| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 21 | | tagDensity | 0.238 | | leniency | 0.476 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 81.08% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 793 | | totalAiIsmAdverbs | 3 | | found | | 0 | | | 1 | | | 2 | | adverb | "barely above a whisper" | | count | 1 |
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| | highlights | | 0 | "tightly" | | 1 | "slowly" | | 2 | "barely above a whisper" |
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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) | |
| 24.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 793 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "tinged" | | 1 | "scanning" | | 2 | "furrowed" | | 3 | "etched" | | 4 | "traced" | | 5 | "racing" | | 6 | "tracing" | | 7 | "flicked" | | 8 | "pounding" | | 9 | "whisper" | | 10 | "potential" | | 11 | "raced" |
| |
| 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 | 1 | | narrationSentences | 40 | | matches | | |
| 35.71% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 40 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 56 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 792 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 25.26% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 481 | | uniqueNames | 7 | | maxNameDensity | 2.49 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 12 | | Tube | 1 | | Kowalski | 1 | | Eva | 9 | | Veil | 2 | | Market | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" |
| | places | | | globalScore | 0.253 | | windowScore | 0.333 | |
| 76.47% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 34 | | glossingSentenceCount | 1 | | matches | | 0 | "marks that seemed to form a circle" |
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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 | 792 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 56 | | matches | (empty) | |
| 90.85% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 24 | | mean | 33 | | std | 15.44 | | cv | 0.468 | | sampleLengths | | 0 | 69 | | 1 | 51 | | 2 | 22 | | 3 | 52 | | 4 | 11 | | 5 | 27 | | 6 | 14 | | 7 | 39 | | 8 | 21 | | 9 | 40 | | 10 | 17 | | 11 | 28 | | 12 | 15 | | 13 | 40 | | 14 | 23 | | 15 | 31 | | 16 | 58 | | 17 | 17 | | 18 | 41 | | 19 | 35 | | 20 | 17 | | 21 | 31 | | 22 | 37 | | 23 | 56 |
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| 87.72% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 40 | | matches | | 0 | "was made" | | 1 | "been unleashed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 81 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 56 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 481 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.035343035343035345 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.018711018711018712 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 56 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 56 | | mean | 14.14 | | std | 7.93 | | cv | 0.561 | | sampleLengths | | 0 | 22 | | 1 | 24 | | 2 | 23 | | 3 | 23 | | 4 | 19 | | 5 | 9 | | 6 | 11 | | 7 | 11 | | 8 | 7 | | 9 | 13 | | 10 | 14 | | 11 | 18 | | 12 | 11 | | 13 | 3 | | 14 | 24 | | 15 | 3 | | 16 | 11 | | 17 | 2 | | 18 | 37 | | 19 | 3 | | 20 | 18 | | 21 | 12 | | 22 | 14 | | 23 | 14 | | 24 | 8 | | 25 | 9 | | 26 | 10 | | 27 | 18 | | 28 | 6 | | 29 | 9 | | 30 | 16 | | 31 | 11 | | 32 | 13 | | 33 | 8 | | 34 | 15 | | 35 | 9 | | 36 | 22 | | 37 | 22 | | 38 | 7 | | 39 | 29 | | 40 | 11 | | 41 | 6 | | 42 | 9 | | 43 | 32 | | 44 | 8 | | 45 | 27 | | 46 | 12 | | 47 | 5 | | 48 | 3 | | 49 | 28 |
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| 60.71% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.375 | | totalSentences | 56 | | uniqueOpeners | 21 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 39 | | matches | (empty) | | ratio | 0 | |
| 76.41% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 39 | | matches | | 0 | "She adjusted her grip on" | | 1 | "She wore her usual round" | | 2 | "Her freckled complexion stood out" | | 3 | "She spotted a small, brass" | | 4 | "She bent down to pick" | | 5 | "she asked, holding it up" | | 6 | "They moved deeper into the" | | 7 | "She leaned in, her eyes" | | 8 | "she asked, pointing to the" | | 9 | "They descended the stairs to" | | 10 | "She stopped at a set" | | 11 | "she said, her voice low" | | 12 | "She approached it slowly, her" | | 13 | "She pulled out her radio," |
| | ratio | 0.359 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 38 | | totalSentences | 39 | | matches | | 0 | "Detective Harlow Quinn stood at" | | 1 | "The air was thick with" | | 2 | "She adjusted her grip on" | | 3 | "Eva Kowalski, her friend and" | | 4 | "She wore her usual round" | | 5 | "Her freckled complexion stood out" | | 6 | "Eva said, her voice tinged" | | 7 | "Quinn nodded, her eyes scanning" | | 8 | "The platform was cluttered with" | | 9 | "She spotted a small, brass" | | 10 | "She bent down to pick" | | 11 | "she asked, holding it up" | | 12 | "Eva's eyes widened." | | 13 | "Quinn's brow furrowed." | | 14 | "Quinn's gaze sharpened." | | 15 | "They moved deeper into the" | | 16 | "Quinn noticed a series of" | | 17 | "She leaned in, her eyes" | | 18 | "she asked, pointing to the" | | 19 | "Eva leaned in, her glasses" |
| | ratio | 0.974 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 39 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 1 | | matches | | 0 | "She bent down to pick it up, her fingers brushing against the patina of verdigris on its casing." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, her voice low" | | 1 | "Quinn said, her voice barely above a whisper" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 21 | | tagDensity | 0.238 | | leniency | 0.476 | | rawRatio | 0 | | effectiveRatio | 0 | |