| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 1 | | adverbTags | | 0 | "The officer stepped back [back]" |
| | dialogueSentences | 42 | | tagDensity | 0.095 | | leniency | 0.19 | | rawRatio | 0.25 | | effectiveRatio | 0.048 | |
| 82.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1164 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | | 2 | | adverb | "reluctantly" | | count | 1 |
| | 3 | |
| | highlights | | 0 | "sharply" | | 1 | "lightly" | | 2 | "reluctantly" | | 3 | "softly" |
| |
| 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) | |
| 35.57% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1164 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "echoed" | | 1 | "vibrated" | | 2 | "etched" | | 3 | "intricate" | | 4 | "furrowed" | | 5 | "measured" | | 6 | "footsteps" | | 7 | "glinting" | | 8 | "scanning" | | 9 | "raced" | | 10 | "whisper" |
| |
| 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 | "clenched jaw/fists" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "clenched her jaw" |
| |
| 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 | 1 | | hedgeCount | 0 | | narrationSentences | 78 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 115 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1162 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 41.55% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 876 | | uniqueNames | 5 | | maxNameDensity | 2.17 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 19 | | Veil | 2 | | Market | 2 |
| | persons | | | places | (empty) | | globalScore | 0.416 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | 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 | 1162 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 115 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 18.74 | | std | 14.89 | | cv | 0.795 | | sampleLengths | | 0 | 76 | | 1 | 34 | | 2 | 23 | | 3 | 3 | | 4 | 34 | | 5 | 14 | | 6 | 13 | | 7 | 43 | | 8 | 17 | | 9 | 4 | | 10 | 33 | | 11 | 25 | | 12 | 29 | | 13 | 13 | | 14 | 31 | | 15 | 3 | | 16 | 9 | | 17 | 34 | | 18 | 10 | | 19 | 6 | | 20 | 33 | | 21 | 4 | | 22 | 8 | | 23 | 2 | | 24 | 38 | | 25 | 33 | | 26 | 14 | | 27 | 25 | | 28 | 57 | | 29 | 3 | | 30 | 23 | | 31 | 20 | | 32 | 17 | | 33 | 29 | | 34 | 3 | | 35 | 10 | | 36 | 20 | | 37 | 13 | | 38 | 8 | | 39 | 14 | | 40 | 23 | | 41 | 4 | | 42 | 26 | | 43 | 3 | | 44 | 11 | | 45 | 24 | | 46 | 7 | | 47 | 14 | | 48 | 29 | | 49 | 5 |
| |
| 82.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 78 | | matches | | 0 | "was etched" | | 1 | "were rumpled" | | 2 | "were cracked" | | 3 | "were tangled" | | 4 | "been disturbed" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 151 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 115 | | ratio | 0.009 | | matches | | 0 | "She pulled it out—a bone token, its surface etched with the same sigils as the compass." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 877 | | adjectiveStacks | 1 | | stackExamples | | 0 | "cold pressed against her" |
| | adverbCount | 34 | | adverbRatio | 0.03876852907639681 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.01596351197263398 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 115 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 115 | | mean | 10.1 | | std | 5.49 | | cv | 0.543 | | sampleLengths | | 0 | 20 | | 1 | 15 | | 2 | 21 | | 3 | 20 | | 4 | 14 | | 5 | 20 | | 6 | 10 | | 7 | 13 | | 8 | 3 | | 9 | 23 | | 10 | 11 | | 11 | 11 | | 12 | 3 | | 13 | 13 | | 14 | 12 | | 15 | 17 | | 16 | 14 | | 17 | 13 | | 18 | 4 | | 19 | 4 | | 20 | 9 | | 21 | 24 | | 22 | 16 | | 23 | 9 | | 24 | 5 | | 25 | 8 | | 26 | 16 | | 27 | 6 | | 28 | 7 | | 29 | 7 | | 30 | 13 | | 31 | 11 | | 32 | 3 | | 33 | 9 | | 34 | 8 | | 35 | 26 | | 36 | 6 | | 37 | 4 | | 38 | 6 | | 39 | 3 | | 40 | 9 | | 41 | 10 | | 42 | 11 | | 43 | 4 | | 44 | 3 | | 45 | 5 | | 46 | 2 | | 47 | 14 | | 48 | 14 | | 49 | 10 |
| |
| 46.38% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.30434782608695654 | | totalSentences | 115 | | uniqueOpeners | 35 | |
| 43.86% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 76 | | matches | | 0 | "Instead, she turned the compass" |
| | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 76 | | matches | | 0 | "Her shoes echoed sharply against" | | 1 | "He gestured toward the far" | | 2 | "She nodded, her stride purposeful," | | 3 | "He handed her a small" | | 4 | "Her brows furrowed as she" | | 5 | "His clothes were rumpled, but" | | 6 | "She crouched beside the body," | | 7 | "She stood, brushing her hands" | | 8 | "She glanced back at the" | | 9 | "She reached out, her fingers" | | 10 | "She pressed harder, and a" | | 11 | "He nodded reluctantly, pulling a" | | 12 | "She stepped through the gap," | | 13 | "She moved forward, her footsteps" | | 14 | "She’d heard rumors, whispers of" | | 15 | "It all connected, but the" | | 16 | "She turned and retraced her" | | 17 | "It was already closing, the" | | 18 | "She pulled it out—a bone" | | 19 | "Her jaw tightened." |
| | ratio | 0.263 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 72 | | totalSentences | 76 | | matches | | 0 | "The air in the abandoned" | | 1 | "Detective Harlow Quinn adjusted her" | | 2 | "Her shoes echoed sharply against" | | 3 | "The flickering lights overhead cast" | | 4 | "A uniformed officer stood at" | | 5 | "He gestured toward the far" | | 6 | "She nodded, her stride purposeful," | | 7 | "The officer fell in beside" | | 8 | "He handed her a small" | | 9 | "The face was etched with" | | 10 | "Her brows furrowed as she" | | 11 | "The detectives reached the scene," | | 12 | "The body lay sprawled on" | | 13 | "His clothes were rumpled, but" | | 14 | "She crouched beside the body," | | 15 | "Quinn’s gaze swept the platform," | | 16 | "The station was eerily quiet," | | 17 | "another officer said, crouching on" | | 18 | "Quinn’s voice was firm" | | 19 | "She stood, brushing her hands" |
| | ratio | 0.947 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 76 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 2 | | matches | | 0 | "Enchanted objects, jars of swirling liquids, and ancient tomes filled the spaces, their vendors watching her with curious eyes." | | 1 | "The vendors watched her with unblinking gazes, their wares shifting and pulsating with unseen energy." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 3 | | matches | | 0 | "officer stood, his voice clipped" | | 1 | "He handed, its casing weathered with verdigris" | | 2 | "The officer stepped back, his hand instinctively reaching for his baton" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 42 | | tagDensity | 0.024 | | leniency | 0.048 | | rawRatio | 0 | | effectiveRatio | 0 | |