| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 60 | | tagDensity | 0.283 | | leniency | 0.567 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.41% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1518 | | totalAiIsmAdverbs | 2 | | 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) | |
| 76.94% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1518 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "flickered" | | 1 | "weight" | | 2 | "charm" | | 3 | "silence" | | 4 | "traced" | | 5 | "intensity" |
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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 | 78 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 78 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 122 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 65 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1525 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 929 | | uniqueNames | 9 | | maxNameDensity | 0.86 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Ptolemy | 3 | | Rory | 8 | | Moreau | 3 | | Golden | 1 | | Empress | 1 | | Lucien | 5 | | Eva | 4 | | Avaros | 1 | | London | 1 |
| | persons | | 0 | "Ptolemy" | | 1 | "Rory" | | 2 | "Moreau" | | 3 | "Lucien" | | 4 | "Eva" |
| | places | | 0 | "Golden" | | 1 | "Avaros" | | 2 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 1 | | matches | | 0 | "something like clove cigarettes" |
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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 | 1525 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 122 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 66 | | mean | 23.11 | | std | 19.88 | | cv | 0.86 | | sampleLengths | | 0 | 54 | | 1 | 31 | | 2 | 49 | | 3 | 43 | | 4 | 12 | | 5 | 37 | | 6 | 11 | | 7 | 28 | | 8 | 1 | | 9 | 16 | | 10 | 73 | | 11 | 19 | | 12 | 8 | | 13 | 58 | | 14 | 6 | | 15 | 15 | | 16 | 35 | | 17 | 5 | | 18 | 4 | | 19 | 27 | | 20 | 34 | | 21 | 21 | | 22 | 55 | | 23 | 7 | | 24 | 12 | | 25 | 68 | | 26 | 5 | | 27 | 57 | | 28 | 7 | | 29 | 62 | | 30 | 6 | | 31 | 8 | | 32 | 51 | | 33 | 4 | | 34 | 1 | | 35 | 30 | | 36 | 36 | | 37 | 41 | | 38 | 7 | | 39 | 35 | | 40 | 2 | | 41 | 2 | | 42 | 2 | | 43 | 47 | | 44 | 6 | | 45 | 33 | | 46 | 45 | | 47 | 12 | | 48 | 2 | | 49 | 25 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 78 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 143 | | matches | | |
| 25.76% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 122 | | ratio | 0.041 | | matches | | 0 | "Something flickered in his mismatched eyes — amber and black, like a candle flame against a void." | | 1 | "He surveyed the room with the practiced attention of a man who noticed everything — the research notes pinned to the wall above Eva’s desk, the collection of jars on the windowsill, the stack of takeaway menus near the kettle." | | 2 | "“No. You never do.” He moved closer, and she caught the scent of him — cedar and smoke, something like clove cigarettes." | | 3 | "The demon looked down at the cat, then back at Rory, and something in his face cracked open — a sliver of uncertainty, of fear, of the man beneath the suits and the secrets." | | 4 | "Behind her, she heard him exhale — a sound that might have been relief or exhaustion or something she wasn’t ready to name yet." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 687 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.02911208151382824 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.004366812227074236 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 122 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 122 | | mean | 12.5 | | std | 10.91 | | cv | 0.873 | | sampleLengths | | 0 | 20 | | 1 | 15 | | 2 | 6 | | 3 | 13 | | 4 | 21 | | 5 | 3 | | 6 | 7 | | 7 | 23 | | 8 | 17 | | 9 | 9 | | 10 | 3 | | 11 | 7 | | 12 | 33 | | 13 | 12 | | 14 | 24 | | 15 | 13 | | 16 | 8 | | 17 | 3 | | 18 | 17 | | 19 | 7 | | 20 | 4 | | 21 | 1 | | 22 | 16 | | 23 | 5 | | 24 | 7 | | 25 | 35 | | 26 | 2 | | 27 | 24 | | 28 | 19 | | 29 | 8 | | 30 | 9 | | 31 | 40 | | 32 | 9 | | 33 | 6 | | 34 | 15 | | 35 | 2 | | 36 | 17 | | 37 | 16 | | 38 | 5 | | 39 | 4 | | 40 | 8 | | 41 | 19 | | 42 | 14 | | 43 | 20 | | 44 | 17 | | 45 | 4 | | 46 | 17 | | 47 | 22 | | 48 | 4 | | 49 | 12 |
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| 48.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3442622950819672 | | totalSentences | 122 | | uniqueOpeners | 42 | |
| 95.24% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 70 | | matches | | 0 | "Then the second." | | 1 | "Then at him." |
| | ratio | 0.029 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 70 | | matches | | 0 | "She marked her place in" | | 1 | "She crossed the cramped flat," | | 2 | "She pressed her eye to" | | 3 | "His platinum hair caught the" | | 4 | "She hadn’t seen him in" | | 5 | "She pulled the third bolt" | | 6 | "His voice came low, accented," | | 7 | "She didn’t open the door" | | 8 | "He shifted his weight onto" | | 9 | "She should close the door." | | 10 | "She knew she should close" | | 11 | "She’d made a life in" | | 12 | "She pulled the door open" | | 13 | "He surveyed the room with" | | 14 | "His gaze lingered on the" | | 15 | "It was a small thing," | | 16 | "He turned to face her" | | 17 | "His voice dropped, losing some" | | 18 | "He didn’t do vulnerable." | | 19 | "He didn’t do the hard" |
| | ratio | 0.571 | |
| 24.29% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 70 | | matches | | 0 | "The knock came at half" | | 1 | "She marked her place in" | | 2 | "Eva wasn’t due back until" | | 3 | "The delivery drivers from the" | | 4 | "She crossed the cramped flat," | | 5 | "She pressed her eye to" | | 6 | "Lucien Moreau stood in the" | | 7 | "His platinum hair caught the" | | 8 | "The charcoal suit fit him" | | 9 | "Rory’s breath caught." | | 10 | "She hadn’t seen him in" | | 11 | "She pulled the third bolt" | | 12 | "His voice came low, accented," | | 13 | "She didn’t open the door" | | 14 | "Something flickered in his mismatched" | | 15 | "He shifted his weight onto" | | 16 | "She should close the door." | | 17 | "She knew she should close" | | 18 | "Whatever business Lucien Moreau had" | | 19 | "She’d made a life in" |
| | ratio | 0.871 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 70 | | matches | (empty) | | ratio | 0 | |
| 44.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 4 | | matches | | 0 | "The knock came at half past eleven, three sharp raps against the wood that sent Ptolemy scattering from Rory’s lap." | | 1 | "He surveyed the room with the practiced attention of a man who noticed everything — the research notes pinned to the wall above Eva’s desk, the collection of ja…" | | 2 | "Lucien Moreau dealt in secrets and favors, in the careful exchange of information that kept London’s supernatural underworld from tearing itself apart." | | 3 | "Behind her, she heard him exhale — a sound that might have been relief or exhaustion or something she wasn’t ready to name yet." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 60 | | tagDensity | 0.083 | | leniency | 0.167 | | rawRatio | 0.2 | | effectiveRatio | 0.033 | |