| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 42 | | tagDensity | 0.214 | | leniency | 0.429 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.14% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2056 | | 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) | |
| 58.66% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2056 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "flicked" | | 1 | "pulse" | | 2 | "silence" | | 3 | "warmth" | | 4 | "sanctuary" | | 5 | "flickered" | | 6 | "tension" | | 7 | "weight" | | 8 | "footsteps" | | 9 | "traced" |
| |
| 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 | 0 | | narrationSentences | 77 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 77 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2056 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 98.41% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 1163 | | uniqueNames | 8 | | maxNameDensity | 1.03 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Brick | 3 | | Lane | 3 | | Lucien | 12 | | Aurora | 10 | | Golden | 1 | | Empress | 1 | | Eva | 1 | | Ptolemy | 2 |
| | persons | | 0 | "Lucien" | | 1 | "Aurora" | | 2 | "Empress" | | 3 | "Eva" | | 4 | "Ptolemy" |
| | places | | | globalScore | 0.984 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.486 | | wordCount | 2056 | | matches | | 0 | "not for the paper, but to rest two fingers lightly on the edge" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 81.62% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 54.11 | | std | 23.57 | | cv | 0.436 | | sampleLengths | | 0 | 120 | | 1 | 24 | | 2 | 55 | | 3 | 1 | | 4 | 37 | | 5 | 31 | | 6 | 63 | | 7 | 6 | | 8 | 61 | | 9 | 63 | | 10 | 31 | | 11 | 38 | | 12 | 51 | | 13 | 50 | | 14 | 58 | | 15 | 78 | | 16 | 55 | | 17 | 71 | | 18 | 49 | | 19 | 73 | | 20 | 58 | | 21 | 32 | | 22 | 61 | | 23 | 66 | | 24 | 42 | | 25 | 74 | | 26 | 45 | | 27 | 69 | | 28 | 58 | | 29 | 80 | | 30 | 35 | | 31 | 50 | | 32 | 55 | | 33 | 53 | | 34 | 54 | | 35 | 53 | | 36 | 34 | | 37 | 122 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 77 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 177 | | matches | (empty) | |
| 90.91% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 110 | | ratio | 0.018 | | matches | | 0 | "One amber eye and one black eye held none of the usual polite distance; the black caught the shadows first." | | 1 | "A drop landed on a corner of research notes; she wiped it with the hem of her sleeve rather than a cloth." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1165 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 45 | | adverbRatio | 0.03862660944206009 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006008583690987125 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 18.69 | | std | 10.2 | | cv | 0.546 | | sampleLengths | | 0 | 20 | | 1 | 12 | | 2 | 7 | | 3 | 24 | | 4 | 23 | | 5 | 25 | | 6 | 9 | | 7 | 9 | | 8 | 11 | | 9 | 4 | | 10 | 24 | | 11 | 20 | | 12 | 11 | | 13 | 1 | | 14 | 25 | | 15 | 12 | | 16 | 13 | | 17 | 18 | | 18 | 6 | | 19 | 24 | | 20 | 13 | | 21 | 20 | | 22 | 6 | | 23 | 32 | | 24 | 16 | | 25 | 13 | | 26 | 10 | | 27 | 42 | | 28 | 11 | | 29 | 10 | | 30 | 21 | | 31 | 7 | | 32 | 14 | | 33 | 17 | | 34 | 38 | | 35 | 13 | | 36 | 13 | | 37 | 22 | | 38 | 15 | | 39 | 21 | | 40 | 37 | | 41 | 21 | | 42 | 30 | | 43 | 9 | | 44 | 18 | | 45 | 25 | | 46 | 30 | | 47 | 7 | | 48 | 23 | | 49 | 41 |
| |
| 65.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.4090909090909091 | | totalSentences | 110 | | uniqueOpeners | 45 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 77 | | matches | (empty) | | ratio | 0 | |
| 79.74% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 77 | | matches | | 0 | "Her bright blue eyes flicked" | | 1 | "She set the kettle down" | | 2 | "She eased the first deadbolt" | | 3 | "He carried no briefcase, nothing" | | 4 | "She kept one hand on" | | 5 | "His shoulders stayed square, yet" | | 6 | "He followed the path she" | | 7 | "She poured into two mismatched" | | 8 | "She set her mug down" | | 9 | "He placed the cup back" | | 10 | "She rubbed at the wet" | | 11 | "His hand came to rest" | | 12 | "She straightened, cloth balled in" | | 13 | "She let the curtain fall." | | 14 | "He moved from the counter," | | 15 | "She faced him again, the" | | 16 | "His hand lifted, palm open," | | 17 | "She gestured toward the single" | | 18 | "She studied the way his" | | 19 | "He nodded once, slow." |
| | ratio | 0.351 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 77 | | matches | | 0 | "Aurora stopped dead at the" | | 1 | "Her bright blue eyes flicked" | | 2 | "Ptolemy lifted his head from" | | 3 | "She set the kettle down" | | 4 | "The blade-cane caught the low" | | 5 | "She eased the first deadbolt" | | 6 | "The third stuck for a" | | 7 | "The door swung inward." | | 8 | "Lucien stood on the threshold," | | 9 | "He carried no briefcase, nothing" | | 10 | "She kept one hand on" | | 11 | "His shoulders stayed square, yet" | | 12 | "Aurora didn't step back at" | | 13 | "The small flat pressed around" | | 14 | "A kettle hissed faintly behind" | | 15 | "The door shut with a" | | 16 | "He followed the path she" | | 17 | "The charcoal suit absorbed the" | | 18 | "She poured into two mismatched" | | 19 | "The mug she set before" |
| | ratio | 0.922 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 77 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 2 | | matches | | 0 | "The contact sent a small current through the narrow space between their bodies, the same pull that had always cut through their past conversations even when the…" | | 1 | "Attraction flickered beneath the tension, the same thread that had pulled them toward each other during late-night discussions over scrolls and city maps." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |