| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 49 | | tagDensity | 0.449 | | leniency | 0.898 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1623 | | 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) | |
| 47.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1623 | | totalAiIsms | 17 | | found | | 0 | | | 1 | | | 2 | | word | "carried the weight" | | count | 1 |
| | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | |
| | highlights | | 0 | "shattered" | | 1 | "footsteps" | | 2 | "carried the weight" | | 3 | "porcelain" | | 4 | "glinting" | | 5 | "flicked" | | 6 | "tension" | | 7 | "unspoken" | | 8 | "silence" | | 9 | "warmth" | | 10 | "throbbed" | | 11 | "pulse" | | 12 | "tracing" | | 13 | "weight" | | 14 | "flickered" | | 15 | "beacon" |
| |
| 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 | 92 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 92 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 118 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 56 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1616 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 72 | | wordCount | 1050 | | uniqueNames | 14 | | maxNameDensity | 2.57 | | worstName | "Aurora" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Aurora" | | discoveredNames | | Golden | 1 | | Empress | 1 | | Raven | 1 | | Nest | 1 | | Cardiff | 4 | | University | 1 | | Aurora | 27 | | Evan | 1 | | Albany | 2 | | Road | 2 | | Eva | 23 | | London | 4 | | Silas | 3 | | Pre-Law | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Evan" | | 2 | "Eva" | | 3 | "Silas" |
| | places | | 0 | "Raven" | | 1 | "Cardiff" | | 2 | "Albany" | | 3 | "Road" | | 4 | "London" |
| | globalScore | 0.214 | | windowScore | 0.167 | |
| 71.88% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like breaking glass" | | 1 | "seemed inevitable" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1616 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 118 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 40.4 | | std | 26.6 | | cv | 0.658 | | sampleLengths | | 0 | 107 | | 1 | 69 | | 2 | 13 | | 3 | 12 | | 4 | 57 | | 5 | 13 | | 6 | 88 | | 7 | 36 | | 8 | 16 | | 9 | 37 | | 10 | 59 | | 11 | 47 | | 12 | 54 | | 13 | 14 | | 14 | 29 | | 15 | 15 | | 16 | 14 | | 17 | 70 | | 18 | 49 | | 19 | 17 | | 20 | 37 | | 21 | 70 | | 22 | 28 | | 23 | 31 | | 24 | 39 | | 25 | 5 | | 26 | 63 | | 27 | 31 | | 28 | 30 | | 29 | 6 | | 30 | 24 | | 31 | 33 | | 32 | 97 | | 33 | 35 | | 34 | 70 | | 35 | 77 | | 36 | 31 | | 37 | 75 | | 38 | 6 | | 39 | 12 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 92 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 169 | | matches | (empty) | |
| 46.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 118 | | ratio | 0.034 | | matches | | 0 | "The darkness pooled around her in the Raven's Nest—dim amber light, the smell of spilled ale and polished mahogany, walls papered with maps that curled at the corners, the ink bleeding into the plaster." | | 1 | "Eva studied her, taking in the delivery stains on Aurora's jacket, the dark circles under her eyes, the way she held herself—coiled, ready to spring." | | 2 | "She looked at her hands—delivery-rough, calloused, strong from carrying bags up four flights of stairs." | | 3 | "The scent of Eva's perfume—jasmine and bergamot, the same bottle from Cardiff—filled her nose, transporting her back to the kitchen on Albany Road, to safety and warmth and the future that had seemed inevitable." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1063 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 10 | | adverbRatio | 0.00940733772342427 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0018814675446848542 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 118 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 118 | | mean | 13.69 | | std | 10.73 | | cv | 0.783 | | sampleLengths | | 0 | 15 | | 1 | 14 | | 2 | 34 | | 3 | 19 | | 4 | 25 | | 5 | 10 | | 6 | 23 | | 7 | 16 | | 8 | 3 | | 9 | 17 | | 10 | 3 | | 11 | 10 | | 12 | 12 | | 13 | 3 | | 14 | 13 | | 15 | 2 | | 16 | 18 | | 17 | 1 | | 18 | 1 | | 19 | 19 | | 20 | 10 | | 21 | 3 | | 22 | 3 | | 23 | 12 | | 24 | 36 | | 25 | 15 | | 26 | 22 | | 27 | 2 | | 28 | 14 | | 29 | 20 | | 30 | 4 | | 31 | 12 | | 32 | 17 | | 33 | 10 | | 34 | 10 | | 35 | 5 | | 36 | 7 | | 37 | 31 | | 38 | 16 | | 39 | 12 | | 40 | 31 | | 41 | 3 | | 42 | 1 | | 43 | 4 | | 44 | 24 | | 45 | 26 | | 46 | 5 | | 47 | 7 | | 48 | 2 | | 49 | 7 |
| |
| 42.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.2796610169491525 | | totalSentences | 118 | | uniqueOpeners | 33 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 81 | | matches | | 0 | "She unloaded the containers with" | | 1 | "She wore a Cardiff University" | | 2 | "She straightened, squaring her shoulders," | | 3 | "Her glass froze in mid-air," | | 4 | "She wiped her hands on" | | 5 | "She was thinner now, the" | | 6 | "She reached out, then stopped," | | 7 | "She crossed her arms, the" | | 8 | "She laughed, and the sound" | | 9 | "His hazel eyes flicked from" | | 10 | "He set the glasses down" | | 11 | "Her hand shook, the amber" | | 12 | "She touched the scar on" | | 13 | "It burned, clean and fierce." | | 14 | "She looked at her hands—delivery—rough," | | 15 | "Her fingers were cold, the" | | 16 | "Her eyes were red-rimmed, mascara" | | 17 | "She glanced at the maps" | | 18 | "She thought of the Pre-Law" | | 19 | "She thought of Eva's wedding," |
| | ratio | 0.284 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 76 | | totalSentences | 81 | | matches | | 0 | "Aurora pushed through the door," | | 1 | "The Golden Empress bags cut" | | 2 | "The darkness pooled around her" | | 3 | "She unloaded the containers with" | | 4 | "A woman sat at the" | | 5 | "Auburn hair pulled back in" | | 6 | "She wore a Cardiff University" | | 7 | "Aurora's lungs locked." | | 8 | "She straightened, squaring her shoulders," | | 9 | "Eva looked up." | | 10 | "Her glass froze in mid-air," | | 11 | "Eva's voice cracked on the" | | 12 | "Aurora didn't smile." | | 13 | "She wiped her hands on" | | 14 | "The flat on Albany Road" | | 15 | "Eva set the glass down" | | 16 | "Aurora stepped closer." | | 17 | "The floorboards creaked under her" | | 18 | "She was thinner now, the" | | 19 | "The girl who'd worn sundresses" |
| | ratio | 0.938 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 17.86% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 7 | | matches | | 0 | "The darkness pooled around her in the Raven's Nest—dim amber light, the smell of spilled ale and polished mahogany, walls papered with maps that curled at the c…" | | 1 | "She straightened, squaring her shoulders, feeling the crescent scar on her left wrist tingle beneath her sleeve." | | 2 | "The flat on Albany Road where they'd shared cigarettes and cheap wine, planning futures that shattered against the pavement." | | 3 | "She was thinner now, the bones of her wrist sharp beneath the pale scar, her bright blue eyes fixed on Eva's with the flat assessment of someone who had learned…" | | 4 | "His hazel eyes flicked from Aurora to Eva, reading the tension that hummed between them, the unspoken history pressing against the air like humidity." | | 5 | "She thought of Eva's wedding, maybe, or the funeral she'd missed, or the children she might have had, the normal life that had dissolved into the London rain, l…" | | 6 | "The scent of Eva's perfume—jasmine and bergamot, the same bottle from Cardiff—filled her nose, transporting her back to the kitchen on Albany Road, to safety an…" |
| |
| 56.82% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 3 | | matches | | 0 | "Aurora's jaw tightened, a muscle jumping beneath her skin" | | 1 | "Aurora whispered, her voice low against the hum of the refrigerator" | | 2 | "She gestured, the maps, the whisky, the green neon outside" |
| |
| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 7 | | fancyTags | | 0 | "Eva whispered (whisper)" | | 1 | "She laughed (laugh)" | | 2 | "Aurora ordered (order)" | | 3 | "Aurora whispered (whisper)" | | 4 | "Aurora laughed (laugh)" | | 5 | "Aurora whispered (whisper)" | | 6 | "Aurora whispered (whisper)" |
| | dialogueSentences | 49 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 1 | | effectiveRatio | 0.286 | |