| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 1 | | adverbTags | | 0 | "Megan said quietly [quietly]" |
| | dialogueSentences | 44 | | tagDensity | 0.455 | | leniency | 0.909 | | rawRatio | 0.05 | | effectiveRatio | 0.045 | |
| 91.95% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1242 | | 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) | |
| 75.85% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1242 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "scanned" | | 1 | "stomach" | | 2 | "determined" | | 3 | "perfect" | | 4 | "familiar" | | 5 | "traced" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 62 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 62 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 84 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 61 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 11 | | totalWords | 1252 | | ratio | 0.009 | | matches | | 0 | "stay as long as you like, ask nothing of me." | | 1 | "your" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 19.79% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 57 | | wordCount | 768 | | uniqueNames | 13 | | maxNameDensity | 2.6 | | worstName | "Rory" | | maxWindowNameDensity | 4 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Thursday | 1 | | Szechuan | 1 | | Rory | 20 | | Welsh | 1 | | Price | 1 | | Cardiff | 1 | | University | 1 | | Megan | 19 | | Merthyr | 1 | | Silas | 6 | | Negroni | 3 |
| | persons | | 0 | "Raven" | | 1 | "Rory" | | 2 | "Price" | | 3 | "Megan" | | 4 | "Silas" | | 5 | "Negroni" |
| | places | | | globalScore | 0.198 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 37 | | 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 | 1252 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 84 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 33.84 | | std | 25.74 | | cv | 0.761 | | sampleLengths | | 0 | 88 | | 1 | 18 | | 2 | 55 | | 3 | 18 | | 4 | 8 | | 5 | 59 | | 6 | 30 | | 7 | 7 | | 8 | 18 | | 9 | 86 | | 10 | 25 | | 11 | 15 | | 12 | 6 | | 13 | 50 | | 14 | 20 | | 15 | 38 | | 16 | 5 | | 17 | 53 | | 18 | 59 | | 19 | 20 | | 20 | 113 | | 21 | 1 | | 22 | 28 | | 23 | 49 | | 24 | 19 | | 25 | 28 | | 26 | 51 | | 27 | 4 | | 28 | 61 | | 29 | 31 | | 30 | 53 | | 31 | 19 | | 32 | 31 | | 33 | 9 | | 34 | 5 | | 35 | 30 | | 36 | 42 |
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| 93.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 62 | | matches | | 0 | "was meant" | | 1 | "were shaped" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 145 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 84 | | ratio | 0.06 | | matches | | 0 | "She scanned the bar with the practiced sweep of someone used to reading rooms — the maps on the walls, the photographs, the exits." | | 1 | "But under the jaw, half-hidden by the collar of the coat, there was a scar Rory didn't remember — thin, pale, deliberate-looking." | | 2 | "Megan looked up at him — really looked, the room-reading sweep again — and Rory watched her take in the limp as he moved away, the signet ring, the stillness of him, and file it all somewhere." | | 3 | "Rory thought about all the versions of this conversation she'd imagined on night buses and delivery runs — the ones where she was magnificent and cutting, the ones where Megan wept." | | 4 | "Behind the bar, Silas turned the music up by one small degree, giving them the mercy of noise, and the years sat down between them like a third old friend — uninvited, unchangeable, and, at last, acknowledged." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 770 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.02987012987012987 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.00909090909090909 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 84 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 84 | | mean | 14.9 | | std | 12.69 | | cv | 0.851 | | sampleLengths | | 0 | 23 | | 1 | 34 | | 2 | 31 | | 3 | 18 | | 4 | 24 | | 5 | 24 | | 6 | 7 | | 7 | 16 | | 8 | 2 | | 9 | 7 | | 10 | 1 | | 11 | 2 | | 12 | 3 | | 13 | 4 | | 14 | 18 | | 15 | 32 | | 16 | 11 | | 17 | 19 | | 18 | 5 | | 19 | 2 | | 20 | 15 | | 21 | 3 | | 22 | 8 | | 23 | 25 | | 24 | 5 | | 25 | 4 | | 26 | 4 | | 27 | 18 | | 28 | 22 | | 29 | 3 | | 30 | 22 | | 31 | 10 | | 32 | 5 | | 33 | 3 | | 34 | 3 | | 35 | 21 | | 36 | 29 | | 37 | 15 | | 38 | 5 | | 39 | 6 | | 40 | 32 | | 41 | 5 | | 42 | 21 | | 43 | 32 | | 44 | 10 | | 45 | 5 | | 46 | 44 | | 47 | 5 | | 48 | 15 | | 49 | 13 |
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| 73.02% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.4880952380952381 | | totalSentences | 84 | | uniqueOpeners | 41 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 51 | | matches | | 0 | "Then her eyes found Rory," | | 1 | "Somewhere behind them a chair" |
| | ratio | 0.039 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 7 | | totalSentences | 51 | | matches | | 0 | "She was three sips in" | | 1 | "She scanned the bar with" | | 2 | "They'd shared a kettle, a" | | 3 | "She turned the glass, and" | | 4 | "She finally sipped" | | 5 | "She turned an olive on" | | 6 | "She turned her hand over" |
| | ratio | 0.137 | |
| 48.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 42 | | totalSentences | 51 | | matches | | 0 | "The Raven's Nest was quiet" | | 1 | "Rory had come down the" | | 2 | "Silas poured it without asking," | | 3 | "She was three sips in" | | 4 | "The woman who shook off" | | 5 | "She scanned the bar with" | | 6 | "The voice came out unguarded," | | 7 | "Rory's stomach dropped somewhere near" | | 8 | "Pre-Law, Cardiff University." | | 9 | "They'd shared a kettle, a" | | 10 | "Megan had been the loudest" | | 11 | "This Megan crossed the bar" | | 12 | "Megan laughed, and it was" | | 13 | "Rory couldn't tell if it" | | 14 | "Megan flagged Silas, ordered a" | | 15 | "The brows were shaped." | | 16 | "The nails were perfect." | | 17 | "The name landed in Rory's" | | 18 | "Megan's smile faltered." | | 19 | "Rory turned her glass in" |
| | ratio | 0.824 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 51 | | matches | (empty) | | ratio | 0 | |
| 18.63% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 4 | | matches | | 0 | "Rory had come down the back stairs from her flat still smelling of Szechuan oil from the evening's deliveries, wanting nothing more than a ginger ale and twenty…" | | 1 | "The woman who shook off the rain was tall, polished, her blonde hair cut into something architectural that probably cost more than Rory's rent." | | 2 | "Megan had been the loudest laugh in any room, crop tops and fake ID, determined to become a barrister mostly to spite her father, who'd told her girls from Mert…" | | 3 | "Rory found she didn't know what to do with her hands, so she pressed the crescent scar on her left wrist flat against the cold glass and felt the old familiar s…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 2 | | fancyTags | | 0 | "Megan laughed (laugh)" | | 1 | "she whispered (whisper)" |
| | dialogueSentences | 44 | | tagDensity | 0.227 | | leniency | 0.455 | | rawRatio | 0.2 | | effectiveRatio | 0.091 | |