| 38.71% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 24 | | adverbTagCount | 5 | | adverbTags | | 0 | "He gestured around [around]" | | 1 | "He looked around [around]" | | 2 | "Thomas nodded slowly [slowly]" | | 3 | "he said eventually [eventually]" | | 4 | "she said quietly [quietly]" |
| | dialogueSentences | 62 | | tagDensity | 0.387 | | leniency | 0.774 | | rawRatio | 0.208 | | effectiveRatio | 0.161 | |
| 86.84% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1140 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | |
| 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) | |
| 69.30% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1140 | | totalAiIsms | 7 | | found | | 0 | | word | "practiced ease" | | count | 1 |
| | 1 | | | 2 | | | 3 | | | 4 | | | 5 | |
| | highlights | | 0 | "practiced ease" | | 1 | "footsteps" | | 2 | "eyebrow" | | 3 | "silence" | | 4 | "flickered" | | 5 | "comfortable" |
| |
| 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 | 0 | | narrationSentences | 92 | | matches | (empty) | |
| 96.27% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 92 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 129 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1138 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 815 | | uniqueNames | 16 | | maxNameDensity | 0.61 | | worstName | "Thomas" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Thomas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Evan | 3 | | Carter | 1 | | Whitmore | 1 | | Cardiff | 1 | | Eva | 1 | | London | 1 | | Silas | 4 | | Thomas | 5 | | Surprise | 1 | | Took | 1 | | Student | 1 | | Union | 1 | | Aurora | 5 | | Soho | 1 |
| | persons | | 0 | "Nest" | | 1 | "Evan" | | 2 | "Carter" | | 3 | "Whitmore" | | 4 | "Eva" | | 5 | "Silas" | | 6 | "Thomas" | | 7 | "Student" | | 8 | "Aurora" |
| | places | | 0 | "Raven" | | 1 | "Cardiff" | | 2 | "London" | | 3 | "Soho" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | 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 | 1138 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 129 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 64 | | mean | 17.78 | | std | 16.21 | | cv | 0.912 | | sampleLengths | | 0 | 45 | | 1 | 5 | | 2 | 15 | | 3 | 56 | | 4 | 7 | | 5 | 5 | | 6 | 31 | | 7 | 40 | | 8 | 3 | | 9 | 4 | | 10 | 1 | | 11 | 12 | | 12 | 10 | | 13 | 37 | | 14 | 2 | | 15 | 20 | | 16 | 24 | | 17 | 59 | | 18 | 10 | | 19 | 4 | | 20 | 15 | | 21 | 9 | | 22 | 14 | | 23 | 15 | | 24 | 1 | | 25 | 32 | | 26 | 5 | | 27 | 59 | | 28 | 5 | | 29 | 4 | | 30 | 19 | | 31 | 6 | | 32 | 27 | | 33 | 7 | | 34 | 39 | | 35 | 12 | | 36 | 5 | | 37 | 11 | | 38 | 20 | | 39 | 12 | | 40 | 4 | | 41 | 48 | | 42 | 2 | | 43 | 7 | | 44 | 5 | | 45 | 17 | | 46 | 21 | | 47 | 29 | | 48 | 10 | | 49 | 59 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 92 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 150 | | matches | | |
| 76.41% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 129 | | ratio | 0.023 | | matches | | 0 | "Nobody called her Carter except—" | | 1 | "Somewhere above them, a pipe creaked—her flat, her tiny kitchen, her makeshift home that she'd built from scratch after arriving with nothing but a bag and a broken spirit." | | 2 | "The suit, the briefcase, the expensive cologne—they all seemed to deflate, leaving just Thomas." |
| |
| 97.52% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 817 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.042839657282741736 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0073439412484700125 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 129 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 129 | | mean | 8.82 | | std | 7.93 | | cv | 0.899 | | sampleLengths | | 0 | 17 | | 1 | 17 | | 2 | 11 | | 3 | 5 | | 4 | 4 | | 5 | 11 | | 6 | 12 | | 7 | 21 | | 8 | 23 | | 9 | 3 | | 10 | 1 | | 11 | 3 | | 12 | 5 | | 13 | 7 | | 14 | 22 | | 15 | 2 | | 16 | 15 | | 17 | 17 | | 18 | 8 | | 19 | 3 | | 20 | 1 | | 21 | 3 | | 22 | 1 | | 23 | 7 | | 24 | 5 | | 25 | 8 | | 26 | 2 | | 27 | 2 | | 28 | 12 | | 29 | 19 | | 30 | 4 | | 31 | 2 | | 32 | 17 | | 33 | 3 | | 34 | 3 | | 35 | 17 | | 36 | 4 | | 37 | 9 | | 38 | 12 | | 39 | 38 | | 40 | 10 | | 41 | 4 | | 42 | 9 | | 43 | 6 | | 44 | 9 | | 45 | 6 | | 46 | 6 | | 47 | 2 | | 48 | 14 | | 49 | 1 |
| |
| 73.13% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.4806201550387597 | | totalSentences | 129 | | uniqueOpeners | 62 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 8 | | totalSentences | 78 | | matches | | 0 | "Instead, she just stared." | | 1 | "Then she'd run to London," | | 2 | "Instead, she poured herself the" | | 3 | "Somewhere above them, a pipe" | | 4 | "Just the boy who'd held" | | 5 | "Then he reached into his" | | 6 | "Just a name, a phone" | | 7 | "Somewhere in Soho, a siren" |
| | ratio | 0.103 | |
| 55.90% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 78 | | matches | | 0 | "She didn't look up." | | 1 | "He leaned against the back" | | 2 | "His hair was slicked back," | | 3 | "He held a leather briefcase" | | 4 | "Her heart stopped." | | 5 | "Her voice came out wrong," | | 6 | "He stepped closer, and she" | | 7 | "He settled onto a bar" | | 8 | "She should move." | | 9 | "He'd driven her to the" | | 10 | "He smiled, but it didn't" | | 11 | "His laugh was genuine that" | | 12 | "He gestured around the bar" | | 13 | "She finally moved, reaching for" | | 14 | "She poured him the good" | | 15 | "He took a long sip" | | 16 | "He looked around, at the" | | 17 | "She didn't answer." | | 18 | "She gestured at Silas, who" | | 19 | "They sat in silence." |
| | ratio | 0.41 | |
| 49.74% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 78 | | matches | | 0 | "The glass slid across the" | | 1 | "Aurora wiped the counter, not" | | 2 | "Tuesday nights at The Raven's" | | 3 | "She didn't look up." | | 4 | "Silas chuckled, the sound roughened" | | 5 | "He leaned against the back" | | 6 | "The maps on the walls" | | 7 | "The door opened." | | 8 | "The lock clicked." | | 9 | "Aurora felt it before she" | | 10 | "That prickle at the back" | | 11 | "The man standing by the" | | 12 | "His hair was slicked back," | | 13 | "He held a leather briefcase" | | 14 | "Her heart stopped." | | 15 | "That wasn't possible." | | 16 | "The name hit her like" | | 17 | "Nobody called her Carter except—" | | 18 | "Her voice came out wrong," | | 19 | "That same laugh, just deeper" |
| | ratio | 0.821 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 78 | | matches | (empty) | | ratio | 0 | |
| 60.44% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 3 | | matches | | 0 | "His hair was slicked back, prematurely grey at the temples in a way that looked intentional, cultivated." | | 1 | "The neon sign buzzed, a insect-like hum that had become white noise years ago." | | 2 | "Just the boy who'd held her hair back when she was sick, who'd cried at her mother's funeral, who'd tried to fight Evan in a car park behind the Student's Union…" |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 24 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 62 | | tagDensity | 0.081 | | leniency | 0.161 | | rawRatio | 0 | | effectiveRatio | 0 | |