| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 23 | | tagDensity | 0.174 | | leniency | 0.348 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.88% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 825 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 825 | | totalAiIsms | 19 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | word | "down her spine" | | count | 1 |
| | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | |
| | highlights | | 0 | "flicker" | | 1 | "grave" | | 2 | "gloom" | | 3 | "footsteps" | | 4 | "echoing" | | 5 | "weight" | | 6 | "familiar" | | 7 | "electric" | | 8 | "pulsed" | | 9 | "down her spine" | | 10 | "pulse" | | 11 | "silence" | | 12 | "could feel" | | 13 | "flicked" | | 14 | "tension" | | 15 | "unspoken" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "eyes widened" | | 1 | "the air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 82 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 82 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 100 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 22 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 4 | | totalWords | 813 | | ratio | 0.005 | | matches | | 0 | "The Raven’s Nest" | | 1 | "Private" |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 704 | | uniqueNames | 7 | | maxNameDensity | 1.85 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 13 | | Tube | 1 | | London | 1 | | Raven | 1 | | Herrera | 7 | | Saint | 1 | | Christopher | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" |
| | places | | | globalScore | 0.577 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | 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 | 813 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 100 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 26.23 | | std | 19.97 | | cv | 0.761 | | sampleLengths | | 0 | 77 | | 1 | 67 | | 2 | 32 | | 3 | 49 | | 4 | 5 | | 5 | 53 | | 6 | 64 | | 7 | 43 | | 8 | 28 | | 9 | 55 | | 10 | 27 | | 11 | 11 | | 12 | 6 | | 13 | 8 | | 14 | 11 | | 15 | 34 | | 16 | 13 | | 17 | 37 | | 18 | 14 | | 19 | 9 | | 20 | 17 | | 21 | 27 | | 22 | 14 | | 23 | 17 | | 24 | 5 | | 25 | 10 | | 26 | 20 | | 27 | 20 | | 28 | 26 | | 29 | 9 | | 30 | 5 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 82 | | matches | (empty) | |
| 93.33% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 125 | | matches | | 0 | "was running" | | 1 | "wasn’t leaving" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 100 | | ratio | 0.06 | | matches | | 0 | "The suspect—some low-level dealer, probably—had bolted into the shadows near the old Tube station entrance, his hood pulled low." | | 1 | "The air smelled wrong—wet earth, something sour, like old coins left in a grave." | | 2 | "A narrow alley opened up ahead, the walls lined with flickering lanterns—oil, not electric." | | 3 | "She’d heard whispers about places like this—underground, off the grid, where things didn’t follow the rules." | | 4 | "A man behind the bar—a gaunt figure with a scar running down his cheek—glanced up, his eyes narrowing." | | 5 | "She recognised the medallion around his neck, the one she’d seen in old photos—Saint Christopher, ironically enough." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 716 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.027932960893854747 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.006983240223463687 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 100 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 100 | | mean | 8.13 | | std | 4.57 | | cv | 0.562 | | sampleLengths | | 0 | 16 | | 1 | 15 | | 2 | 19 | | 3 | 8 | | 4 | 19 | | 5 | 9 | | 6 | 3 | | 7 | 13 | | 8 | 16 | | 9 | 14 | | 10 | 12 | | 11 | 12 | | 12 | 13 | | 13 | 4 | | 14 | 3 | | 15 | 14 | | 16 | 10 | | 17 | 17 | | 18 | 8 | | 19 | 5 | | 20 | 13 | | 21 | 3 | | 22 | 8 | | 23 | 16 | | 24 | 7 | | 25 | 6 | | 26 | 7 | | 27 | 13 | | 28 | 14 | | 29 | 16 | | 30 | 14 | | 31 | 11 | | 32 | 18 | | 33 | 8 | | 34 | 6 | | 35 | 3 | | 36 | 4 | | 37 | 13 | | 38 | 8 | | 39 | 8 | | 40 | 18 | | 41 | 10 | | 42 | 2 | | 43 | 17 | | 44 | 7 | | 45 | 7 | | 46 | 6 | | 47 | 7 | | 48 | 3 | | 49 | 5 |
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| 40.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.22 | | totalSentences | 100 | | uniqueOpeners | 22 | |
| 86.58% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 77 | | matches | | 0 | "Then she saw the sign." | | 1 | "Then he spoke, his voice" |
| | ratio | 0.026 | |
| 90.13% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 77 | | matches | | 0 | "She kept her pace steady," | | 1 | "She didn’t recognise him, but" | | 2 | "She lunged, fingers curling around" | | 3 | "Her flashlight cut through the" | | 4 | "She didn’t like this." | | 5 | "She’d heard whispers about places" | | 6 | "She was here for the" | | 7 | "he said, voice smooth as" | | 8 | "She didn’t answer." | | 9 | "She didn’t have time." | | 10 | "She recognised the medallion around" | | 11 | "He turned just as she" | | 12 | "His dark eyes locked onto" | | 13 | "he said, voice calm" | | 14 | "She didn’t move." | | 15 | "She knew better than to" | | 16 | "She carried a knife, its" | | 17 | "she said, voice low" | | 18 | "She kept her eyes on" | | 19 | "She could feel the weight" |
| | ratio | 0.325 | |
| 11.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 77 | | matches | | 0 | "The rain hammered down in" | | 1 | "She kept her pace steady," | | 2 | "The suspect—some low-level dealer, probably—had" | | 3 | "She didn’t recognise him, but" | | 4 | "The scent of damp concrete" | | 5 | "A flicker of movement near" | | 6 | "Quinn didn’t hesitate." | | 7 | "She lunged, fingers curling around" | | 8 | "The moment her boots hit" | | 9 | "The air smelled wrong—wet earth," | | 10 | "Her flashlight cut through the" | | 11 | "The suspect was already moving," | | 12 | "Quinn adjusted her grip on" | | 13 | "She didn’t like this." | | 14 | "A narrow alley opened up" | | 15 | "The kind of place that" | | 16 | "The suspect ducked into a" | | 17 | "Quinn followed, her breath steady" | | 18 | "A jagged green neon glow" | | 19 | "*The Raven’s Nest*." |
| | ratio | 0.896 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 77 | | matches | (empty) | | ratio | 0 | |
| 96.77% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 2 | | matches | | 0 | "The suspect was already moving, his footsteps echoing off the damp walls." | | 1 | "A man behind the bar—a gaunt figure with a scar running down his cheek—glanced up, his eyes narrowing." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 3 | | matches | | 0 | "he said, voice smooth as oil" | | 1 | "he said, voice calm" | | 2 | "she said, voice low" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 23 | | tagDensity | 0.174 | | leniency | 0.348 | | rawRatio | 0 | | effectiveRatio | 0 | |