| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 1 | | adverbTags | | 0 | "The name tasted like [like]" |
| | dialogueSentences | 45 | | tagDensity | 0.311 | | leniency | 0.622 | | rawRatio | 0.071 | | effectiveRatio | 0.044 | |
| 96.61% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1476 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 25.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1476 | | totalAiIsms | 22 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "whisper" | | 1 | "silence" | | 2 | "chaotic" | | 3 | "charged" | | 4 | "chill" | | 5 | "scanned" | | 6 | "marble" | | 7 | "familiar" | | 8 | "unreadable" | | 9 | "complex" | | 10 | "resonance" | | 11 | "tracing" | | 12 | "shattered" | | 13 | "stark" | | 14 | "chilled" | | 15 | "electric" | | 16 | "trembled" | | 17 | "treacherous" | | 18 | "flicker" |
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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 | 111 | | matches | (empty) | |
| 91.38% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 111 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 140 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 1474 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 1048 | | uniqueNames | 12 | | maxNameDensity | 0.76 | | worstName | "Eva" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Eva" | | discoveredNames | | Earl | 1 | | Grey | 1 | | London | 1 | | Eva | 8 | | Brick | 1 | | Lane | 1 | | Moreau | 1 | | French-accented | 1 | | Cardiff | 1 | | Seeing | 1 | | Ptolemy | 3 | | Rory | 3 |
| | persons | | 0 | "Earl" | | 1 | "Grey" | | 2 | "Eva" | | 3 | "Moreau" | | 4 | "Ptolemy" | | 5 | "Rory" |
| | places | | 0 | "London" | | 1 | "Brick" | | 2 | "Lane" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 50.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 75 | | glossingSentenceCount | 3 | | matches | | 0 | "rumble that seemed to vibrate in the small room" | | 1 | "tasted like rust and old fury on her tong" | | 2 | "felt like a violation" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.678 | | wordCount | 1474 | | matches | | 0 | "not for a weapon, but for a slim silver cigarette case" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 140 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 51 | | mean | 28.9 | | std | 17.97 | | cv | 0.622 | | sampleLengths | | 0 | 39 | | 1 | 52 | | 2 | 77 | | 3 | 37 | | 4 | 6 | | 5 | 42 | | 6 | 2 | | 7 | 65 | | 8 | 38 | | 9 | 30 | | 10 | 28 | | 11 | 44 | | 12 | 3 | | 13 | 28 | | 14 | 44 | | 15 | 37 | | 16 | 46 | | 17 | 42 | | 18 | 22 | | 19 | 10 | | 20 | 26 | | 21 | 10 | | 22 | 37 | | 23 | 8 | | 24 | 59 | | 25 | 16 | | 26 | 48 | | 27 | 38 | | 28 | 28 | | 29 | 17 | | 30 | 5 | | 31 | 28 | | 32 | 60 | | 33 | 9 | | 34 | 5 | | 35 | 50 | | 36 | 36 | | 37 | 41 | | 38 | 34 | | 39 | 23 | | 40 | 47 | | 41 | 7 | | 42 | 23 | | 43 | 19 | | 44 | 17 | | 45 | 1 | | 46 | 12 | | 47 | 21 | | 48 | 33 | | 49 | 17 |
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| 98.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 111 | | matches | | 0 | "been carved" | | 1 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 160 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 140 | | ratio | 0.014 | | matches | | 0 | "Her hand closed around the first solid object she reached—a heavy, brass-backed bookend shaped like a griffin." | | 1 | "The scent of him hit her—sandalwood, cold rain, and something darker, like embers." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1031 | | adjectiveStacks | 2 | | stackExamples | | 0 | "thin, leather-bound journal" | | 1 | "low, French-accented rumble" |
| | adverbCount | 26 | | adverbRatio | 0.02521823472356935 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005819592628516004 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 140 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 140 | | mean | 10.53 | | std | 7.41 | | cv | 0.704 | | sampleLengths | | 0 | 5 | | 1 | 13 | | 2 | 21 | | 3 | 11 | | 4 | 6 | | 5 | 14 | | 6 | 1 | | 7 | 12 | | 8 | 8 | | 9 | 7 | | 10 | 22 | | 11 | 2 | | 12 | 13 | | 13 | 6 | | 14 | 1 | | 15 | 26 | | 16 | 10 | | 17 | 2 | | 18 | 14 | | 19 | 1 | | 20 | 10 | | 21 | 6 | | 22 | 3 | | 23 | 12 | | 24 | 17 | | 25 | 6 | | 26 | 4 | | 27 | 2 | | 28 | 19 | | 29 | 9 | | 30 | 23 | | 31 | 12 | | 32 | 2 | | 33 | 16 | | 34 | 5 | | 35 | 17 | | 36 | 20 | | 37 | 3 | | 38 | 7 | | 39 | 19 | | 40 | 9 | | 41 | 3 | | 42 | 30 | | 43 | 7 | | 44 | 4 | | 45 | 3 | | 46 | 7 | | 47 | 21 | | 48 | 12 | | 49 | 1 |
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| 58.81% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.37857142857142856 | | totalSentences | 140 | | uniqueOpeners | 53 | |
| 66.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 100 | | matches | | 0 | "Just held it, his thumb" | | 1 | "Then he was gone, the" |
| | ratio | 0.02 | |
| 28.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 100 | | matches | | 0 | "she muttered, twisting the key" | | 1 | "It gave with a metallic" | | 2 | "She slotted the last bolt" | | 3 | "Her flat felt different since" | | 4 | "She’d felt it the moment" | | 5 | "She pushed off the door" | | 6 | "She moved without thinking, her" | | 7 | "Her hand closed around the" | | 8 | "She rounded the doorway." | | 9 | "He stood by the window," | | 10 | "It had been eight months." | | 11 | "he said, his voice a" | | 12 | "He didn’t turn." | | 13 | "She lowered the bookend, but" | | 14 | "He finally turned." | | 15 | "He held up the journal" | | 16 | "Her best friend, her saviour," | | 17 | "He moved towards the desk," | | 18 | "He laid the journal down." | | 19 | "He was a creature of" |
| | ratio | 0.48 | |
| 50.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 100 | | matches | | 0 | "The second deadbolt wouldn't turn." | | 1 | "Aurora put her shoulder into" | | 2 | "The scent of stale curry" | | 3 | "she muttered, twisting the key" | | 4 | "It gave with a metallic" | | 5 | "She slotted the last bolt" | | 6 | "A heavy, listening sort of" | | 7 | "The kind of quiet that" | | 8 | "Her flat felt different since" | | 9 | "Books still toppled in precarious" | | 10 | "A chaotic, scholarly nest that" | | 11 | "She’d felt it the moment" | | 12 | "She pushed off the door" | | 13 | "Ptolemy, Eva’s fat tabby, was" | | 14 | "A floorboard groaned in the" | | 15 | "Rory’s breath stilled." | | 16 | "She moved without thinking, her" | | 17 | "Her hand closed around the" | | 18 | "She rounded the doorway." | | 19 | "He stood by the window," |
| | ratio | 0.82 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 100 | | matches | (empty) | | ratio | 0 | |
| 86.47% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 3 | | matches | | 0 | "He was a creature of sleek city shadows and whispered deals, not cramped flats that smelled of take-away." | | 1 | "Work with the one person who’d shattered her fledgling belief that this new life could be safe, could be simple." | | 2 | "Eva, who’d given her a home when she had none." |
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| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, her voice steady now, cold" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 45 | | tagDensity | 0.067 | | leniency | 0.133 | | rawRatio | 0.333 | | effectiveRatio | 0.044 | |