| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 2 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 62.38% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1462 | | totalAiIsmAdverbs | 11 | | found | | | highlights | | 0 | "slowly" | | 1 | "perfectly" | | 2 | "sharply" | | 3 | "suddenly" | | 4 | "slightly" | | 5 | "softly" | | 6 | "loosely" |
| |
| 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) | |
| 14.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1462 | | totalAiIsms | 25 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | |
| | highlights | | 0 | "pulsed" | | 1 | "throb" | | 2 | "echoed" | | 3 | "scanning" | | 4 | "perfect" | | 5 | "quickened" | | 6 | "loomed" | | 7 | "etched" | | 8 | "gloom" | | 9 | "silence" | | 10 | "unsettled" | | 11 | "weight" | | 12 | "fleeting" | | 13 | "quivered" | | 14 | "flickered" | | 15 | "chill" | | 16 | "calculated" | | 17 | "footsteps" | | 18 | "warmth" | | 19 | "gleaming" | | 20 | "stomach" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "sent a shiver through" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "sent a jolt through" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 132 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 132 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 132 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 11 | | totalWords | 1462 | | ratio | 0.008 | | matches | | 0 | "Rory. Rory." | | 1 | "Why did you come?" | | 2 | "What do you carry?" | | 3 | "Stay." |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 81.37% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 1457 | | uniqueNames | 2 | | maxNameDensity | 1.37 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | | persons | | | places | (empty) | | globalScore | 0.814 | | windowScore | 0.833 | |
| 53.85% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 104 | | glossingSentenceCount | 4 | | matches | | 0 | "spirals that seemed to shift when she looked away" | | 1 | "sounded like her own yet twisted, stretche" | | 2 | "sounded like questions" | | 3 | "seemed almost apologetic" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1462 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 132 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 45.69 | | std | 23.75 | | cv | 0.52 | | sampleLengths | | 0 | 56 | | 1 | 57 | | 2 | 62 | | 3 | 68 | | 4 | 58 | | 5 | 8 | | 6 | 65 | | 7 | 68 | | 8 | 61 | | 9 | 64 | | 10 | 56 | | 11 | 59 | | 12 | 64 | | 13 | 70 | | 14 | 69 | | 15 | 4 | | 16 | 4 | | 17 | 64 | | 18 | 54 | | 19 | 52 | | 20 | 49 | | 21 | 58 | | 22 | 8 | | 23 | 56 | | 24 | 6 | | 25 | 56 | | 26 | 1 | | 27 | 50 | | 28 | 54 | | 29 | 46 | | 30 | 8 | | 31 | 7 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 132 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 256 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 132 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1458 | | adjectiveStacks | 1 | | stackExamples | | 0 | "Same straight black hair" |
| | adverbCount | 52 | | adverbRatio | 0.03566529492455418 | | lyAdverbCount | 21 | | lyAdverbRatio | 0.01440329218106996 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 132 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 132 | | mean | 11.08 | | std | 6.04 | | cv | 0.545 | | sampleLengths | | 0 | 16 | | 1 | 23 | | 2 | 17 | | 3 | 15 | | 4 | 22 | | 5 | 12 | | 6 | 8 | | 7 | 12 | | 8 | 2 | | 9 | 9 | | 10 | 2 | | 11 | 12 | | 12 | 25 | | 13 | 4 | | 14 | 16 | | 15 | 13 | | 16 | 17 | | 17 | 18 | | 18 | 13 | | 19 | 6 | | 20 | 5 | | 21 | 5 | | 22 | 9 | | 23 | 20 | | 24 | 8 | | 25 | 2 | | 26 | 12 | | 27 | 9 | | 28 | 20 | | 29 | 22 | | 30 | 16 | | 31 | 19 | | 32 | 13 | | 33 | 20 | | 34 | 6 | | 35 | 10 | | 36 | 6 | | 37 | 1 | | 38 | 12 | | 39 | 9 | | 40 | 17 | | 41 | 6 | | 42 | 2 | | 43 | 1 | | 44 | 17 | | 45 | 6 | | 46 | 5 | | 47 | 27 | | 48 | 7 | | 49 | 4 |
| |
| 45.20% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.30303030303030304 | | totalSentences | 132 | | uniqueOpeners | 40 | |
| 27.55% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 121 | | matches | | 0 | "Only more flowers, their faces" |
| | ratio | 0.008 | |
| 91.07% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 121 | | matches | | 0 | "She planted her feet wider" | | 1 | "She had followed the signal" | | 2 | "She turned slowly, scanning the" | | 3 | "She exhaled through her nose" | | 4 | "She quickened her pace." | | 5 | "She stopped and held her" | | 6 | "She pivoted sharply, bright blue" | | 7 | "she muttered, voice low and" | | 8 | "She gripped the silver chain" | | 9 | "She resumed walking toward the" | | 10 | "Her boots sank deeper into" | | 11 | "She backed up two steps," | | 12 | "She forced her breathing to" | | 13 | "She glanced at the path" | | 14 | "Her words came out flat," | | 15 | "She took that as encouragement" | | 16 | "She yanked her hand back," | | 17 | "She wiped it on her" | | 18 | "They slithered between the stones," | | 19 | "She pressed her scarred wrist" |
| | ratio | 0.322 | |
| 17.85% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 107 | | totalSentences | 121 | | matches | | 0 | "Rory shoved aside another clump" | | 1 | "The heartstone pendant flared hot" | | 2 | "She planted her feet wider" | | 3 | "The gem pulsed faster now," | | 4 | "She had followed the signal" | | 5 | "Answers about the unknown benefactor" | | 6 | "The pendant had never burned" | | 7 | "A soft scrape echoed behind" | | 8 | "She turned slowly, scanning the" | | 9 | "The flowers stood motionless, their" | | 10 | "She exhaled through her nose" | | 11 | "She quickened her pace." | | 12 | "The wildflowers grew denser here," | | 13 | "Each bloom carried a faint" | | 14 | "Rory rubbed the crescent scar" | | 15 | "The stones loomed larger now," | | 16 | "Another sound joined the first," | | 17 | "She stopped and held her" | | 18 | "The rustle stopped with her." | | 19 | "Rory took one deliberate step." |
| | ratio | 0.884 | |
| 41.32% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 121 | | matches | | 0 | "Now they felt like walls." |
| | ratio | 0.008 | |
| 76.19% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 75 | | technicalSentenceCount | 7 | | matches | | 0 | "The heartstone pendant flared hot against her chest, dragging her deeper into the clearing as though the chain had tightened into a leash." | | 1 | "The wildflowers grew denser here, brushing her thighs with cool, damp touches that lingered too long." | | 2 | "Rory rubbed the crescent scar on her wrist without thinking, the old mark prickling as though fresh." | | 3 | "She wiped it on her jeans, leaving a streak that refused to smear." | | 4 | "Their stalks bent with eerie precision, creating a ripple that moved faster than she did." | | 5 | "The pendant stirred against her skin, warmth returning in tentative pulses that seemed almost apologetic." | | 6 | "The flowers between her and the stone parted suddenly, stems folding aside as though invisible hands had swept them clear." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "she muttered, voice low and steady" |
| |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 2 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 1 | | effectiveRatio | 1 | |