| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 4 | | adverbTags | | 0 | "quick-thinking edge she’d always [always]" | | 1 | "she said finally [finally]" | | 2 | "She gestured vaguely [vaguely]" | | 3 | "She looked away [away]" |
| | dialogueSentences | 21 | | tagDensity | 0.571 | | leniency | 1 | | rawRatio | 0.333 | | effectiveRatio | 0.333 | |
| 71.80% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1064 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "slightly" | | 1 | "suddenly" | | 2 | "slowly" | | 3 | "carefully" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 24.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1064 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "scanning" | | 1 | "familiar" | | 2 | "weight" | | 3 | "etched" | | 4 | "unspoken" | | 5 | "potential" | | 6 | "flicker" | | 7 | "charged" | | 8 | "silence" | | 9 | "tangible" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 50 | | matches | (empty) | |
| 85.71% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 50 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 57 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1057 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 843 | | uniqueNames | 14 | | maxNameDensity | 0.83 | | worstName | "Silas" | | maxWindowNameDensity | 2 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Carter | 1 | | Rory | 2 | | Yu-Fei | 1 | | Cheung | 1 | | Golden | 1 | | Empress | 1 | | Silas | 7 | | Cardiff | 2 | | Blackwood | 1 | | Spymaster | 1 | | Evan | 1 | | London | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Rory" | | 4 | "Yu-Fei" | | 5 | "Cheung" | | 6 | "Silas" | | 7 | "Blackwood" | | 8 | "Evan" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 96.81% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like a ghost she’d thought she’d l" |
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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 | 1057 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 57 | | matches | (empty) | |
| 49.51% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 12 | | mean | 88.08 | | std | 28.48 | | cv | 0.323 | | sampleLengths | | 0 | 131 | | 1 | 129 | | 2 | 23 | | 3 | 97 | | 4 | 96 | | 5 | 61 | | 6 | 108 | | 7 | 100 | | 8 | 78 | | 9 | 75 | | 10 | 88 | | 11 | 71 |
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| 91.23% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 50 | | matches | | 0 | "were etched" | | 1 | "was, struck" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 136 | | matches | | |
| 42.61% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 57 | | ratio | 0.035 | | matches | | 0 | "She hadn’t come for him; she’d come for the ghost of who she’d been, for the weight of the life she’d left behind." | | 1 | "He knew the score; he’d seen the change in her, the way she moved, the guarded look in her eyes." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 850 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.03529411764705882 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.01764705882352941 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 57 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 57 | | mean | 18.54 | | std | 9.09 | | cv | 0.49 | | sampleLengths | | 0 | 22 | | 1 | 26 | | 2 | 30 | | 3 | 23 | | 4 | 30 | | 5 | 37 | | 6 | 27 | | 7 | 26 | | 8 | 39 | | 9 | 10 | | 10 | 13 | | 11 | 12 | | 12 | 8 | | 13 | 22 | | 14 | 25 | | 15 | 16 | | 16 | 14 | | 17 | 12 | | 18 | 23 | | 19 | 11 | | 20 | 38 | | 21 | 12 | | 22 | 23 | | 23 | 15 | | 24 | 23 | | 25 | 25 | | 26 | 22 | | 27 | 20 | | 28 | 31 | | 29 | 10 | | 30 | 9 | | 31 | 17 | | 32 | 24 | | 33 | 16 | | 34 | 13 | | 35 | 16 | | 36 | 5 | | 37 | 7 | | 38 | 11 | | 39 | 15 | | 40 | 24 | | 41 | 4 | | 42 | 1 | | 43 | 16 | | 44 | 9 | | 45 | 18 | | 46 | 11 | | 47 | 33 | | 48 | 4 | | 49 | 10 |
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| 59.65% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.42105263157894735 | | totalSentences | 57 | | uniqueOpeners | 24 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 49 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 49 | | matches | | 0 | "She’d been delivering for Yu-Fei" | | 1 | "She’d been scanning the familiar," | | 2 | "Her own life had become" | | 3 | "She’d changed, yes, but the" | | 4 | "She’d thought she’d left the" | | 5 | "His voice, low and gravelly," | | 6 | "She blinked, the name rolling" | | 7 | "She pushed her straight, shoulder-length" | | 8 | "Her voice was cool, practiced," | | 9 | "She took a seat on" | | 10 | "He turned fully, his hazel" | | 11 | "He nodded slowly, a ghost" | | 12 | "He gestured to the glass" | | 13 | "she said, her gaze drifting" | | 14 | "She hadn’t come for him;" | | 15 | "He knew the score; he’d" | | 16 | "He took a slow sip" | | 17 | "She’d left Cardiff because of" | | 18 | "She’d left because she’d realized" | | 19 | "She’d fled to London, to" |
| | ratio | 0.592 | |
| 0.82% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 49 | | matches | | 0 | "The green neon sign blinked" | | 1 | "The low hum of the" | | 2 | "Aurora Carter, or Rory, as" | | 3 | "She’d been delivering for Yu-Fei" | | 4 | "She’d been scanning the familiar," | | 5 | "Her own life had become" | | 6 | "She’d changed, yes, but the" | | 7 | "She’d thought she’d left the" | | 8 | "His voice, low and gravelly," | | 9 | "She blinked, the name rolling" | | 10 | "The word felt heavy, laden" | | 11 | "She pushed her straight, shoulder-length" | | 12 | "Her voice was cool, practiced," | | 13 | "She took a seat on" | | 14 | "The bar smelled of him" | | 15 | "He turned fully, his hazel" | | 16 | "The years were etched deeper" | | 17 | "He nodded slowly, a ghost" | | 18 | "He gestured to the glass" | | 19 | "she said, her gaze drifting" |
| | ratio | 0.918 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 49 | | matches | | | ratio | 0.02 | |
| 73.73% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 3 | | matches | | 0 | "She’d been scanning the familiar, slightly grimy booths and the worn leather stools at the polished mahogany bar, looking for any sign of the man who’d been her…" | | 1 | "She’d changed, yes, but the core, the sharp, quick mind that had once plotted escape routes and legal loopholes, was still there, buried under the routine." | | 2 | "Silas Blackwood, the Spymaster, the man who’d taught her to read people like open books, to see the lies beneath the surface, watched her carefully." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 4 | | matches | | 0 | "He took, the amber liquid catching the neon light" | | 1 | "she said finally, her voice low" | | 2 | "she insisted, her voice rising slightly" | | 3 | "He saw, the ghost of the girl who’d once been unafraid" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 21 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0.333 | | effectiveRatio | 0.095 | |