| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 51 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 86.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1141 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "really" | | 1 | "slowly" | | 2 | "softly" |
| |
| 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) | |
| 43.03% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1141 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "flickered" | | 1 | "resolve" | | 2 | "silence" | | 3 | "unspoken" | | 4 | "could feel" | | 5 | "weight" | | 6 | "jaw clenched" | | 7 | "flicked" | | 8 | "echoed" | | 9 | "measured" | | 10 | "perfect" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 159 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 159 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 191 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 12 | | totalWords | 1136 | | ratio | 0.011 | | matches | | 0 | "eerily" | | 1 | "no, Evan Rees now" | | 2 | "click" | | 3 | "I’m sorry. I always will be." |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 24 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 66 | | wordCount | 819 | | uniqueNames | 7 | | maxNameDensity | 2.69 | | worstName | "Rory" | | maxWindowNameDensity | 5 | | worstWindowName | "Evan" | | discoveredNames | | Carter | 1 | | Evan | 21 | | Rees | 1 | | Rory | 22 | | Silas | 19 | | Quiet | 1 | | London | 1 |
| | persons | | 0 | "Evan" | | 1 | "Rees" | | 2 | "Rory" | | 3 | "Silas" |
| | places | | | globalScore | 0.157 | | windowScore | 0 | |
| 41.30% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like an old man’s bones" | | 1 | "looked like months of stubble" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1136 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 191 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 77 | | mean | 14.75 | | std | 11.9 | | cv | 0.807 | | sampleLengths | | 0 | 46 | | 1 | 16 | | 2 | 33 | | 3 | 24 | | 4 | 34 | | 5 | 11 | | 6 | 50 | | 7 | 3 | | 8 | 22 | | 9 | 19 | | 10 | 5 | | 11 | 15 | | 12 | 17 | | 13 | 7 | | 14 | 9 | | 15 | 24 | | 16 | 3 | | 17 | 10 | | 18 | 37 | | 19 | 9 | | 20 | 15 | | 21 | 5 | | 22 | 20 | | 23 | 10 | | 24 | 39 | | 25 | 16 | | 26 | 7 | | 27 | 41 | | 28 | 9 | | 29 | 7 | | 30 | 32 | | 31 | 14 | | 32 | 2 | | 33 | 22 | | 34 | 9 | | 35 | 3 | | 36 | 20 | | 37 | 7 | | 38 | 6 | | 39 | 9 | | 40 | 14 | | 41 | 12 | | 42 | 45 | | 43 | 33 | | 44 | 7 | | 45 | 3 | | 46 | 3 | | 47 | 18 | | 48 | 20 | | 49 | 4 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 159 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 158 | | matches | | 0 | "was reading" | | 1 | "were shaking" |
| |
| 68.06% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 191 | | ratio | 0.026 | | matches | | 0 | "Evan Carter—*no, Evan Rees now*—stood there like he’d aged twenty years in the space of three." | | 1 | "The pub hummed in the background—clinking glasses, low murmurs, the clack of pool balls." | | 2 | "For a second, Rory saw the boy she’d once loved—the one who’d held her hand in the rain, who’d whispered promises in the dark." | | 3 | "Evan opened his mouth—maybe to argue, maybe to plead." | | 4 | "Rory knew that look—the cold eyes, the stance of a man who’d seen too much and feared nothing." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 828 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 31 | | adverbRatio | 0.03743961352657005 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.012077294685990338 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 191 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 191 | | mean | 5.95 | | std | 5.17 | | cv | 0.868 | | sampleLengths | | 0 | 15 | | 1 | 31 | | 2 | 3 | | 3 | 7 | | 4 | 6 | | 5 | 3 | | 6 | 15 | | 7 | 15 | | 8 | 8 | | 9 | 5 | | 10 | 3 | | 11 | 3 | | 12 | 5 | | 13 | 11 | | 14 | 12 | | 15 | 1 | | 16 | 1 | | 17 | 9 | | 18 | 11 | | 19 | 16 | | 20 | 18 | | 21 | 3 | | 22 | 7 | | 23 | 6 | | 24 | 3 | | 25 | 2 | | 26 | 14 | | 27 | 6 | | 28 | 2 | | 29 | 2 | | 30 | 2 | | 31 | 3 | | 32 | 10 | | 33 | 5 | | 34 | 5 | | 35 | 7 | | 36 | 3 | | 37 | 8 | | 38 | 5 | | 39 | 2 | | 40 | 2 | | 41 | 7 | | 42 | 3 | | 43 | 6 | | 44 | 8 | | 45 | 11 | | 46 | 5 | | 47 | 3 | | 48 | 6 | | 49 | 4 |
| |
| 52.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.3507853403141361 | | totalSentences | 191 | | uniqueOpeners | 67 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 115 | | matches | | 0 | "Almost a growl." | | 1 | "Then he turned." | | 2 | "Then he deleted it." | | 3 | "Then she threw again." |
| | ratio | 0.035 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 115 | | matches | | 0 | "His voice was rough, like" | | 1 | "He wiped the glass in" | | 2 | "He placed the glass down." | | 3 | "She didn’t need to look" | | 4 | "His once-neat hair was longer," | | 5 | "They locked eyes." | | 6 | "His voice cut through the" | | 7 | "She met Evan’s gaze head-on." | | 8 | "She could feel the weight" | | 9 | "She took a sip." | | 10 | "He leaned back against the" | | 11 | "His hands were big." | | 12 | "Her voice cut through the" | | 13 | "She stepped closer" | | 14 | "He didn’t need to." | | 15 | "He’d already set the boundaries." | | 16 | "He looked at Silas, then" | | 17 | "His final anchor." | | 18 | "His voice had lost its" | | 19 | "It was steel now." |
| | ratio | 0.261 | |
| 60.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 92 | | totalSentences | 115 | | matches | | 0 | "The pub door swung open" | | 1 | "Rory didn’t look up from" | | 2 | "His voice was rough, like" | | 3 | "Silas didn’t turn." | | 4 | "He wiped the glass in" | | 5 | "The neon sign outside flickered" | | 6 | "He placed the glass down." | | 7 | "The man at the bar" | | 8 | "Rory finally noticed the new" | | 9 | "A man who carried silence" | | 10 | "She didn’t need to look" | | 11 | "Evan Carter—*no, Evan Rees now*—stood" | | 12 | "His once-neat hair was longer," | | 13 | "The colour of a winter" | | 14 | "They locked eyes." | | 15 | "The pub hummed in the" | | 16 | "Rory’s fingers tightened around her" | | 17 | "A grimace, really." | | 18 | "Silas slid off his stool." | | 19 | "His voice cut through the" |
| | ratio | 0.8 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 115 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 51 | | tagDensity | 0.255 | | leniency | 0.51 | | rawRatio | 0 | | effectiveRatio | 0 | |