| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "He pointed vaguely [vaguely]" |
| | dialogueSentences | 35 | | tagDensity | 0.486 | | leniency | 0.971 | | rawRatio | 0.059 | | effectiveRatio | 0.057 | |
| 88.23% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1274 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "gently" | | 1 | "carefully" | | 2 | "slightly" |
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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) | |
| 52.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1274 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "gloom" | | 1 | "quivered" | | 2 | "echoed" | | 3 | "etched" | | 4 | "intricate" | | 5 | "weight" | | 6 | "perfect" | | 7 | "chill" | | 8 | "flickered" | | 9 | "vibrated" |
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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 | 101 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 101 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 117 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 31 | | totalWords | 1274 | | ratio | 0.024 | | matches | | 0 | "Three years ago. Unexplained circumstances. A warehouse by the docks. Symbols on the walls that glowed then faded. Morris's last words: 'It's not a drug deal, Harlow. It's a door.'" | | 1 | "second" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 82.92% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 969 | | uniqueNames | 15 | | maxNameDensity | 1.34 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 13 | | Detective | 2 | | Sergeant | 1 | | Pritchard | 9 | | Tube | 1 | | Morris | 4 | | Protocol | 1 | | Eva | 1 | | Kowalski | 1 | | British | 1 | | Museum | 1 | | Ancient | 1 | | History | 1 | | London | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Pritchard" | | 4 | "Morris" | | 5 | "Protocol" | | 6 | "Eva" | | 7 | "Kowalski" | | 8 | "Museum" |
| | places | | 0 | "British" | | 1 | "Ancient" | | 2 | "London" |
| | globalScore | 0.829 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.785 | | wordCount | 1274 | | matches | | 0 | "not toward the tunnel mouth where the uniformed officers stood, but toward the black emptiness of the disused tracks" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 117 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 32.67 | | std | 25.26 | | cv | 0.773 | | sampleLengths | | 0 | 9 | | 1 | 99 | | 2 | 26 | | 3 | 43 | | 4 | 6 | | 5 | 63 | | 6 | 74 | | 7 | 5 | | 8 | 13 | | 9 | 51 | | 10 | 24 | | 11 | 16 | | 12 | 78 | | 13 | 7 | | 14 | 61 | | 15 | 8 | | 16 | 47 | | 17 | 7 | | 18 | 14 | | 19 | 1 | | 20 | 24 | | 21 | 49 | | 22 | 16 | | 23 | 4 | | 24 | 60 | | 25 | 16 | | 26 | 26 | | 27 | 24 | | 28 | 62 | | 29 | 46 | | 30 | 8 | | 31 | 48 | | 32 | 55 | | 33 | 8 | | 34 | 54 | | 35 | 18 | | 36 | 2 | | 37 | 65 | | 38 | 37 |
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| 87.89% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 101 | | matches | | 0 | "was etched" | | 1 | "was disturbed" | | 2 | "been swept" | | 3 | "was scuffed" | | 4 | "been curled" |
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| 13.52% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 143 | | matches | | 0 | "weren't looking" | | 1 | "was looking" | | 2 | "was already walking" | | 3 | "was still pointing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 117 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 720 | | adjectiveStacks | 1 | | stackExamples | | 0 | "perfect, coin-sized hole" |
| | adverbCount | 13 | | adverbRatio | 0.018055555555555554 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.006944444444444444 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 117 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 117 | | mean | 10.89 | | std | 7.37 | | cv | 0.677 | | sampleLengths | | 0 | 9 | | 1 | 26 | | 2 | 20 | | 3 | 20 | | 4 | 33 | | 5 | 8 | | 6 | 7 | | 7 | 11 | | 8 | 4 | | 9 | 14 | | 10 | 18 | | 11 | 7 | | 12 | 6 | | 13 | 26 | | 14 | 14 | | 15 | 16 | | 16 | 7 | | 17 | 19 | | 18 | 5 | | 19 | 30 | | 20 | 14 | | 21 | 6 | | 22 | 5 | | 23 | 9 | | 24 | 4 | | 25 | 6 | | 26 | 12 | | 27 | 6 | | 28 | 9 | | 29 | 18 | | 30 | 7 | | 31 | 17 | | 32 | 16 | | 33 | 16 | | 34 | 4 | | 35 | 16 | | 36 | 3 | | 37 | 24 | | 38 | 4 | | 39 | 11 | | 40 | 7 | | 41 | 5 | | 42 | 10 | | 43 | 4 | | 44 | 23 | | 45 | 3 | | 46 | 7 | | 47 | 6 | | 48 | 3 | | 49 | 8 |
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| 72.65% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.46153846153846156 | | totalSentences | 117 | | uniqueOpeners | 54 | |
| 35.46% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 94 | | matches | | | ratio | 0.011 | |
| 92.34% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 94 | | matches | | 0 | "His voice echoed in the" | | 1 | "She used a gloved finger" | | 2 | "she repeated, her tone flat" | | 3 | "He was a good detective," | | 4 | "She stood, her knees protesting." | | 5 | "It was clean." | | 6 | "It smelled, when she leaned" | | 7 | "she asked Pritchard" | | 8 | "He handed her a swab." | | 9 | "She took a sample of" | | 10 | "Her torch moved lower." | | 11 | "She probed it with a" | | 12 | "It went deep." | | 13 | "Her mind worked, piecing the" | | 14 | "He frowned, pulling out his" | | 15 | "He pointed vaguely in the" | | 16 | "she said, her voice low" | | 17 | "She looked at the evidence" | | 18 | "She held up the swab" | | 19 | "He knew about Morris." |
| | ratio | 0.319 | |
| 66.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 94 | | matches | | 0 | "Detective Harlow Quinn catalogued them" | | 1 | "His voice echoed in the" | | 2 | "Quinn didn't look up." | | 3 | "She used a gloved finger" | | 4 | "The casing had a greenish" | | 5 | "The needle held its stubborn," | | 6 | "she repeated, her tone flat" | | 7 | "Pritchard shifted his weight" | | 8 | "He was a good detective," | | 9 | "A body in an old" | | 10 | "The case would be closed" | | 11 | "Quinn placed the compass carefully" | | 12 | "She stood, her knees protesting." | | 13 | "The platform was a time" | | 14 | "Pritchard pointed his own torch" | | 15 | "Quinn leaned over the platform" | | 16 | "The beam illuminated the crumpled" | | 17 | "Quinn turned, sweeping her light" | | 18 | "The beam caught something." | | 19 | "A section of the old" |
| | ratio | 0.787 | |
| 53.19% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 94 | | matches | | | ratio | 0.011 | |
| 79.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 3 | | matches | | 0 | "First, the left pocket of his waxed jacket was turned inside out, the lining stained with something that wasn't blood." | | 1 | "Beyond that, it lay smooth and untouched, as if the man had materialised mid-air and dropped straight down." | | 2 | "Everyone did, though the official report blamed faulty electrical wiring for the fire that consumed the evidence." |
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| 36.76% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 3 | | matches | | 0 | "she repeated, her tone flat" | | 1 | "she said, her voice low and final" | | 2 | "she said, her bearing rigid with military precision" |
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| 64.29% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 3 | | fancyTags | | 0 | "she repeated (repeat)" | | 1 | "she ordered (order)" | | 2 | "he muttered (mutter)" |
| | dialogueSentences | 35 | | tagDensity | 0.229 | | leniency | 0.457 | | rawRatio | 0.375 | | effectiveRatio | 0.171 | |