| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.414 | | leniency | 0.828 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.52% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1115 | | totalAiIsmAdverbs | 1 | | 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) | |
| 23.77% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1115 | | totalAiIsms | 17 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | word | "casual indifference" | | count | 1 |
| | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | |
| | highlights | | 0 | "scanning" | | 1 | "scanned" | | 2 | "pulsed" | | 3 | "flicked" | | 4 | "calculated" | | 5 | "complex" | | 6 | "casual indifference" | | 7 | "weight" | | 8 | "eyebrow" | | 9 | "etched" | | 10 | "clandestine" | | 11 | "flicker" | | 12 | "unreadable" | | 13 | "could feel" |
| |
| 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 | 100 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 100 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 117 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1109 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 912 | | uniqueNames | 12 | | maxNameDensity | 1.54 | | worstName | "Silas" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Silas" | | discoveredNames | | Mercer | 7 | | Met | 1 | | Leicester | 1 | | Square | 1 | | Glock | 1 | | Raven | 3 | | Nest | 3 | | Soho | 1 | | Silas | 14 | | Harlow | 11 | | Rumors | 1 | | Morris | 2 |
| | persons | | 0 | "Mercer" | | 1 | "Square" | | 2 | "Glock" | | 3 | "Raven" | | 4 | "Silas" | | 5 | "Harlow" | | 6 | "Morris" |
| | places | | | globalScore | 0.732 | | windowScore | 0.5 | |
| 70.63% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 2 | | matches | | 0 | "tasted like grit and exhaust" | | 1 | "as if reading her mind" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1109 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 117 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 28.44 | | std | 16.92 | | cv | 0.595 | | sampleLengths | | 0 | 71 | | 1 | 47 | | 2 | 47 | | 3 | 29 | | 4 | 33 | | 5 | 4 | | 6 | 28 | | 7 | 66 | | 8 | 11 | | 9 | 15 | | 10 | 2 | | 11 | 38 | | 12 | 35 | | 13 | 9 | | 14 | 24 | | 15 | 35 | | 16 | 20 | | 17 | 17 | | 18 | 15 | | 19 | 2 | | 20 | 21 | | 21 | 5 | | 22 | 28 | | 23 | 52 | | 24 | 43 | | 25 | 32 | | 26 | 35 | | 27 | 5 | | 28 | 24 | | 29 | 26 | | 30 | 47 | | 31 | 12 | | 32 | 28 | | 33 | 39 | | 34 | 13 | | 35 | 25 | | 36 | 34 | | 37 | 37 | | 38 | 55 |
| |
| 98.25% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 100 | | matches | | 0 | "was gone" | | 1 | "being concealed" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 146 | | matches | | 0 | "was chasing" | | 1 | "was walking" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 117 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 918 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, tarnished silver coin" |
| | adverbCount | 19 | | adverbRatio | 0.020697167755991286 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.007625272331154684 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 117 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 117 | | mean | 9.48 | | std | 6.47 | | cv | 0.682 | | sampleLengths | | 0 | 7 | | 1 | 15 | | 2 | 2 | | 3 | 24 | | 4 | 2 | | 5 | 21 | | 6 | 7 | | 7 | 21 | | 8 | 12 | | 9 | 3 | | 10 | 3 | | 11 | 1 | | 12 | 7 | | 13 | 17 | | 14 | 22 | | 15 | 1 | | 16 | 14 | | 17 | 12 | | 18 | 3 | | 19 | 11 | | 20 | 11 | | 21 | 10 | | 22 | 1 | | 23 | 4 | | 24 | 14 | | 25 | 14 | | 26 | 27 | | 27 | 19 | | 28 | 20 | | 29 | 6 | | 30 | 5 | | 31 | 8 | | 32 | 7 | | 33 | 2 | | 34 | 13 | | 35 | 22 | | 36 | 3 | | 37 | 3 | | 38 | 7 | | 39 | 7 | | 40 | 6 | | 41 | 1 | | 42 | 11 | | 43 | 9 | | 44 | 10 | | 45 | 14 | | 46 | 13 | | 47 | 1 | | 48 | 5 | | 49 | 4 |
| |
| 64.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.4188034188034188 | | totalSentences | 117 | | uniqueOpeners | 49 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 85.12% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 86 | | matches | | 0 | "He’d gained three blocks on" | | 1 | "Her shoes slapped against the" | | 2 | "It suggested something…" | | 3 | "She risked a glance over" | | 4 | "He ducked into a narrow" | | 5 | "she muttered, her breath misting" | | 6 | "She scanned the surrounding buildings," | | 7 | "He was a fixture in" | | 8 | "He gestured with a subtle" | | 9 | "She knew that look on" | | 10 | "She’d dealt with his kind" | | 11 | "They thrived in the shadows," | | 12 | "she asked, keeping her voice" | | 13 | "She’d dismissed it, filed it" | | 14 | "She pictured the disappearance reports." | | 15 | "she said, her gaze fixed" | | 16 | "She considered her options." | | 17 | "Her watch, a worn leather" | | 18 | "She thought of the families" | | 19 | "She thought of Morris, and" |
| | ratio | 0.337 | |
| 35.58% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 86 | | matches | | 0 | "The rain tasted like grit" | | 1 | "Harlow shoved a stray strand" | | 2 | "He’d gained three blocks on" | | 3 | "Her shoes slapped against the" | | 4 | "The neon glow of Leicester" | | 5 | "Mercer moved with purpose, not" | | 6 | "That bothered her." | | 7 | "It suggested something…" | | 8 | "She risked a glance over" | | 9 | "A scattering of late-night revelers," | | 10 | "He ducked into a narrow" | | 11 | "Harlow followed without hesitation, the" | | 12 | "Mercer was gone." | | 13 | "she muttered, her breath misting" | | 14 | "She scanned the surrounding buildings," | | 15 | "A fire escape, a rooftop" | | 16 | "The voice was low, smooth," | | 17 | "Harlow spun around, her hand" | | 18 | "Silas stood in the alley’s" | | 19 | "The distinctive green neon sign" |
| | ratio | 0.849 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 2 | | matches | | 0 | "He’d gained three blocks on her in the last five minutes, weaving through the late-night crowds with a disconcerting grace that defied his build." | | 1 | "The voice was low, smooth, laced with a cynical amusement that tightened her jaw." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 7 | | matches | | 0 | "she muttered, her breath misting in the cold air" | | 1 | "Harlow said, her voice clipped" | | 2 | "Silas said, the word dripping with casual indifference" | | 3 | "Silas said, his voice devoid of inflection" | | 4 | "Silas added, as if reading her mind" | | 5 | "Silas replied, his smile widening slightly" | | 6 | "she said, her voice hardening" |
| |
| 46.55% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 3 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "Harlow breathed (breathe)" | | 2 | "Silas added (add)" |
| | dialogueSentences | 29 | | tagDensity | 0.345 | | leniency | 0.69 | | rawRatio | 0.3 | | effectiveRatio | 0.207 | |