| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 33 | | tagDensity | 0.424 | | leniency | 0.848 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.57% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1312 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "completely" | | 2 | "softly" |
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| 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) | |
| 39.02% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1312 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "silence" | | 1 | "etched" | | 2 | "resolve" | | 3 | "echo" | | 4 | "furrowed" | | 5 | "footsteps" | | 6 | "echoing" | | 7 | "scanning" | | 8 | "calibrated" | | 9 | "scanned" | | 10 | "tracing" | | 11 | "complex" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 51 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 51 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 69 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 55 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 1312 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 540 | | uniqueNames | 8 | | maxNameDensity | 2.96 | | worstName | "Quinn" | | maxWindowNameDensity | 5 | | worstWindowName | "Eva" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 16 | | Morris | 1 | | Kowalski | 1 | | Eva | 14 | | Veil | 1 | | Compass | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Kowalski" | | 4 | "Eva" |
| | places | (empty) | | globalScore | 0.019 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | 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 | 1312 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 69 | | matches | (empty) | |
| 27.70% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 21 | | mean | 62.48 | | std | 15.43 | | cv | 0.247 | | sampleLengths | | 0 | 103 | | 1 | 81 | | 2 | 79 | | 3 | 71 | | 4 | 57 | | 5 | 71 | | 6 | 56 | | 7 | 68 | | 8 | 51 | | 9 | 54 | | 10 | 65 | | 11 | 52 | | 12 | 89 | | 13 | 42 | | 14 | 57 | | 15 | 56 | | 16 | 40 | | 17 | 65 | | 18 | 45 | | 19 | 50 | | 20 | 60 |
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| 98.38% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 51 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 90 | | matches | | |
| 60.04% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 69 | | ratio | 0.029 | | matches | | 0 | "The only disturbance was a faint, shimmering residue on the concrete near the far wall – a residue Quinn recognized from her partner’s case: residual magical energy, cold and dead." | | 1 | "A faint, almost invisible pattern emerged under the UV light – a complex, swirling symbol, barely visible to the naked eye." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 540 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.03888888888888889 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.018518518518518517 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 69 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 69 | | mean | 19.01 | | std | 13.33 | | cv | 0.701 | | sampleLengths | | 0 | 22 | | 1 | 15 | | 2 | 15 | | 3 | 31 | | 4 | 20 | | 5 | 22 | | 6 | 5 | | 7 | 3 | | 8 | 7 | | 9 | 4 | | 10 | 10 | | 11 | 30 | | 12 | 14 | | 13 | 32 | | 14 | 16 | | 15 | 17 | | 16 | 4 | | 17 | 8 | | 18 | 19 | | 19 | 18 | | 20 | 22 | | 21 | 6 | | 22 | 38 | | 23 | 13 | | 24 | 3 | | 25 | 41 | | 26 | 27 | | 27 | 5 | | 28 | 25 | | 29 | 26 | | 30 | 6 | | 31 | 32 | | 32 | 30 | | 33 | 3 | | 34 | 36 | | 35 | 12 | | 36 | 8 | | 37 | 7 | | 38 | 7 | | 39 | 32 | | 40 | 10 | | 41 | 55 | | 42 | 11 | | 43 | 41 | | 44 | 10 | | 45 | 6 | | 46 | 36 | | 47 | 37 | | 48 | 9 | | 49 | 28 |
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| 48.31% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.3333333333333333 | | totalSentences | 69 | | uniqueOpeners | 23 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 50 | | matches | (empty) | | ratio | 0 | |
| 52.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 50 | | matches | | 0 | "Her worn leather watch ticked" | | 1 | "She stood over the scene," | | 2 | "Her military bearing was rigid," | | 3 | "She clutched a worn leather" | | 4 | "Her nervous habit was evident" | | 5 | "She knelt, her gloved hands" | | 6 | "She rose, her gaze sweeping" | | 7 | "She pointed at the shimmering" | | 8 | "She pulled a small, intricately" | | 9 | "She walked towards the far" | | 10 | "She paused, her eyes scanning" | | 11 | "She gestured at the empty" | | 12 | "She pulled the Veil Compass" | | 13 | "It remained stubbornly still, its" | | 14 | "Her military training honed her" | | 15 | "She walked to the far" | | 16 | "She pulled a small, handheld" | | 17 | "She looked at Quinn, her" | | 18 | "She stepped back, her gaze" | | 19 | "She looked at Eva, her" |
| | ratio | 0.42 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 48 | | totalSentences | 50 | | matches | | 0 | "The air in the abandoned" | | 1 | "Detective Harlow Quinn’s breath misted" | | 2 | "Her worn leather watch ticked" | | 3 | "She stood over the scene," | | 4 | "Her military bearing was rigid," | | 5 | "Detective Quinn’s partner, DS Morris," | | 6 | "Quinn hadn’t slept well since." | | 7 | "The evidence was confounding." | | 8 | "The floor was clean, no" | | 9 | "The only disturbance was a" | | 10 | "Eva Kowalski’s voice cut through" | | 11 | "Eva, Quinn’s childhood friend and" | | 12 | "She clutched a worn leather" | | 13 | "Her nervous habit was evident" | | 14 | "Quinn didn’t turn immediately." | | 15 | "She knelt, her gloved hands" | | 16 | "She rose, her gaze sweeping" | | 17 | "She pointed at the shimmering" | | 18 | "Eva frowned, her green eyes" | | 19 | "She pulled a small, intricately" |
| | ratio | 0.96 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 50 | | matches | | 0 | "Now, another disappearance." |
| | ratio | 0.02 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 16 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 7 | | matches | | 0 | "She walked, her footsteps echoing" | | 1 | "She paused, her eyes scanning the shadows" | | 2 | "Quinn countered, her voice low" | | 3 | "She walked, her gloved hand tracing the cold concrete" | | 4 | "Eva murmured, her voice tight" | | 5 | "She looked, her green eyes intense" | | 6 | "She turned, her military bearing snapping back into place" |
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| 89.39% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "Quinn breathed (breathe)" | | 1 | "Eva murmured (murmur)" |
| | dialogueSentences | 33 | | tagDensity | 0.061 | | leniency | 0.121 | | rawRatio | 1 | | effectiveRatio | 0.121 | |