| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 24 | | adverbTagCount | 3 | | adverbTags | | 0 | "I gestured vaguely [vaguely]" | | 1 | "Cerys said finally [finally]" | | 2 | "She looked around [around]" |
| | dialogueSentences | 69 | | tagDensity | 0.348 | | leniency | 0.696 | | rawRatio | 0.125 | | effectiveRatio | 0.087 | |
| 88.21% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1696 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "quickly" | | 1 | "slowly" | | 2 | "really" |
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| 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) | |
| 67.57% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1696 | | totalAiIsms | 11 | | found | | 0 | | | 1 | | | 2 | | | 3 | | word | "down my spine" | | count | 1 |
| | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | |
| | highlights | | 0 | "shattered" | | 1 | "familiar" | | 2 | "comfortable" | | 3 | "down my spine" | | 4 | "lilt" | | 5 | "trembled" | | 6 | "fractured" | | 7 | "weight" | | 8 | "stomach" | | 9 | "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 | 108 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 108 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 153 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 68 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1685 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 23 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1041 | | uniqueNames | 15 | | maxNameDensity | 0.86 | | worstName | "Silas" | | maxWindowNameDensity | 2 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 2 | | Nest | 3 | | Silas | 9 | | Soho | 1 | | Friday | 1 | | London | 3 | | Ellis | 1 | | Fractured | 1 | | Cardiff | 3 | | Cerys | 9 | | Welsh | 2 | | Impersonal | 1 | | Silence | 1 | | Evan | 1 | | Drew | 1 |
| | persons | | 0 | "Raven" | | 1 | "Silas" | | 2 | "Ellis" | | 3 | "Cerys" | | 4 | "Evan" | | 5 | "Drew" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Cardiff" | | 3 | "Welsh" |
| | globalScore | 1 | | windowScore | 1 | |
| 74.24% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like mine" | | 1 | "r drink orders apparently extending to Welsh" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1685 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 153 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 68 | | mean | 24.78 | | std | 21.62 | | cv | 0.872 | | sampleLengths | | 0 | 8 | | 1 | 40 | | 2 | 37 | | 3 | 2 | | 4 | 1 | | 5 | 54 | | 6 | 12 | | 7 | 40 | | 8 | 24 | | 9 | 48 | | 10 | 2 | | 11 | 1 | | 12 | 53 | | 13 | 55 | | 14 | 1 | | 15 | 10 | | 16 | 14 | | 17 | 21 | | 18 | 76 | | 19 | 1 | | 20 | 16 | | 21 | 27 | | 22 | 3 | | 23 | 29 | | 24 | 35 | | 25 | 45 | | 26 | 20 | | 27 | 1 | | 28 | 3 | | 29 | 59 | | 30 | 19 | | 31 | 49 | | 32 | 20 | | 33 | 4 | | 34 | 77 | | 35 | 2 | | 36 | 11 | | 37 | 29 | | 38 | 1 | | 39 | 30 | | 40 | 2 | | 41 | 16 | | 42 | 39 | | 43 | 11 | | 44 | 4 | | 45 | 31 | | 46 | 11 | | 47 | 80 | | 48 | 9 | | 49 | 10 |
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| 98.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 108 | | matches | | 0 | "being asked" | | 1 | "been replaced" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 187 | | matches | | 0 | "was looking" | | 1 | "was crying" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 153 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1048 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.02767175572519084 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.01049618320610687 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 153 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 153 | | mean | 11.01 | | std | 10.06 | | cv | 0.914 | | sampleLengths | | 0 | 8 | | 1 | 11 | | 2 | 9 | | 3 | 20 | | 4 | 13 | | 5 | 22 | | 6 | 2 | | 7 | 2 | | 8 | 1 | | 9 | 11 | | 10 | 3 | | 11 | 11 | | 12 | 29 | | 13 | 12 | | 14 | 13 | | 15 | 16 | | 16 | 7 | | 17 | 4 | | 18 | 17 | | 19 | 7 | | 20 | 28 | | 21 | 15 | | 22 | 5 | | 23 | 2 | | 24 | 1 | | 25 | 3 | | 26 | 3 | | 27 | 24 | | 28 | 5 | | 29 | 5 | | 30 | 13 | | 31 | 15 | | 32 | 4 | | 33 | 19 | | 34 | 5 | | 35 | 3 | | 36 | 9 | | 37 | 1 | | 38 | 10 | | 39 | 2 | | 40 | 2 | | 41 | 10 | | 42 | 8 | | 43 | 13 | | 44 | 24 | | 45 | 20 | | 46 | 32 | | 47 | 1 | | 48 | 7 | | 49 | 9 |
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| 67.97% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.47058823529411764 | | totalSentences | 153 | | uniqueOpeners | 72 | |
| 36.63% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 91 | | matches | | 0 | "Already feeling the walls of" |
| | ratio | 0.011 | |
| 52.97% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 91 | | matches | | 0 | "My hand moved on instinct," | | 1 | "He didn't move from his" | | 2 | "They knew better." | | 3 | "I set the mug upright" | | 4 | "She nodded too quickly, gathering" | | 5 | "I wiped my hands on" | | 6 | "I'd earned the drink." | | 7 | "I gestured at the walls," | | 8 | "He didn't smile." | | 9 | "He rarely did." | | 10 | "It wasn't even particularly comfortable." | | 11 | "I didn't look up." | | 12 | "I turned slowly, already knowing" | | 13 | "She wore the kind of" | | 14 | "It belonged to someone I'd" | | 15 | "She stepped closer, her heels" | | 16 | "She laughed, but it came" | | 17 | "I felt his attention like" | | 18 | "She was looking at my" | | 19 | "I gestured vaguely toward the" |
| | ratio | 0.418 | |
| 47.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 91 | | matches | | 0 | "The glass shattered before I" | | 1 | "My hand moved on instinct," | | 2 | "Muscle memory from a life" | | 3 | "The bloke who'd thrown it" | | 4 | "Silas's voice carried across The" | | 5 | "He didn't move from his" | | 6 | "The bloke's mates dragged him" | | 7 | "They knew better." | | 8 | "Everyone in Soho knew better" | | 9 | "I set the mug upright" | | 10 | "She nodded too quickly, gathering" | | 11 | "I wiped my hands on" | | 12 | "I'd earned the drink." | | 13 | "Silas's hazel eyes held that" | | 14 | "I gestured at the walls," | | 15 | "The green neon sign outside" | | 16 | "He didn't smile." | | 17 | "He rarely did." | | 18 | "The Raven's Nest wasn't glamorous." | | 19 | "It wasn't even particularly comfortable." |
| | ratio | 0.824 | |
| 54.95% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 91 | | matches | | 0 | "Before I'd learned that survival" |
| | ratio | 0.011 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 6 | | matches | | 0 | "The bloke who'd thrown it blinked, swaying on his barstool, brain struggling to catch up with his own drunken violence." | | 1 | "He didn't move from his spot behind the counter, polishing a pint glass with the patience of a man who'd seen worse." | | 2 | "I set the mug upright and pushed it toward its original owner, a terrified uni student who'd made the mistake of wearing a low-cut top on a Friday night." | | 3 | "But his shoulders loosened a fraction as he resumed polishing, and I turned back to my drink, savouring the familiar burn of cheap lager." | | 4 | "Cerys Ellis stood in the doorway, rain darkening her blonde bob, her face caught somewhere between disbelief and something that looked dangerously like hope." | | 5 | "She wore the kind of coat I couldn't afford, the kind of shoes that cost more than my monthly rent." |
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| 83.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 24 | | uselessAdditionCount | 2 | | matches | | 0 | "She stepped, her heels clicking against the worn floorboards" | | 1 | "The words came, sharper" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 3 | | fancyTags | | 0 | "She laughed (laugh)" | | 1 | "She whispered (whisper)" | | 2 | "she whispered (whisper)" |
| | dialogueSentences | 69 | | tagDensity | 0.116 | | leniency | 0.232 | | rawRatio | 0.375 | | effectiveRatio | 0.087 | |