| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 59 | | tagDensity | 0.22 | | leniency | 0.441 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1150 | | 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) | |
| 60.87% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1150 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "crystal" | | 1 | "flicked" | | 2 | "silk" | | 3 | "weight" | | 4 | "familiar" | | 5 | "sanctuary" | | 6 | "warmth" | | 7 | "silence" |
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| 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 | 67 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 67 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 113 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 1150 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 25.55% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 57 | | wordCount | 683 | | uniqueNames | 23 | | maxNameDensity | 2.49 | | worstName | "Callum" | | maxWindowNameDensity | 4 | | worstWindowName | "Callum" | | discoveredNames | | Rory | 13 | | Torts | 1 | | Italian | 1 | | Soho | 1 | | Callum | 17 | | Golden | 1 | | Empress | 1 | | Silas | 5 | | Prague | 1 | | Raven | 2 | | Nest | 2 | | London | 1 | | Ice | 1 | | Silence | 1 | | Cold | 1 | | War | 1 | | Berlin | 1 | | Desperation | 1 | | Cardiff | 1 | | Roath | 1 | | Victoria | 1 | | Station | 1 | | Heavy | 1 |
| | persons | | 0 | "Rory" | | 1 | "Torts" | | 2 | "Callum" | | 3 | "Silas" | | 4 | "Raven" | | 5 | "Nest" | | 6 | "Ice" | | 7 | "Silence" | | 8 | "Desperation" | | 9 | "Heavy" |
| | places | | 0 | "Soho" | | 1 | "Golden" | | 2 | "Prague" | | 3 | "London" | | 4 | "Cold" | | 5 | "Berlin" | | 6 | "Cardiff" | | 7 | "Roath" | | 8 | "Victoria" |
| | globalScore | 0.255 | | windowScore | 0.333 | |
| 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 | 1150 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 113 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 66 | | mean | 17.42 | | std | 17.36 | | cv | 0.996 | | sampleLengths | | 0 | 8 | | 1 | 15 | | 2 | 2 | | 3 | 33 | | 4 | 65 | | 5 | 1 | | 6 | 2 | | 7 | 48 | | 8 | 6 | | 9 | 26 | | 10 | 5 | | 11 | 11 | | 12 | 6 | | 13 | 5 | | 14 | 45 | | 15 | 4 | | 16 | 5 | | 17 | 56 | | 18 | 64 | | 19 | 6 | | 20 | 7 | | 21 | 11 | | 22 | 15 | | 23 | 11 | | 24 | 12 | | 25 | 2 | | 26 | 46 | | 27 | 2 | | 28 | 4 | | 29 | 20 | | 30 | 1 | | 31 | 9 | | 32 | 10 | | 33 | 35 | | 34 | 5 | | 35 | 11 | | 36 | 3 | | 37 | 19 | | 38 | 3 | | 39 | 7 | | 40 | 38 | | 41 | 5 | | 42 | 5 | | 43 | 2 | | 44 | 31 | | 45 | 12 | | 46 | 16 | | 47 | 8 | | 48 | 24 | | 49 | 9 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 67 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 109 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 113 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 689 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.02177068214804064 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.00725689404934688 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 113 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 113 | | mean | 10.18 | | std | 7.05 | | cv | 0.693 | | sampleLengths | | 0 | 8 | | 1 | 9 | | 2 | 6 | | 3 | 2 | | 4 | 21 | | 5 | 12 | | 6 | 2 | | 7 | 20 | | 8 | 20 | | 9 | 9 | | 10 | 14 | | 11 | 1 | | 12 | 2 | | 13 | 6 | | 14 | 6 | | 15 | 21 | | 16 | 15 | | 17 | 3 | | 18 | 3 | | 19 | 15 | | 20 | 11 | | 21 | 5 | | 22 | 11 | | 23 | 6 | | 24 | 5 | | 25 | 12 | | 26 | 12 | | 27 | 21 | | 28 | 4 | | 29 | 5 | | 30 | 6 | | 31 | 15 | | 32 | 16 | | 33 | 19 | | 34 | 2 | | 35 | 13 | | 36 | 23 | | 37 | 26 | | 38 | 4 | | 39 | 2 | | 40 | 7 | | 41 | 11 | | 42 | 15 | | 43 | 11 | | 44 | 7 | | 45 | 5 | | 46 | 2 | | 47 | 14 | | 48 | 6 | | 49 | 26 |
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| 100.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.6106194690265486 | | totalSentences | 113 | | uniqueOpeners | 69 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 56 | | matches | | 0 | "Instead, he slid a thick" | | 1 | "Just her dead name, *Aurora*," |
| | ratio | 0.036 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 10 | | totalSentences | 56 | | matches | | 0 | "His hair, once a bird's" | | 1 | "She tugged the cuff of" | | 2 | "His hazel eyes flicked from" | | 3 | "She looked past Callum at" | | 4 | "He swallowed his gin in" | | 5 | "His shoulders sagged, spoiling the" | | 6 | "He turned on his stool," | | 7 | "Her gaze snapped from the" | | 8 | "They were trembling." | | 9 | "His silver signet ring tapped" |
| | ratio | 0.179 | |
| 85.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 42 | | totalSentences | 56 | | matches | | 0 | "Rory froze, the heavy crystal" | | 1 | "The man on the stool" | | 2 | "The dim green glow from" | | 3 | "A sharp dark Italian wool" | | 4 | "His hair, once a bird's" | | 5 | "Nobody in Soho used that" | | 6 | "Rory set the whisky down," | | 7 | "She tugged the cuff of" | | 8 | "Callum's gaze dropped to the" | | 9 | "His hazel eyes flicked from" | | 10 | "Silas shifted his weight off" | | 11 | "Silas studied Callum for three" | | 12 | "The quiet authority of a" | | 13 | "Callum met the stare, his" | | 14 | "Silas gave a single nod" | | 15 | "She looked past Callum at" | | 16 | "Rory picked at a peeling" | | 17 | "Cardboard flaked under her thumbnail." | | 18 | "Callum rotated his glass" | | 19 | "Ice clinked, a sharp, lonely" |
| | ratio | 0.75 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 4 | | matches | | 0 | "Gone were the frayed jumpers and ink-stained knuckles of the boy who shared his Torts notes in cold lecture halls." | | 1 | "The quiet authority of a man who survived Prague hung between them, heavy and unmistakable." | | 2 | "A crack splintered the polished courtroom veneer, revealing a flash of the twenty-year-old boy who used to leave custard creams outside her door during exam wee…" | | 3 | "Sitting beside Callum, smelling his cedarwood cologne instead of cheap roll-ups, she mourned the girl who used to highlight statutes in neon pink." |
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| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 1 | | matches | | 0 | "Callum leaned in, breath reeking of juniper and sheer terror" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | 0 | "she corrected (correct)" |
| | dialogueSentences | 59 | | tagDensity | 0.102 | | leniency | 0.203 | | rawRatio | 0.167 | | effectiveRatio | 0.034 | |