| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 62 | | tagDensity | 0.226 | | leniency | 0.452 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1441 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 72.24% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1441 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "weight" | | 1 | "measured" | | 2 | "scanning" | | 3 | "silence" | | 4 | "unspoken" | | 5 | "tracing" | | 6 | "dancing" |
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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 | 65 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 65 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 113 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1437 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 860 | | uniqueNames | 11 | | maxNameDensity | 1.63 | | worstName | "Gareth" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Gareth" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Dean | 1 | | Street | 1 | | South | 1 | | Wales | 1 | | Golden | 1 | | Empress | 1 | | Gareth | 14 | | Rory | 11 | | Silas | 6 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Gareth" | | 3 | "Rory" | | 4 | "Silas" |
| | places | | 0 | "Dean" | | 1 | "Street" | | 2 | "South" | | 3 | "Wales" | | 4 | "Golden" |
| | globalScore | 0.686 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | 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 | 1437 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 113 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 77 | | mean | 18.66 | | std | 16.19 | | cv | 0.867 | | sampleLengths | | 0 | 48 | | 1 | 11 | | 2 | 33 | | 3 | 5 | | 4 | 32 | | 5 | 30 | | 6 | 47 | | 7 | 14 | | 8 | 1 | | 9 | 24 | | 10 | 10 | | 11 | 1 | | 12 | 33 | | 13 | 6 | | 14 | 1 | | 15 | 60 | | 16 | 5 | | 17 | 24 | | 18 | 14 | | 19 | 6 | | 20 | 15 | | 21 | 39 | | 22 | 10 | | 23 | 4 | | 24 | 3 | | 25 | 23 | | 26 | 2 | | 27 | 57 | | 28 | 10 | | 29 | 3 | | 30 | 22 | | 31 | 5 | | 32 | 58 | | 33 | 1 | | 34 | 2 | | 35 | 20 | | 36 | 44 | | 37 | 6 | | 38 | 3 | | 39 | 36 | | 40 | 8 | | 41 | 4 | | 42 | 18 | | 43 | 16 | | 44 | 22 | | 45 | 6 | | 46 | 38 | | 47 | 12 | | 48 | 8 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 65 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 131 | | matches | (empty) | |
| 41.72% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 113 | | ratio | 0.035 | | matches | | 0 | "The voice carried the thick, rounded vowels of South Wales—a sound she had spent four years scrubbing off her own tongue." | | 1 | "He glanced around the bar—the dusty maritime maps pinned to the plaster, the black-and-white photos of forgotten boxers, the faint smell of stale draft beer." | | 2 | "Gareth rubbed his temple with two fingers—a gesture straight out of their old university library sessions." | | 3 | "He looked at her one last time—at the black hair, the hard lines around her mouth, the sharp intelligence that no amount of grease or cheap booze could erase." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 875 | | adjectiveStacks | 2 | | stackExamples | | 0 | "pale, crescent-shaped scar" | | 1 | "damp, diesel-tainted air" |
| | adverbCount | 9 | | adverbRatio | 0.010285714285714285 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 113 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 113 | | mean | 12.72 | | std | 9.06 | | cv | 0.713 | | sampleLengths | | 0 | 18 | | 1 | 18 | | 2 | 12 | | 3 | 11 | | 4 | 10 | | 5 | 10 | | 6 | 13 | | 7 | 5 | | 8 | 28 | | 9 | 4 | | 10 | 10 | | 11 | 20 | | 12 | 14 | | 13 | 8 | | 14 | 25 | | 15 | 7 | | 16 | 7 | | 17 | 1 | | 18 | 3 | | 19 | 21 | | 20 | 4 | | 21 | 6 | | 22 | 1 | | 23 | 25 | | 24 | 8 | | 25 | 6 | | 26 | 1 | | 27 | 14 | | 28 | 24 | | 29 | 22 | | 30 | 5 | | 31 | 11 | | 32 | 13 | | 33 | 14 | | 34 | 6 | | 35 | 15 | | 36 | 20 | | 37 | 19 | | 38 | 10 | | 39 | 4 | | 40 | 3 | | 41 | 16 | | 42 | 7 | | 43 | 2 | | 44 | 24 | | 45 | 33 | | 46 | 10 | | 47 | 3 | | 48 | 22 | | 49 | 5 |
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| 53.98% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.37168141592920356 | | totalSentences | 113 | | uniqueOpeners | 42 | |
| 53.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 62 | | matches | | 0 | "Bright blue eyes locked onto" |
| | ratio | 0.016 | |
| 71.61% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 62 | | matches | | 0 | "His grey-streaked auburn hair caught" | | 1 | "Her straight black hair fell" | | 2 | "She kept her gaze fixed" | | 3 | "He ran fingers through combed" | | 4 | "His gaze snagged on the" | | 5 | "His boots froze on the" | | 6 | "She turned her stool." | | 7 | "He took three fast steps" | | 8 | "He surveyed her, taking in" | | 9 | "His hazel eyes lingered on" | | 10 | "He took a quick sip," | | 11 | "He waited for a reaction," | | 12 | "He glanced around the bar—the" | | 13 | "He glanced at the water-stained" | | 14 | "She swallowed the rest of" | | 15 | "He looked at her through" | | 16 | "Her gaze softened for a" | | 17 | "He stood up, smoothing the" | | 18 | "He pulled a crisp fifty-pound" | | 19 | "He took his briefcase, holding" |
| | ratio | 0.371 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 62 | | matches | | 0 | "Rain smashed against the front" | | 1 | "Silas set a heavy glass" | | 2 | "His grey-streaked auburn hair caught" | | 3 | "Rory thumbed the pale, crescent-shaped" | | 4 | "Her straight black hair fell" | | 5 | "She kept her gaze fixed" | | 6 | "Silas wiped down the stainless" | | 7 | "The brass chime over the" | | 8 | "A draft of damp, diesel-tainted" | | 9 | "A tall man stepped over" | | 10 | "A leather briefcase swung from" | | 11 | "He ran fingers through combed" | | 12 | "His gaze snagged on the" | | 13 | "His boots froze on the" | | 14 | "Rory’s shoulders hitched." | | 15 | "The voice carried the thick," | | 16 | "She turned her stool." | | 17 | "He took three fast steps" | | 18 | "A gold watch gleamed under" | | 19 | "Gareth stripped off his leather" |
| | ratio | 0.952 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 3 | | matches | | 0 | "He ran fingers through combed brown hair, scanning the low-ceilinged room with the cautious eye of someone who took the wrong turn off Dean Street." | | 1 | "He took three fast steps forward, stopping short of the empty stool beside her as if an outstretched hand might shatter the air between them." | | 2 | "He hesitated, his lips parted as if to offer a counter-argument, but no legal precedent existed for the space she occupied now." |
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| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 1 | | matches | | 0 | "He waited, his posture stiffening into the poise of the courtroom" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "Gareth murmured (murmur)" |
| | dialogueSentences | 62 | | tagDensity | 0.032 | | leniency | 0.065 | | rawRatio | 0.5 | | effectiveRatio | 0.032 | |