| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 42 | | adverbTagCount | 4 | | adverbTags | | 0 | "Julian gestured vaguely [vaguely]" | | 1 | "He looks like [like]" | | 2 | "It feels like [like]" | | 3 | "you look like [like]" |
| | dialogueSentences | 54 | | tagDensity | 0.778 | | leniency | 1 | | rawRatio | 0.095 | | effectiveRatio | 0.095 | |
| 97.36% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1892 | | totalAiIsmAdverbs | 1 | | 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) | |
| 44.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1892 | | totalAiIsms | 21 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | word | "carried the weight" | | count | 1 |
| | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | |
| | highlights | | 0 | "tracing" | | 1 | "rhythmic" | | 2 | "flicked" | | 3 | "scanned" | | 4 | "carried the weight" | | 5 | "intensity" | | 6 | "sanctuary" | | 7 | "weight" | | 8 | "whisper" | | 9 | "unwavering" | | 10 | "profound" | | 11 | "resolve" | | 12 | "silence" | | 13 | "encounter" | | 14 | "stomach" | | 15 | "reminder" | | 16 | "flickered" |
| |
| 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 | 1 | | narrationSentences | 116 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 116 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 122 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 67 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1890 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 30 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 88 | | wordCount | 1513 | | uniqueNames | 19 | | maxNameDensity | 1.39 | | worstName | "Aurora" | | maxWindowNameDensity | 3 | | worstWindowName | "Aurora" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Soho | 4 | | London | 1 | | Carter | 2 | | Silas | 17 | | Blackwood | 1 | | Cardiff | 3 | | Aurora | 21 | | Wales | 1 | | Julian | 13 | | Golden | 1 | | Empress | 1 | | Rory | 2 | | Highland | 1 | | You | 13 | | Bar | 1 | | Penarth | 1 | | Dust | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Silas" | | 4 | "Blackwood" | | 5 | "Aurora" | | 6 | "Julian" | | 7 | "Rory" | | 8 | "You" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Cardiff" | | 3 | "Wales" | | 4 | "Highland" | | 5 | "Penarth" |
| | globalScore | 0.806 | | windowScore | 0.667 | |
| 59.64% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like the Cardiff courtrooms Aurora" | | 1 | "felt like the only permanent thing she" | | 2 | "looked like he wanted to say something pr" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1890 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 122 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 37.8 | | std | 21.12 | | cv | 0.559 | | sampleLengths | | 0 | 58 | | 1 | 103 | | 2 | 8 | | 3 | 52 | | 4 | 65 | | 5 | 1 | | 6 | 63 | | 7 | 50 | | 8 | 37 | | 9 | 18 | | 10 | 1 | | 11 | 42 | | 12 | 16 | | 13 | 19 | | 14 | 46 | | 15 | 24 | | 16 | 38 | | 17 | 49 | | 18 | 55 | | 19 | 48 | | 20 | 73 | | 21 | 66 | | 22 | 37 | | 23 | 39 | | 24 | 65 | | 25 | 50 | | 26 | 25 | | 27 | 24 | | 28 | 23 | | 29 | 66 | | 30 | 50 | | 31 | 18 | | 32 | 21 | | 33 | 40 | | 34 | 26 | | 35 | 7 | | 36 | 42 | | 37 | 25 | | 38 | 21 | | 39 | 5 | | 40 | 35 | | 41 | 27 | | 42 | 26 | | 43 | 18 | | 44 | 42 | | 45 | 67 | | 46 | 17 | | 47 | 34 | | 48 | 59 | | 49 | 49 |
| |
| 84.09% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 116 | | matches | | 0 | "being asked" | | 1 | "was devastated" | | 2 | "were meant" | | 3 | "were supposed" | | 4 | "were outdated" | | 5 | "been redrawn" | | 6 | "was punctuated" | | 7 | "was choked" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 263 | | matches | | 0 | "were being" | | 1 | "were traveling" | | 2 | "was still turning" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 122 | | ratio | 0.008 | | matches | | 0 | "He looked like the Cardiff courtrooms Aurora had fled—polished, rigid, and entirely out of place in a Soho basement." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 995 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 37 | | adverbRatio | 0.0371859296482412 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.016080402010050253 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 122 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 122 | | mean | 15.49 | | std | 12.7 | | cv | 0.82 | | sampleLengths | | 0 | 27 | | 1 | 4 | | 2 | 27 | | 3 | 22 | | 4 | 13 | | 5 | 13 | | 6 | 18 | | 7 | 16 | | 8 | 21 | | 9 | 8 | | 10 | 13 | | 11 | 3 | | 12 | 11 | | 13 | 11 | | 14 | 5 | | 15 | 9 | | 16 | 13 | | 17 | 11 | | 18 | 19 | | 19 | 22 | | 20 | 1 | | 21 | 8 | | 22 | 28 | | 23 | 4 | | 24 | 23 | | 25 | 10 | | 26 | 16 | | 27 | 24 | | 28 | 4 | | 29 | 13 | | 30 | 20 | | 31 | 5 | | 32 | 13 | | 33 | 1 | | 34 | 21 | | 35 | 21 | | 36 | 16 | | 37 | 13 | | 38 | 6 | | 39 | 10 | | 40 | 10 | | 41 | 6 | | 42 | 4 | | 43 | 2 | | 44 | 7 | | 45 | 7 | | 46 | 17 | | 47 | 7 | | 48 | 38 | | 49 | 27 |
| |
| 36.07% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.29508196721311475 | | totalSentences | 122 | | uniqueOpeners | 36 | |
| 31.75% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 105 | | matches | | 0 | "Instead, I find you in" |
| | ratio | 0.01 | |
| 44.76% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 46 | | totalSentences | 105 | | matches | | 0 | "She watched Silas Blackwood through" | | 1 | "He dragged his left leg" | | 2 | "She felt the shift in" | | 3 | "He didn't greet the newcomer." | | 4 | "He simply waited, the rag" | | 5 | "He wore a charcoal wool" | | 6 | "He looked like the Cardiff" | | 7 | "He scanned the room, his" | | 8 | "It was a ghost of" | | 9 | "She didn't look up." | | 10 | "She looked at the small" | | 11 | "His voice was a gravelly" | | 12 | "He didn't move from behind" | | 13 | "He took three steps toward" | | 14 | "Her bright blue eyes were" | | 15 | "I didn't want to believe" | | 16 | "You were the top of" | | 17 | "You had the Carter name" | | 18 | "He looks like he’s seen" | | 19 | "He was devastated when you" |
| | ratio | 0.438 | |
| 2.86% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 96 | | totalSentences | 105 | | matches | | 0 | "The green neon sign outside" | | 1 | "Shadows pooled in the corners" | | 2 | "Aurora Carter sat at the" | | 3 | "The straight, shoulder-length black hair" | | 4 | "She watched Silas Blackwood through" | | 5 | "Silas moved with a practiced," | | 6 | "He dragged his left leg" | | 7 | "The silver signet ring on" | | 8 | "The door chime gave a" | | 9 | "Aurora didn't turn." | | 10 | "She felt the shift in" | | 11 | "Silas’s hazel eyes flicked toward" | | 12 | "He didn't greet the newcomer." | | 13 | "He simply waited, the rag" | | 14 | "A man stepped into the" | | 15 | "He wore a charcoal wool" | | 16 | "He looked like the Cardiff" | | 17 | "He scanned the room, his" | | 18 | "The name hit Aurora like" | | 19 | "It was a ghost of" |
| | ratio | 0.914 | |
| 95.24% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 105 | | matches | | 0 | "To leave like that, in" | | 1 | "If I look like I’ve" |
| | ratio | 0.019 | |
| 3.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 7 | | matches | | 0 | "The green neon sign outside The Raven’s Nest hummed, a low-frequency vibration that rattled the windowpanes and bled a sickly emerald hue onto the rain-slicked …" | | 1 | "Shadows pooled in the corners of the bar, trapped between the framed maps of 19th-century London and the yellowed photographs of men who had long since vanished…" | | 2 | "The silver signet ring on his right hand clinked against the glass, a steady, metallic ticking that marked the passing minutes." | | 3 | "She looked at the small crescent-shaped scar on her left wrist, a childhood mark that felt like the only permanent thing she owned." | | 4 | "He didn't move from behind the tap, but his posture flattened, the quiet authority of a man who knew exactly where the exits were." | | 5 | "Julian set the glass down. The whiskey was half-finished. He looked around the room again, his eyes lingering on the bookshelf that hid Silas’s secret room. He …" | | 6 | "Aurora picked up a pair of chopsticks. Her hand was steady. She looked at the green light on the floor and the way the shadows danced as cars passed by outside.…" |
| |
| 95.59% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 34 | | uselessAdditionCount | 2 | | matches | | 0 | "Julian said, his voice dropping to a whisper" | | 1 | "she said, her voice barely audible over the hum of the neon" |
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| 94.44% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 18 | | fancyCount | 3 | | fancyTags | | 0 | "Aurora snapped (snap)" | | 1 | "Julian laughed (laugh)" | | 2 | "she whispered (whisper)" |
| | dialogueSentences | 54 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.167 | | effectiveRatio | 0.111 | |