| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn repeated slowly [slowly]" |
| | dialogueSentences | 41 | | tagDensity | 0.512 | | leniency | 1 | | rawRatio | 0.048 | | effectiveRatio | 0.048 | |
| 77.31% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1102 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "carefully" | | 2 | "really" | | 3 | "slowly" |
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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) | |
| 50.09% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1102 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "gloom" | | 1 | "echoing" | | 2 | "standard" | | 3 | "scanning" | | 4 | "spectral" | | 5 | "perfect" | | 6 | "disrupt" | | 7 | "racing" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 80 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 80 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 100 | | 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 | 5 | | markdownWords | 5 | | totalWords | 1094 | | ratio | 0.005 | | matches | | 0 | "everything" | | 1 | "in" | | 2 | "because" | | 3 | "control" | | 4 | "everything" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 6.23% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 626 | | uniqueNames | 13 | | maxNameDensity | 2.88 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 18 | | Tube | 1 | | Camden | 1 | | Veil | 1 | | Market | 1 | | Miller | 7 | | Detective | 2 | | Inspector | 1 | | Davies | 7 | | Eva | 3 | | Kowalski | 1 | | Shadow | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Miller" | | 4 | "Inspector" | | 5 | "Davies" | | 6 | "Eva" | | 7 | "Kowalski" |
| | places | (empty) | | globalScore | 0.062 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 50 | | glossingSentenceCount | 1 | | matches | | 0 | "tasted like wet concrete and something el" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.914 | | wordCount | 1094 | | matches | | 0 | "not exactly lethal, but it induces a state of complete paralysis" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 100 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 32.18 | | std | 18.17 | | cv | 0.565 | | sampleLengths | | 0 | 86 | | 1 | 40 | | 2 | 8 | | 3 | 39 | | 4 | 44 | | 5 | 18 | | 6 | 15 | | 7 | 10 | | 8 | 27 | | 9 | 47 | | 10 | 18 | | 11 | 15 | | 12 | 43 | | 13 | 48 | | 14 | 20 | | 15 | 6 | | 16 | 40 | | 17 | 14 | | 18 | 48 | | 19 | 20 | | 20 | 23 | | 21 | 19 | | 22 | 50 | | 23 | 18 | | 24 | 28 | | 25 | 55 | | 26 | 55 | | 27 | 28 | | 28 | 7 | | 29 | 27 | | 30 | 48 | | 31 | 47 | | 32 | 24 | | 33 | 59 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 80 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 114 | | matches | (empty) | |
| 28.57% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 100 | | ratio | 0.04 | | matches | | 0 | "The initial assessment—multiple stab wounds—suggested a straightforward mugging gone wrong." | | 1 | "Wallet, phone, a thick roll of cash—all present." | | 2 | "He was fresh out of the academy, and this – this wasn’t a regular crime scene." | | 3 | "Her focus landed on something Miller had overlooked—a single, iridescent scale, clinging to the hem of the victim’s suit." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 675 | | adjectiveStacks | 1 | | stackExamples | | 0 | "faded, leather-bound book." |
| | adverbCount | 26 | | adverbRatio | 0.03851851851851852 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.014814814814814815 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 100 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 100 | | mean | 10.94 | | std | 7.47 | | cv | 0.682 | | sampleLengths | | 0 | 9 | | 1 | 2 | | 2 | 14 | | 3 | 22 | | 4 | 13 | | 5 | 6 | | 6 | 10 | | 7 | 10 | | 8 | 18 | | 9 | 2 | | 10 | 6 | | 11 | 10 | | 12 | 1 | | 13 | 3 | | 14 | 8 | | 15 | 11 | | 16 | 21 | | 17 | 7 | | 18 | 11 | | 19 | 6 | | 20 | 8 | | 21 | 6 | | 22 | 8 | | 23 | 5 | | 24 | 18 | | 25 | 4 | | 26 | 11 | | 27 | 8 | | 28 | 2 | | 29 | 11 | | 30 | 16 | | 31 | 4 | | 32 | 12 | | 33 | 20 | | 34 | 3 | | 35 | 1 | | 36 | 3 | | 37 | 2 | | 38 | 2 | | 39 | 18 | | 40 | 12 | | 41 | 3 | | 42 | 3 | | 43 | 31 | | 44 | 5 | | 45 | 4 | | 46 | 11 | | 47 | 13 | | 48 | 24 | | 49 | 3 |
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| 80.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.52 | | totalSentences | 100 | | uniqueOpeners | 52 | |
| 47.62% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 70 | | matches | | 0 | "Just then Eva Kowalski pushed" |
| | ratio | 0.014 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 70 | | matches | | 0 | "She swept her gaze across" | | 1 | "It was the Veil Market’s" | | 2 | "He held up a small," | | 3 | "He was fresh out of" | | 4 | "She moved past the body," | | 5 | "It was mostly overturned, merchandise" | | 6 | "She moved towards a darkened" | | 7 | "She knelt, examining the shimmering" | | 8 | "She ran a gloved hand" | | 9 | "She gestured to the meticulously" | | 10 | "It all felt too perfect," | | 11 | "Her focus landed on something" | | 12 | "She carefully plucked it with" | | 13 | "she said, holding up the" | | 14 | "She hurried towards Quinn, her" | | 15 | "She fiddled with her hair" | | 16 | "She produced a faded, leather-bound" | | 17 | "She flipped through the bestiary," | | 18 | "It explained the victim’s apparent" | | 19 | "She looks at Miller" |
| | ratio | 0.3 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 70 | | matches | | 0 | "The air tasted like wet" | | 1 | "Detective Harlow Quinn wrinkled her" | | 2 | "She swept her gaze across" | | 3 | "Water dripped from the arched" | | 4 | "This wasn’t just any abandoned" | | 5 | "This was beneath Camden, a" | | 6 | "It was the Veil Market’s" | | 7 | "A body lay sprawled near" | | 8 | "The initial assessment—multiple stab wounds—suggested" | | 9 | "nothing felt straightforward." | | 10 | "Quinn asked, her voice echoing" | | 11 | "A younger officer, Miller, knelt" | | 12 | "He held up a small," | | 13 | "Quinn circled the body, her" | | 14 | "The wounds were precise, almost" | | 15 | "Wallet, phone, a thick roll" | | 16 | "A robbery wouldn't explain that." | | 17 | "Quinn asked, her eyes scanning" | | 18 | "Miller shook his head." | | 19 | "Quinn paused, tilting her head" |
| | ratio | 0.929 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 70 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 29.76% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 4 | | matches | | 0 | "Quinn asked, her voice echoing slightly" | | 1 | "Quinn declared, her voice low and firm" | | 2 | "Eva said, breathlessly" | | 3 | "Quinn closed, her mind racing" |
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| 28.05% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 5 | | fancyTags | | 0 | "Quinn questioned (question)" | | 1 | "Quinn declared (declare)" | | 2 | "she explained (explain)" | | 3 | "Quinn repeated slowly (repeat)" | | 4 | "Quinn retorted (retort)" |
| | dialogueSentences | 41 | | tagDensity | 0.268 | | leniency | 0.537 | | rawRatio | 0.455 | | effectiveRatio | 0.244 | |