| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 1 | | adverbTags | | 0 | "he corrected softly [softly]" |
| | dialogueSentences | 45 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.056 | | effectiveRatio | 0.044 | |
| 89.22% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1392 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "perfectly" | | 1 | "softly" | | 2 | "suddenly" |
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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) | |
| 38.94% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1392 | | totalAiIsms | 17 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | word | "down her spine" | | count | 1 |
| | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | |
| | highlights | | 0 | "silence" | | 1 | "sanctuary" | | 2 | "testament" | | 3 | "pulse" | | 4 | "rhythmic" | | 5 | "echoed" | | 6 | "stark" | | 7 | "down her spine" | | 8 | "charged" | | 9 | "throbbed" | | 10 | "weight" | | 11 | "magnetic" | | 12 | "warmth" | | 13 | "whisper" | | 14 | "tension" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "hung in the air" | | count | 1 |
| | 1 | | label | "sent a shiver through" | | count | 1 |
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| | highlights | | 0 | "hung in the air" | | 1 | "sent a shiver down" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 95 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 95 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 123 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1392 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1020 | | uniqueNames | 6 | | maxNameDensity | 1.18 | | worstName | "Lucien" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Carter | 1 | | Eva | 2 | | Moreau | 1 | | Lucien | 12 | | Aurora | 11 | | Evan | 1 |
| | persons | | 0 | "Carter" | | 1 | "Eva" | | 2 | "Moreau" | | 3 | "Lucien" | | 4 | "Aurora" | | 5 | "Evan" |
| | places | (empty) | | globalScore | 0.912 | | windowScore | 0.833 | |
| 65.25% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like a bone snapping in the silenc" | | 1 | "looked like armor, framing a face that ha" |
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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 | 1392 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 123 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 29 | | std | 23.36 | | cv | 0.805 | | sampleLengths | | 0 | 79 | | 1 | 11 | | 2 | 37 | | 3 | 82 | | 4 | 38 | | 5 | 24 | | 6 | 28 | | 7 | 4 | | 8 | 23 | | 9 | 4 | | 10 | 12 | | 11 | 48 | | 12 | 9 | | 13 | 11 | | 14 | 72 | | 15 | 18 | | 16 | 28 | | 17 | 26 | | 18 | 3 | | 19 | 36 | | 20 | 7 | | 21 | 43 | | 22 | 36 | | 23 | 52 | | 24 | 27 | | 25 | 43 | | 26 | 63 | | 27 | 53 | | 28 | 20 | | 29 | 77 | | 30 | 13 | | 31 | 16 | | 32 | 6 | | 33 | 7 | | 34 | 10 | | 35 | 29 | | 36 | 47 | | 37 | 8 | | 38 | 14 | | 39 | 10 | | 40 | 42 | | 41 | 17 | | 42 | 2 | | 43 | 4 | | 44 | 8 | | 45 | 63 | | 46 | 4 | | 47 | 78 |
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| 97.88% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 95 | | matches | | 0 | "was supposed" | | 1 | "was known" |
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| 96.91% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 194 | | matches | | 0 | "was lying" | | 1 | "was always lying" | | 2 | "was seeing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 123 | | ratio | 0.008 | | matches | | 0 | "One amber, burning like a dying coal; the other black, depthless and void-like." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 357 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 5 | | adverbRatio | 0.014005602240896359 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 123 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 123 | | mean | 11.32 | | std | 7.78 | | cv | 0.687 | | sampleLengths | | 0 | 17 | | 1 | 23 | | 2 | 4 | | 3 | 4 | | 4 | 31 | | 5 | 11 | | 6 | 20 | | 7 | 15 | | 8 | 2 | | 9 | 34 | | 10 | 26 | | 11 | 9 | | 12 | 13 | | 13 | 13 | | 14 | 5 | | 15 | 12 | | 16 | 8 | | 17 | 5 | | 18 | 19 | | 19 | 14 | | 20 | 14 | | 21 | 4 | | 22 | 23 | | 23 | 4 | | 24 | 7 | | 25 | 5 | | 26 | 7 | | 27 | 15 | | 28 | 6 | | 29 | 20 | | 30 | 9 | | 31 | 11 | | 32 | 4 | | 33 | 11 | | 34 | 3 | | 35 | 4 | | 36 | 4 | | 37 | 17 | | 38 | 15 | | 39 | 14 | | 40 | 4 | | 41 | 3 | | 42 | 11 | | 43 | 13 | | 44 | 11 | | 45 | 4 | | 46 | 18 | | 47 | 8 | | 48 | 3 | | 49 | 23 |
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| 36.31% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.3008130081300813 | | totalSentences | 123 | | uniqueOpeners | 37 | |
| 80.32% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 83 | | matches | | 0 | "Instead, she gripped the doorframe," | | 1 | "Then she looked at Lucien." |
| | ratio | 0.024 | |
| 22.41% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 41 | | totalSentences | 83 | | matches | | 0 | "She hadn't ordered anything." | | 1 | "She hadn't expected anyone." | | 2 | "She slid the third bolt" | | 3 | "It smelled of ozone, expensive" | | 4 | "He stood perfectly still, one" | | 5 | "His hair was platinum blond," | | 6 | "She should slam the door." | | 7 | "She should reach for the" | | 8 | "Her voice was steady, a" | | 9 | "he corrected softly" | | 10 | "He stepped forward, not waiting" | | 11 | "she said, though the command" | | 12 | "She stared at him." | | 13 | "He was lying." | | 14 | "He was always lying." | | 15 | "He didn't crouch." | | 16 | "He simply stood there, a" | | 17 | "She turned to face him," | | 18 | "He stopped near the small" | | 19 | "He turned to her then," |
| | ratio | 0.494 | |
| 20.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 83 | | matches | | 0 | "The first click of the" | | 1 | "Aurora Carter paused, her hand" | | 2 | "She hadn't ordered anything." | | 3 | "She hadn't expected anyone." | | 4 | "The flat above the kitchen" | | 5 | "She slid the third bolt" | | 6 | "The air in the corridor" | | 7 | "It smelled of ozone, expensive" | | 8 | "He stood perfectly still, one" | | 9 | "His hair was platinum blond," | | 10 | "Aurora’s heart hammered against her" | | 11 | "She should slam the door." | | 12 | "She should reach for the" | | 13 | "Her voice was steady, a" | | 14 | "Lucien’s lips quirked, a ghost" | | 15 | "he corrected softly" | | 16 | "He stepped forward, not waiting" | | 17 | "The cane clicked against the" | | 18 | "Aurora didn't move to stop" | | 19 | "she said, though the command" |
| | ratio | 0.88 | |
| 60.24% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 83 | | matches | | | ratio | 0.012 | |
| 29.22% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 7 | | matches | | 0 | "Aurora Carter paused, her hand hovering over the second lock, the smell of turmeric and cumin drifting up from the curry house below." | | 1 | "He stood perfectly still, one hand resting on the ivory handle of his cane, the other tucked into the pocket of a charcoal suit that looked tailored to within a…" | | 2 | "The cane clicked against the floorboards, a rhythmic sound that echoed in the cramped hallway." | | 3 | "Ptolemy, Eva's tabby cat, wound himself around Aurora's ankles, purring, before darting toward the intruder." | | 4 | "The crescent-shaped scar there throbbed, a phantom pain from a childhood accident that had nothing to do with demons, but everything to do with how she felt whe…" | | 5 | "It was the same pull that had drawn them together in the first place, the magnetic force of two people orbiting a black hole." | | 6 | "She thought of the way his eyes shifted when he looked at her, like he was seeing something that wasn't there." |
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| 13.89% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 4 | | matches | | 0 | "she said, though the command lacked heat" | | 1 | "Lucien countered, his voice low" | | 2 | "she said, her hand drifting to her left wrist" | | 3 | "she asked, her voice dropping to a whisper" |
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| 83.33% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 3 | | fancyTags | | 0 | "he corrected softly (correct)" | | 1 | "he murmured (murmur)" | | 2 | "he corrected (correct)" |
| | dialogueSentences | 45 | | tagDensity | 0.289 | | leniency | 0.578 | | rawRatio | 0.231 | | effectiveRatio | 0.133 | |