| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 2 | | adverbTags | | 0 | "His eyes darted around [around]" | | 1 | "He asked quietly [quietly]" |
| | dialogueSentences | 36 | | tagDensity | 0.583 | | leniency | 1 | | rawRatio | 0.095 | | effectiveRatio | 0.095 | |
| 91.47% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1173 | | totalAiIsmAdverbs | 2 | | found | | 0 | | | 1 | | adverb | "ever so slightly" | | count | 1 |
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| | highlights | | 0 | "tightly" | | 1 | "ever so slightly" |
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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) | |
| 44.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1173 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "scanned" | | 1 | "echo" | | 2 | "warmth" | | 3 | "flicker" | | 4 | "traced" | | 5 | "reminder" | | 6 | "glint" | | 7 | "comfortable" | | 8 | "silence" | | 9 | "weight" | | 10 | "grapple" | | 11 | "echoed" |
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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 | 2 | | narrationSentences | 67 | | matches | | 0 | "d with determination" | | 1 | "g in fear" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 67 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 94.93% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 81 | | gibberishSentences | 1 | | adjustedGibberishSentences | 1 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0.012 | | matches | | 0 | "\"Same shit, different day. Just need a stiff drink to forget it,\" Roryυννωσα numpyчного+=\" α=20 - β,\" she sighed, downing the Scotch in one bracing gulp." |
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| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1171 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 47.96% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 833 | | uniqueNames | 15 | | maxNameDensity | 2.04 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Carter | 1 | | Raven | 2 | | Nest | 2 | | October | 1 | | Golden | 1 | | Empress | 1 | | Scotch | 1 | | Rory | 17 | | Silas | 12 | | Blackwood | 1 | | Cardiff | 1 | | Guinness | 2 | | Prague | 1 | | Laila | 1 | | Aurora | 2 |
| | persons | | 0 | "Carter" | | 1 | "Rory" | | 2 | "Silas" | | 3 | "Blackwood" | | 4 | "Laila" | | 5 | "Aurora" |
| | places | | 0 | "Raven" | | 1 | "Cardiff" | | 2 | "Prague" |
| | globalScore | 0.48 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1171 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 81 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 35.48 | | std | 20.04 | | cv | 0.565 | | sampleLengths | | 0 | 83 | | 1 | 81 | | 2 | 9 | | 3 | 40 | | 4 | 11 | | 5 | 56 | | 6 | 32 | | 7 | 38 | | 8 | 29 | | 9 | 45 | | 10 | 42 | | 11 | 52 | | 12 | 40 | | 13 | 43 | | 14 | 16 | | 15 | 28 | | 16 | 24 | | 17 | 30 | | 18 | 25 | | 19 | 67 | | 20 | 42 | | 21 | 10 | | 22 | 14 | | 23 | 36 | | 24 | 25 | | 25 | 10 | | 26 | 11 | | 27 | 25 | | 28 | 44 | | 29 | 8 | | 30 | 38 | | 31 | 73 | | 32 | 44 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 67 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 140 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 81 | | ratio | 0.012 | | matches | | 0 | "He knew it all - the bruises, the therapist bills, the late night calls." |
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| 94.18% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 836 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.04665071770334928 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.01674641148325359 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 81 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 81 | | mean | 14.46 | | std | 7.19 | | cv | 0.498 | | sampleLengths | | 0 | 14 | | 1 | 25 | | 2 | 20 | | 3 | 24 | | 4 | 16 | | 5 | 20 | | 6 | 13 | | 7 | 15 | | 8 | 17 | | 9 | 7 | | 10 | 2 | | 11 | 26 | | 12 | 14 | | 13 | 11 | | 14 | 20 | | 15 | 14 | | 16 | 22 | | 17 | 16 | | 18 | 16 | | 19 | 23 | | 20 | 15 | | 21 | 10 | | 22 | 13 | | 23 | 6 | | 24 | 20 | | 25 | 6 | | 26 | 19 | | 27 | 19 | | 28 | 23 | | 29 | 20 | | 30 | 10 | | 31 | 22 | | 32 | 13 | | 33 | 27 | | 34 | 14 | | 35 | 7 | | 36 | 17 | | 37 | 3 | | 38 | 2 | | 39 | 16 | | 40 | 19 | | 41 | 9 | | 42 | 17 | | 43 | 7 | | 44 | 15 | | 45 | 15 | | 46 | 5 | | 47 | 20 | | 48 | 12 | | 49 | 17 |
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| 95.06% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.5925925925925926 | | totalSentences | 81 | | uniqueOpeners | 48 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 63 | | matches | | 0 | "Bright blue eyes, the only" | | 1 | "Finally, Silas exhaled heavily, his" | | 2 | "Maybe there was hope for" |
| | ratio | 0.048 | |
| 99.37% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 63 | | matches | | 0 | "She shrugged off her coat" | | 1 | "It'd been a long day" | | 2 | "she called out to the" | | 3 | "He'd traded the sharp suits" | | 4 | "His eyes darted around the" | | 5 | "They settled into a private" | | 6 | "She had a million questions," | | 7 | "She wiped it away with" | | 8 | "His eyes traced the curves" | | 9 | "He knew it all -" | | 10 | "He also knew the moment" | | 11 | "He asked quietly, brushing a" | | 12 | "She took a shaky breath," | | 13 | "His thumb stroked her knuckles," | | 14 | "They lapsed into a comfortable" | | 15 | "He'd learned long ago to" | | 16 | "He slid from the booth," | | 17 | "Her eyes found his in" | | 18 | "It wasn't until Rory downed" |
| | ratio | 0.302 | |
| 47.30% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 63 | | matches | | 0 | "Aurora Carter stumbled into The" | | 1 | "She shrugged off her coat" | | 2 | "It'd been a long day" | | 3 | "she called out to the" | | 4 | "Wisps of raven hair escaped" | | 5 | "A beat up cap from" | | 6 | "A glass clinked on the" | | 7 | "Roryυννωσα she sighed, downing the" | | 8 | "The peaty taste lingered as" | | 9 | "a deep voice chuckled from" | | 10 | "Rory spun around to see" | | 11 | "A grin spread across his" | | 12 | "He'd traded the sharp suits" | | 13 | "Rory hugged the retired spymaster" | | 14 | "His eyes darted around the" | | 15 | "Rory glanced at her half-empty" | | 16 | "The warmth of the whisky" | | 17 | "They settled into a private" | | 18 | "Rory's bright blue eyes sparkled" | | 19 | "She had a million questions," |
| | ratio | 0.825 | |
| 79.37% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 63 | | matches | | 0 | "Though years had passed since" |
| | ratio | 0.016 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 1 | | matches | | 0 | "Pausing at the entrance to The Raven's Nest, Silas glanced back one last time, his heart swelling with that unnameable emotion, watching Rory fade into the dark…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 6 | | matches | | 0 | "Rory whispered, her blues eyes shimmering with unshed tears" | | 1 | "Rory admitted, her lower lip trembling ever so slightly" | | 2 | "Silas reached, his rough hands engulfing hers" | | 3 | "Rory began, a quiet desperation creeping into her voice" | | 4 | "Silas soothed, his fingers tightening around hers" | | 5 | "Rory asked, vulnerability shining through her bravado" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 8 | | fancyTags | | 0 | "Roryυννωσα she sighed (sigh)" | | 1 | "a deep voice chuckled (chuckle)" | | 2 | "Rory whispered (whisper)" | | 3 | "Silas sighed (sigh)" | | 4 | "Rory admitted (admit)" | | 5 | "Silas vowed (vow)" | | 6 | "Silas agreed (agree)" | | 7 | "Silas swore (swear)" |
| | dialogueSentences | 36 | | tagDensity | 0.278 | | leniency | 0.556 | | rawRatio | 0.8 | | effectiveRatio | 0.444 | |