| 97.44% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 2 | | adverbTags | | 0 | "Julian's eyes flickered around [around]" | | 1 | "He turned back [back]" |
| | dialogueSentences | 39 | | tagDensity | 0.385 | | leniency | 0.769 | | rawRatio | 0.133 | | effectiveRatio | 0.103 | |
| 88.45% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 866 | | totalAiIsmAdverbs | 2 | | 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) | |
| 30.72% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 866 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "tracing" | | 1 | "sanctuary" | | 2 | "scanned" | | 3 | "stomach" | | 4 | "flickered" | | 5 | "familiar" | | 6 | "pang" | | 7 | "flicker" | | 8 | "silence" | | 9 | "could feel" | | 10 | "facade" |
| |
| 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 | 63 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 63 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 87 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 858 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 93.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 614 | | uniqueNames | 11 | | maxNameDensity | 1.14 | | worstName | "Silas" | | maxWindowNameDensity | 2 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Rory | 3 | | Silas | 7 | | Evan | 1 | | Cardiff | 1 | | Jennifer | 1 | | Yu-Fei | 1 | | Golden | 1 | | Empress | 1 |
| | persons | | 0 | "Raven" | | 1 | "Rory" | | 2 | "Silas" | | 3 | "Evan" | | 4 | "Jennifer" |
| | places | | 0 | "Soho" | | 1 | "Cardiff" | | 2 | "Yu-Fei" |
| | globalScore | 0.93 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 50 | | 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 | 858 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 87 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 22.58 | | std | 17.29 | | cv | 0.766 | | sampleLengths | | 0 | 56 | | 1 | 3 | | 2 | 10 | | 3 | 61 | | 4 | 57 | | 5 | 17 | | 6 | 29 | | 7 | 17 | | 8 | 55 | | 9 | 17 | | 10 | 18 | | 11 | 30 | | 12 | 19 | | 13 | 47 | | 14 | 5 | | 15 | 22 | | 16 | 3 | | 17 | 30 | | 18 | 25 | | 19 | 2 | | 20 | 24 | | 21 | 10 | | 22 | 4 | | 23 | 14 | | 24 | 28 | | 25 | 52 | | 26 | 15 | | 27 | 5 | | 28 | 11 | | 29 | 10 | | 30 | 13 | | 31 | 13 | | 32 | 48 | | 33 | 12 | | 34 | 8 | | 35 | 44 | | 36 | 15 | | 37 | 9 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 63 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 95 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 87 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 622 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 20 | | adverbRatio | 0.03215434083601286 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.00964630225080386 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 87 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 87 | | mean | 9.86 | | std | 7.27 | | cv | 0.737 | | sampleLengths | | 0 | 20 | | 1 | 14 | | 2 | 22 | | 3 | 3 | | 4 | 8 | | 5 | 2 | | 6 | 22 | | 7 | 8 | | 8 | 14 | | 9 | 17 | | 10 | 10 | | 11 | 10 | | 12 | 15 | | 13 | 16 | | 14 | 6 | | 15 | 12 | | 16 | 5 | | 17 | 10 | | 18 | 8 | | 19 | 4 | | 20 | 7 | | 21 | 11 | | 22 | 6 | | 23 | 48 | | 24 | 7 | | 25 | 9 | | 26 | 6 | | 27 | 2 | | 28 | 12 | | 29 | 6 | | 30 | 22 | | 31 | 8 | | 32 | 19 | | 33 | 7 | | 34 | 18 | | 35 | 22 | | 36 | 5 | | 37 | 8 | | 38 | 13 | | 39 | 1 | | 40 | 3 | | 41 | 12 | | 42 | 18 | | 43 | 8 | | 44 | 8 | | 45 | 9 | | 46 | 2 | | 47 | 12 | | 48 | 12 | | 49 | 5 |
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| 81.23% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.5287356321839081 | | totalSentences | 87 | | uniqueOpeners | 46 | |
| 54.64% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 61 | | matches | | 0 | "Bright, intelligent, and utterly without" |
| | ratio | 0.016 | |
| 10.16% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 61 | | matches | | 0 | "She lived two flights of" | | 1 | "It had been her sanctuary" | | 2 | "He scanned the dimly lit" | | 3 | "His face was older, the" | | 4 | "he said, his voice cutting" | | 5 | "She hadn't heard that name" | | 6 | "Her own voice was a" | | 7 | "He took the stool next" | | 8 | "She kept her face a" | | 9 | "She took a sip of" | | 10 | "He signalled to Silas" | | 11 | "He turned back to her," | | 12 | "He leaned forward, his voice" | | 13 | "He paused, searching for the" | | 14 | "He accepted his drink from" | | 15 | "She hadn't spoken to Jennifer" | | 16 | "He swirled the gin in" | | 17 | "She set her tumbler down." | | 18 | "It was hard to tell." | | 19 | "He took a long drink" |
| | ratio | 0.525 | |
| 9.18% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 61 | | matches | | 0 | "The cut-glass tumbler hit the" | | 1 | "Silas slid the glass towards" | | 2 | "The Raven's Nest was quiet," | | 3 | "Rory nodded, her fingers tracing" | | 4 | "She lived two flights of" | | 5 | "It had been her sanctuary" | | 6 | "Here, she was just Rory," | | 7 | "Here, Evan was a ghost," | | 8 | "The bell above the door" | | 9 | "A man stepped inside, shaking" | | 10 | "He scanned the dimly lit" | | 11 | "His face was older, the" | | 12 | "he said, his voice cutting" | | 13 | "The ice in her glass" | | 14 | "She hadn't heard that name" | | 15 | "Her own voice was a" | | 16 | "He took the stool next" | | 17 | "The name landed like a" | | 18 | "She kept her face a" | | 19 | "Silas polished a glass behind" |
| | ratio | 0.902 | |
| 81.97% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 61 | | matches | | 0 | "Before he could answer, her" |
| | ratio | 0.016 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 1 | | matches | | 0 | "He scanned the dimly lit room, his gaze passing over her once, then snapping back." |
| |
| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 3 | | matches | | 0 | "he said, his voice cutting through the bar's quiet hum" | | 1 | "She took, the whiskey burning a familiar path down her throat" | | 2 | "He leaned, his voice dropping" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "a stranger's flatter (a stranger flatter)" |
| | dialogueSentences | 39 | | tagDensity | 0.077 | | leniency | 0.154 | | rawRatio | 0.333 | | effectiveRatio | 0.051 | |