| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 25 | | tagDensity | 0.52 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 65.45% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1013 | | totalAiIsmAdverbs | 7 | | found | | 0 | | | 1 | | adverb | "barely above a whisper" | | count | 1 |
| | 2 | | | 3 | |
| | highlights | | 0 | "slowly" | | 1 | "barely above a whisper" | | 2 | "very" | | 3 | "carefully" |
| |
| 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) | |
| 35.83% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1013 | | totalAiIsms | 13 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | word | "down her spine" | | count | 1 |
|
| | highlights | | 0 | "weight" | | 1 | "footsteps" | | 2 | "pounding" | | 3 | "racing" | | 4 | "silence" | | 5 | "pulse" | | 6 | "furrowed" | | 7 | "whisper" | | 8 | "chill" | | 9 | "down her spine" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 109 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 109 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 121 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 77 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1008 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 850 | | uniqueNames | 7 | | maxNameDensity | 1.88 | | worstName | "Rory" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 16 | | Samhain | 1 | | Eva | 4 | | Grove | 3 | | Isolde | 2 | | Forest | 1 | | Like | 3 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Isolde" | | 3 | "Like" |
| | places | | | globalScore | 0.559 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like she'd just made the biggest m" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1008 | | matches | (empty) | |
| 56.47% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 4 | | totalSentences | 121 | | matches | | 0 | "screamed that these" | | 1 | "think that she'd" | | 2 | "hope that Isolde" | | 3 | "Hope that she" |
| |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 31.5 | | std | 21.53 | | cv | 0.683 | | sampleLengths | | 0 | 33 | | 1 | 77 | | 2 | 27 | | 3 | 7 | | 4 | 9 | | 5 | 116 | | 6 | 17 | | 7 | 20 | | 8 | 22 | | 9 | 20 | | 10 | 8 | | 11 | 33 | | 12 | 38 | | 13 | 13 | | 14 | 27 | | 15 | 17 | | 16 | 30 | | 17 | 40 | | 18 | 28 | | 19 | 18 | | 20 | 42 | | 21 | 32 | | 22 | 27 | | 23 | 16 | | 24 | 26 | | 25 | 37 | | 26 | 54 | | 27 | 36 | | 28 | 9 | | 29 | 59 | | 30 | 46 | | 31 | 24 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 109 | | matches | | |
| 6.20% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 172 | | matches | | 0 | "was holding" | | 1 | "was following" | | 2 | "Was it...growing" | | 3 | "was coming" | | 4 | "was telling" |
| |
| 95.63% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 121 | | ratio | 0.017 | | matches | | 0 | "She'd left her lost phone back at the moving stones—surely a poor story-turning point, to sacrifice your only lifeline first, and her head screamed that these were entrenamiento, ghosts, her boyfriend silently impossibly coming for her, but her fingers reminded her that the only thing dangerous were the policeman that she knew had stalked her long enough, the acquaintances and the officer of all law she knew would soon smell the blood he had sniffed..." | | 1 | "She was close enough now that Rory could smell her—like wildflowers and something darker, something sharper." |
| |
| 88.17% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 855 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 43 | | adverbRatio | 0.050292397660818715 | | lyAdverbCount | 20 | | lyAdverbRatio | 0.023391812865497075 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 121 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 121 | | mean | 8.33 | | std | 7.72 | | cv | 0.927 | | sampleLengths | | 0 | 11 | | 1 | 6 | | 2 | 2 | | 3 | 4 | | 4 | 5 | | 5 | 5 | | 6 | 10 | | 7 | 16 | | 8 | 7 | | 9 | 9 | | 10 | 16 | | 11 | 2 | | 12 | 11 | | 13 | 6 | | 14 | 9 | | 15 | 3 | | 16 | 10 | | 17 | 5 | | 18 | 5 | | 19 | 2 | | 20 | 1 | | 21 | 4 | | 22 | 2 | | 23 | 2 | | 24 | 10 | | 25 | 14 | | 26 | 75 | | 27 | 3 | | 28 | 4 | | 29 | 2 | | 30 | 8 | | 31 | 5 | | 32 | 1 | | 33 | 7 | | 34 | 4 | | 35 | 6 | | 36 | 7 | | 37 | 7 | | 38 | 1 | | 39 | 9 | | 40 | 8 | | 41 | 4 | | 42 | 10 | | 43 | 10 | | 44 | 2 | | 45 | 3 | | 46 | 3 | | 47 | 6 | | 48 | 8 | | 49 | 10 |
| |
| 61.43% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.4380165289256198 | | totalSentences | 121 | | uniqueOpeners | 53 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 96 | | matches | | 0 | "Only twenty-eight hours until Samhain." | | 1 | "Maybe it was the postponement" | | 2 | "Then a fluttering, like something" | | 3 | "Then a rustling." | | 4 | "Then, slowly, a figure emerged" | | 5 | "Slowly, carefully, she reached out" |
| | ratio | 0.063 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 96 | | matches | | 0 | "She glanced at her watch" | | 1 | "She shifted her weight, stretching" | | 2 | "It was strange that in" | | 3 | "She tucked a strand of" | | 4 | "She'd left her lost phone" | | 5 | "She heard another twig snap." | | 6 | "She was not alone." | | 7 | "She took a step forward," | | 8 | "she said, raising her voice" | | 9 | "She glowed in the moonlight," | | 10 | "she asked, voice barely above" | | 11 | "It was a strange smile," | | 12 | "she repeated, elicited to think" | | 13 | "she said, sing-song" | | 14 | "She was close enough now" | | 15 | "she said, her voice low" | | 16 | "she asked, her voice barely" | | 17 | "She held out a hand," | | 18 | "Her hand inched towards the" | | 19 | "She looked at the woman's" |
| | ratio | 0.271 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 96 | | matches | | 0 | "The stones were cold beneath" | | 1 | "She glanced at her watch" | | 2 | "She shifted her weight, stretching" | | 3 | "It was strange that in" | | 4 | "She tucked a strand of" | | 5 | "The one from the attic" | | 6 | "The scar she still couldn't" | | 7 | "A twig snapped behind her." | | 8 | "Heart pounding, Rory turned slowly," | | 9 | "The moon was nearly full" | | 10 | "She'd left her lost phone" | | 11 | "The night was silent." | | 12 | "She heard another twig snap." | | 13 | "Rory straightened, lifting her chin" | | 14 | "Heart racing, she flung out" | | 15 | "Eyes darted past her, shadowed" | | 16 | "She was not alone." | | 17 | "Rory took a deep breath" | | 18 | "Rory's pulse pounded in her" | | 19 | "She took a step forward," |
| | ratio | 0.688 | |
| 52.08% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 96 | | matches | | 0 | "As if nature itself was" |
| | ratio | 0.01 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 5 | | matches | | 0 | "she asked, voice barely above a whisper" | | 1 | "woman said, her voice lilting and melodic" | | 2 | "she repeated, elicited to think that she'd seen this woman somewhere" | | 3 | "she said, her voice low and intimate" | | 4 | "she asked, her voice barely a whisper" |
| |
| 30.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 3 | | fancyTags | | 0 | "she repeated (repeat)" | | 1 | "she breathed (breathe)" | | 2 | "the woman murmured (murmur)" |
| | dialogueSentences | 25 | | tagDensity | 0.48 | | leniency | 0.96 | | rawRatio | 0.25 | | effectiveRatio | 0.24 | |