| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.97% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1658 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 78.89% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1658 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "weight" | | 1 | "scanned" | | 2 | "glint" | | 3 | "etched" | | 4 | "tension" | | 5 | "pulse" | | 6 | "echoed" |
| |
| 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 | 272 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 272 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 272 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 20 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1658 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 53 | | unquotedAttributions | 44 | | matches | | 0 | "The victim looks peaceful, Eva said." | | 1 | "There are no exit wounds, Eva said." | | 2 | "The Veil Compass, Quinn said." | | 3 | "It reacts to rifts, Eva said." | | 4 | "Look at the dust, Quinn said." | | 5 | "No footprints lead to him, Quinn said." | | 6 | "A bone token, Quinn said." | | 7 | "The rift is closed, Quinn said." | | 8 | "It closed after he arrived, Eva said." | | 9 | "Ritual binding, Eva said." | | 10 | "The market rules, Eva said." | | 11 | "He paid, Quinn said." | | 12 | "He was marked, Quinn said." | | 13 | "By the seller, Quinn said." | | 14 | "The compass reacts to the energy, Eva said." | | 15 | "You said the market moves, Quinn said." | | 16 | "Every full moon, Eva said." | | 17 | "The market is here, Eva said." | | 18 | "The token opens the door, Quinn said." | | 19 | "It was used recently, Eva said." | | 20 | "Only one set, Quinn said." | | 21 | "The killer walked back, Eva said." | | 22 | "No, Quinn said." | | 23 | "The rift took him, Quinn said." | | 24 | "It points to you, Eva said." | | 25 | "The energy is here, Quinn said." | | 26 | "We need to call for backup, Eva said." | | 27 | "No, Quinn said." | | 28 | "Put the compass down, Quinn said." | | 29 | "The token, Quinn said." | | 30 | "The market demands a trade, Quinn said." | | 31 | "It accepted the trade, Eva said." | | 32 | "It accepted the price, Quinn said." | | 33 | "The body was preserved, Quinn said." | | 34 | "By the magic, Eva said." | | 35 | "By the lie, Quinn said." | | 36 | "The killer used the market to hide the body, Quinn said." | | 37 | "And the token, Eva said." | | 38 | "The token opened the door, Quinn said." | | 39 | "We need to find the seller, Quinn said." | | 40 | "The seller is in the market, Eva said." | | 41 | "The market is here, Quinn said." | | 42 | "We stay, Quinn said." | | 43 | "Until the moon rises, Quinn said." |
| |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 103 | | wordCount | 1656 | | uniqueNames | 8 | | maxNameDensity | 3.32 | | worstName | "Quinn" | | maxWindowNameDensity | 5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Harlow | 1 | | Quinn | 55 | | Kowalski | 1 | | Eva | 42 | | Veil | 1 | | Compass | 1 | | Ritual | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" | | 4 | "Ritual" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 136 | | 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 | 1658 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 272 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 95 | | mean | 17.45 | | std | 12.42 | | cv | 0.712 | | sampleLengths | | 0 | 65 | | 1 | 63 | | 2 | 37 | | 3 | 6 | | 4 | 39 | | 5 | 20 | | 6 | 29 | | 7 | 6 | | 8 | 45 | | 9 | 21 | | 10 | 14 | | 11 | 53 | | 12 | 6 | | 13 | 7 | | 14 | 28 | | 15 | 26 | | 16 | 47 | | 17 | 25 | | 18 | 29 | | 19 | 19 | | 20 | 6 | | 21 | 14 | | 22 | 27 | | 23 | 13 | | 24 | 28 | | 25 | 23 | | 26 | 10 | | 27 | 30 | | 28 | 23 | | 29 | 19 | | 30 | 21 | | 31 | 7 | | 32 | 33 | | 33 | 8 | | 34 | 16 | | 35 | 16 | | 36 | 32 | | 37 | 5 | | 38 | 5 | | 39 | 26 | | 40 | 23 | | 41 | 14 | | 42 | 15 | | 43 | 16 | | 44 | 7 | | 45 | 5 | | 46 | 23 | | 47 | 9 | | 48 | 13 | | 49 | 11 |
| |
| 96.23% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 272 | | matches | | 0 | "was brought" | | 1 | "was carved" | | 2 | "was meant" | | 3 | "was brought" | | 4 | "was used" | | 5 | "was preserved" | | 6 | "were gone" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 350 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 272 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 695 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.02158273381294964 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0057553956834532375 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 272 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 272 | | mean | 6.1 | | std | 2.94 | | cv | 0.483 | | sampleLengths | | 0 | 13 | | 1 | 15 | | 2 | 17 | | 3 | 20 | | 4 | 9 | | 5 | 12 | | 6 | 5 | | 7 | 7 | | 8 | 15 | | 9 | 8 | | 10 | 7 | | 11 | 13 | | 12 | 9 | | 13 | 15 | | 14 | 6 | | 15 | 6 | | 16 | 11 | | 17 | 5 | | 18 | 9 | | 19 | 2 | | 20 | 6 | | 21 | 7 | | 22 | 5 | | 23 | 4 | | 24 | 4 | | 25 | 3 | | 26 | 13 | | 27 | 8 | | 28 | 5 | | 29 | 6 | | 30 | 4 | | 31 | 11 | | 32 | 8 | | 33 | 9 | | 34 | 13 | | 35 | 5 | | 36 | 10 | | 37 | 6 | | 38 | 6 | | 39 | 4 | | 40 | 4 | | 41 | 3 | | 42 | 15 | | 43 | 12 | | 44 | 8 | | 45 | 15 | | 46 | 6 | | 47 | 4 | | 48 | 3 | | 49 | 7 |
| |
| 33.82% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 44 | | diversityRatio | 0.13602941176470587 | | totalSentences | 272 | | uniqueOpeners | 37 | |
| 52.08% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 256 | | matches | | 0 | "Maybe he was brought in." | | 1 | "Then why move him?" | | 2 | "Then why is he dead?" | | 3 | "Only one set, Quinn said." |
| | ratio | 0.016 | |
| 52.81% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 107 | | totalSentences | 256 | | matches | | 0 | "She stepped over a rusted" | | 1 | "She checked her watch, the" | | 2 | "She stopped three feet from" | | 3 | "She held a small notebook," | | 4 | "She tucked a curl of" | | 5 | "She knelt, keeping her weight" | | 6 | "She scanned the victim’s face." | | 7 | "She pointed to the chest." | | 8 | "She smelled ozone and something" | | 9 | "She reached out and touched" | | 10 | "It wasn't, Eva agreed." | | 11 | "She opened her satchel and" | | 12 | "It pointed instead toward the" | | 13 | "She knew the object from" | | 14 | "It reacts to rifts, Eva" | | 15 | "She walked the perimeter of" | | 16 | "She stopped at the edge" | | 17 | "She crouched again and brushed" | | 18 | "She ran her finger through" | | 19 | "He didn't walk here." |
| | ratio | 0.418 | |
| 22.50% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 224 | | totalSentences | 256 | | matches | | 0 | "The damp air of the" | | 1 | "She stepped over a rusted" | | 2 | "The fluorescent lights overhead buzzed" | | 3 | "Quinn pushed past them, her" | | 4 | "She checked her watch, the" | | 5 | "The time matched the call." | | 6 | "She stopped three feet from" | | 7 | "A man in a dark" | | 8 | "Eva Kowalski crouched beside the" | | 9 | "She held a small notebook," | | 10 | "She tucked a curl of" | | 11 | "The victim looks peaceful, Eva" | | 12 | "She knelt, keeping her weight" | | 13 | "She scanned the victim’s face." | | 14 | "The skin held a grey" | | 15 | "She pointed to the chest." | | 16 | "The fabric is intact." | | 17 | "Quinn leaned closer." | | 18 | "She smelled ozone and something" | | 19 | "She reached out and touched" |
| | ratio | 0.875 | |
| 39.06% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 256 | | matches | | 0 | "If he paid, he should" | | 1 | "If he didn't pay, he" |
| | ratio | 0.008 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |