| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said finally [finally]" |
| | dialogueSentences | 5 | | tagDensity | 0.8 | | leniency | 1 | | rawRatio | 0.25 | | effectiveRatio | 0.25 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 232 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 232 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "traced" | | 1 | "familiar" | | 2 | "calculated" | | 3 | "weight" | | 4 | "unspoken" |
| |
| 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 | 27 | | matches | (empty) | |
| 89.95% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 27 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 28 | | 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 | 0 | | markdownWords | 0 | | totalWords | 231 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 7.82% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 13 | | wordCount | 211 | | uniqueNames | 5 | | maxNameDensity | 2.84 | | worstName | "Eva" | | maxWindowNameDensity | 3 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Eva | 6 | | Silas | 1 | | Aurora | 4 |
| | persons | | 0 | "Raven" | | 1 | "Eva" | | 2 | "Silas" | | 3 | "Aurora" |
| | places | (empty) | | globalScore | 0.078 | | windowScore | 0.667 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 15 | | glossingSentenceCount | 1 | | matches | | 0 | "knot that seemed to pull her face taut with something harder than professionalism" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 231 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 28 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 11 | | mean | 21 | | std | 15.81 | | cv | 0.753 | | sampleLengths | | 0 | 49 | | 1 | 18 | | 2 | 53 | | 3 | 8 | | 4 | 8 | | 5 | 33 | | 6 | 10 | | 7 | 11 | | 8 | 16 | | 9 | 18 | | 10 | 7 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 27 | | matches | (empty) | |
| 14.81% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 36 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 212 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.03773584905660377 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.009433962264150943 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 28 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 28 | | mean | 8.25 | | std | 7.07 | | cv | 0.857 | | sampleLengths | | 0 | 19 | | 1 | 15 | | 2 | 15 | | 3 | 8 | | 4 | 9 | | 5 | 1 | | 6 | 6 | | 7 | 13 | | 8 | 34 | | 9 | 3 | | 10 | 2 | | 11 | 3 | | 12 | 4 | | 13 | 4 | | 14 | 8 | | 15 | 15 | | 16 | 10 | | 17 | 6 | | 18 | 4 | | 19 | 7 | | 20 | 2 | | 21 | 1 | | 22 | 1 | | 23 | 16 | | 24 | 7 | | 25 | 2 | | 26 | 9 | | 27 | 7 |
| |
| 100.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.75 | | totalSentences | 28 | | uniqueOpeners | 21 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 19 | | matches | | | ratio | 0.053 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 4 | | totalSentences | 19 | | matches | | 0 | "Her old friend stood differently" | | 1 | "She nodded at Silas, who" | | 2 | "It wasn't a question." | | 3 | "she said finally" |
| | ratio | 0.211 | |
| 65.26% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 15 | | totalSentences | 19 | | matches | | 0 | "The night pressed against the" | | 1 | "Aurora traced the rim of" | | 2 | "The bar hummed with low" | | 3 | "Her old friend stood differently" | | 4 | "This Eva moved with calculated" | | 5 | "Aurora lifted her glass." | | 6 | "Eva slid onto the barstool," | | 7 | "She nodded at Silas, who" | | 8 | "A silent communication passed between" | | 9 | "It wasn't a question." | | 10 | "The weight of years hung" | | 11 | "Aurora responded, her voice light" | | 12 | "Eva's fingers drummed once against" | | 13 | "A gesture that said more" | | 14 | "she said finally" |
| | ratio | 0.789 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 19 | | matches | (empty) | | ratio | 0 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 7 | | technicalSentenceCount | 1 | | matches | | 0 | "This Eva moved with calculated precision, her tailored grey blazer speaking of corporate ambition, her hair pulled back in a tight knot that seemed to pull her …" |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 25.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | 0 | "Aurora responded (respond)" |
| | dialogueSentences | 5 | | tagDensity | 0.8 | | leniency | 1 | | rawRatio | 0.25 | | effectiveRatio | 0.25 | |