils, when she leaned" | | 6 | "She'd seen enough overdoses to" | | 7 | "She pointed without touching" | | 8 | "She crouched again" | | 9 | "She traced the air above" | | 10 | "She let that sit" | | 11 | "She stood and walked the" | | 12 | "She knelt by the dead" | | 13 | "Its face was etched not" | | 14 | "It quivered, swung, settled—and it" | | 15 | "It pointed past her shoulder," | | 16 | "She was lying" | | 17 | "She didn't know *what* it" | | 18 | "She thought of a name" | | 19 | "She thought of Eva Kowalski," |
| | ratio | 0.396 | |
| 26.04% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 46 | | totalSentences | 53 | | matches | | 0 | "The stairwell down to the" | | 1 | "Detective Harlow Quinn descended it" | | 2 | "She remembered that detail because" | | 3 | "The tiles were the colour" | | 4 | "Someone had strung tarpaulin across" | | 5 | "A uniformed constable, young, gripping" | | 6 | "Quinn looked down." | | 7 | "Chalk, yes—but not the careless" | | 8 | "The body lay at the" | | 9 | "A man, middle-aged, in a" | | 10 | "She crouched at the edge" | | 11 | "Detective Sergeant Aldous Pratt came" | | 12 | "He had the satisfied look" | | 13 | "She didn't look up" | | 14 | "Pratt gestured at the body" | | 15 | "She moved around the circle" | | 16 | "The man's face was slack" | | 17 | "His pupils, when she leaned" | | 18 | "She'd seen enough overdoses to" | | 19 | "She pointed without touching" |
| | ratio | 0.868 | |
| 94.34% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 53 | | matches | | | ratio | 0.019 | |
| 19.70% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 5 | | matches | | 0 | "The stairwell down to the platform smelled of wet brick and old electricity, a current that had no business flowing in a station the Underground had sealed off …" | | 1 | "She remembered that detail because it was the sort of thing that mattered later, in courtrooms, when a barrister wanted to know exactly how long it had taken he…" | | 2 | "A man, middle-aged, in a good wool coat that had cost more than the constable made in a fortnight." | | 3 | "The same wrongness that had been waiting in the empty warehouse the night Morris went in ahead of her and never came back out, the night the official report had…" | | 4 | "She thought of Eva Kowalski, the archive girl who'd looked at her too steadily across an interview table last spring and said *you don't have the vocabulary for…" |
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| 91.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 1 | | matches | | 0 | "She traced, not touching" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 31 | | tagDensity | 0.097 | | leniency | 0.194 | | rawRatio | 0 | | effectiveRatio | 0 | |