| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva gestured vaguely [vaguely]" |
| | dialogueSentences | 63 | | tagDensity | 0.206 | | leniency | 0.413 | | rawRatio | 0.077 | | effectiveRatio | 0.032 | |
| 96.24% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1330 | | 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) | |
| 39.85% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1330 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "echoed" | | 2 | "intricate" | | 3 | "silk" | | 4 | "crystal" | | 5 | "warmth" | | 6 | "reminder" | | 7 | "predator" | | 8 | "silence" | | 9 | "scanning" | | 10 | "unreadable" | | 11 | "footsteps" | | 12 | "glinting" | | 13 | "whisper" | | 14 | "flickered" |
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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 | 1 | | narrationSentences | 73 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 73 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 123 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1330 | | 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 | 43 | | wordCount | 839 | | uniqueNames | 8 | | maxNameDensity | 1.67 | | worstName | "Rory" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 2 | | Nest | 2 | | London | 1 | | Soho | 1 | | Rory | 14 | | Cardiff | 1 | | Eva | 14 | | Silas | 8 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Eva" | | 4 | "Silas" |
| | places | | 0 | "London" | | 1 | "Soho" | | 2 | "Cardiff" |
| | globalScore | 0.666 | | windowScore | 0.167 | |
| 25.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 3 | | matches | | 0 | "quite kill" | | 1 | "looked like she might snap" | | 2 | "felt like a canyon" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.752 | | wordCount | 1330 | | matches | | 0 | "not with pity, but with a terrifying kind of recognition" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 123 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 75 | | mean | 17.73 | | std | 15.11 | | cv | 0.852 | | sampleLengths | | 0 | 67 | | 1 | 8 | | 2 | 44 | | 3 | 8 | | 4 | 7 | | 5 | 55 | | 6 | 10 | | 7 | 7 | | 8 | 4 | | 9 | 51 | | 10 | 14 | | 11 | 1 | | 12 | 39 | | 13 | 1 | | 14 | 8 | | 15 | 17 | | 16 | 20 | | 17 | 9 | | 18 | 31 | | 19 | 4 | | 20 | 8 | | 21 | 17 | | 22 | 37 | | 23 | 6 | | 24 | 6 | | 25 | 48 | | 26 | 10 | | 27 | 6 | | 28 | 6 | | 29 | 9 | | 30 | 23 | | 31 | 7 | | 32 | 14 | | 33 | 6 | | 34 | 10 | | 35 | 2 | | 36 | 31 | | 37 | 3 | | 38 | 21 | | 39 | 16 | | 40 | 13 | | 41 | 48 | | 42 | 21 | | 43 | 12 | | 44 | 7 | | 45 | 27 | | 46 | 7 | | 47 | 25 | | 48 | 7 | | 49 | 20 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 73 | | matches | | |
| 98.99% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 132 | | matches | | 0 | "was polishing" | | 1 | "was staring" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 123 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 842 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, crescent-shaped scar" |
| | adverbCount | 21 | | adverbRatio | 0.02494061757719715 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.011876484560570071 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 123 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 123 | | mean | 10.81 | | std | 6.28 | | cv | 0.581 | | sampleLengths | | 0 | 27 | | 1 | 14 | | 2 | 26 | | 3 | 8 | | 4 | 14 | | 5 | 10 | | 6 | 20 | | 7 | 8 | | 8 | 7 | | 9 | 10 | | 10 | 17 | | 11 | 28 | | 12 | 10 | | 13 | 7 | | 14 | 4 | | 15 | 16 | | 16 | 17 | | 17 | 18 | | 18 | 2 | | 19 | 12 | | 20 | 1 | | 21 | 3 | | 22 | 20 | | 23 | 16 | | 24 | 1 | | 25 | 8 | | 26 | 12 | | 27 | 5 | | 28 | 8 | | 29 | 12 | | 30 | 8 | | 31 | 1 | | 32 | 19 | | 33 | 12 | | 34 | 4 | | 35 | 8 | | 36 | 2 | | 37 | 15 | | 38 | 28 | | 39 | 9 | | 40 | 6 | | 41 | 6 | | 42 | 10 | | 43 | 13 | | 44 | 25 | | 45 | 10 | | 46 | 6 | | 47 | 6 | | 48 | 9 | | 49 | 7 |
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| 39.43% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.2845528455284553 | | totalSentences | 123 | | uniqueOpeners | 35 | |
| 48.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 69 | | matches | | 0 | "Instead, she stared at the" |
| | ratio | 0.014 | |
| 80.87% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 69 | | matches | | 0 | "She didn't look up until" | | 1 | "He didn't look up from" | | 2 | "She rubbed the small, crescent-shaped" | | 3 | "He turned to fetch a" | | 4 | "She held a crystal tumbler" | | 5 | "Her eyes, once bright and" | | 6 | "He sensed the friction, the" | | 7 | "He set the glass down" | | 8 | "She wanted to scream, to" | | 9 | "It was a dull ache" | | 10 | "She reached for her drink" | | 11 | "She stumbled, her shoulder hitting" | | 12 | "She wiped her hand on" | | 13 | "She looked back at Eva." | | 14 | "Her voice had lost its" | | 15 | "She didn't look back at" | | 16 | "She started walking, her pace" | | 17 | "He didn't order a drink." | | 18 | "He simply stood there, a" | | 19 | "He didn't look at the" |
| | ratio | 0.348 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 69 | | matches | | 0 | "The heavy oak door of" | | 1 | "Rory gripped the handle of" | | 2 | "She didn't look up until" | | 3 | "Silas leaned over the polished" | | 4 | "He didn't look up from" | | 5 | "The limp in his stride" | | 6 | "Rory set the bag on" | | 7 | "She rubbed the small, crescent-shaped" | | 8 | "The bar felt smaller than" | | 9 | "Silas asked, his hazel eyes" | | 10 | "He turned to fetch a" | | 11 | "A woman sat there, draped" | | 12 | "She held a crystal tumbler" | | 13 | "The air in the bar" | | 14 | "The woman turned." | | 15 | "The soft, rounded features Rory" | | 16 | "Her eyes, once bright and" | | 17 | "Eva took a slow sip" | | 18 | "The space between them felt" | | 19 | "The smell of stale ale" |
| | ratio | 0.957 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 69 | | matches | (empty) | | ratio | 0 | |
| 73.17% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 4 | | matches | | 0 | "The limp in his stride was more pronounced tonight, a rhythmic hitch that echoed the uneven beat of the music." | | 1 | "The bar felt smaller than usual, the walls crowded with the faded, black-and-white faces of men long dead and the intricate, yellowed lines of maps that led now…" | | 2 | "She started walking, her pace quickening, her breath coming in ragged plumes of white." | | 3 | "A man in a dark overcoat stepped into the bar, his eyes scanning the room before settling on the empty corner booth." |
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| 9.62% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 3 | | matches | | 0 | "Rory hesitated, her tongue feeling heavy" | | 1 | "Rory said, her voice low and steady" | | 2 | "Silas asked, his voice barely a whisper" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 3 | | fancyTags | | 0 | "Eva laughed (laugh)" | | 1 | "Eva snapped (snap)" | | 2 | "Silas muttered (mutter)" |
| | dialogueSentences | 63 | | tagDensity | 0.127 | | leniency | 0.254 | | rawRatio | 0.375 | | effectiveRatio | 0.095 | |