| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 79 | | tagDensity | 0.013 | | leniency | 0.025 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.33% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1876 | | totalAiIsmAdverbs | 1 | | 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) | |
| 78.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1876 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "trembled" | | 1 | "pulse" | | 2 | "weight" | | 3 | "etched" | | 4 | "magnetic" | | 5 | "churned" | | 6 | "stomach" | | 7 | "lurched" |
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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 | 164 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 164 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 242 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 68 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1876 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 1342 | | uniqueNames | 5 | | maxNameDensity | 1.94 | | worstName | "Bell" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Bell" | | discoveredNames | | Keir | 1 | | Bell | 26 | | Quinn | 16 | | English | 1 | | Dust | 3 |
| | persons | | 0 | "Keir" | | 1 | "Bell" | | 2 | "Quinn" | | 3 | "Dust" |
| | places | (empty) | | globalScore | 0.531 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 90 | | 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 | 1876 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 242 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 147 | | mean | 12.76 | | std | 17.94 | | cv | 1.405 | | sampleLengths | | 0 | 4 | | 1 | 43 | | 2 | 5 | | 3 | 10 | | 4 | 90 | | 5 | 19 | | 6 | 12 | | 7 | 44 | | 8 | 42 | | 9 | 4 | | 10 | 5 | | 11 | 3 | | 12 | 9 | | 13 | 86 | | 14 | 4 | | 15 | 4 | | 16 | 2 | | 17 | 5 | | 18 | 7 | | 19 | 29 | | 20 | 80 | | 21 | 3 | | 22 | 30 | | 23 | 3 | | 24 | 1 | | 25 | 5 | | 26 | 4 | | 27 | 1 | | 28 | 5 | | 29 | 4 | | 30 | 5 | | 31 | 29 | | 32 | 11 | | 33 | 38 | | 34 | 5 | | 35 | 14 | | 36 | 5 | | 37 | 11 | | 38 | 7 | | 39 | 5 | | 40 | 11 | | 41 | 11 | | 42 | 3 | | 43 | 4 | | 44 | 2 | | 45 | 10 | | 46 | 40 | | 47 | 4 | | 48 | 7 | | 49 | 12 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 164 | | matches | | 0 | "been etched" | | 1 | "been churned" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 221 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 242 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1345 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 46 | | adverbRatio | 0.03420074349442379 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0037174721189591076 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 242 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 242 | | mean | 7.75 | | std | 7.79 | | cv | 1.004 | | sampleLengths | | 0 | 4 | | 1 | 20 | | 2 | 14 | | 3 | 9 | | 4 | 5 | | 5 | 10 | | 6 | 7 | | 7 | 3 | | 8 | 14 | | 9 | 19 | | 10 | 32 | | 11 | 5 | | 12 | 10 | | 13 | 10 | | 14 | 9 | | 15 | 12 | | 16 | 44 | | 17 | 4 | | 18 | 5 | | 19 | 5 | | 20 | 12 | | 21 | 2 | | 22 | 2 | | 23 | 12 | | 24 | 4 | | 25 | 5 | | 26 | 3 | | 27 | 9 | | 28 | 9 | | 29 | 4 | | 30 | 2 | | 31 | 5 | | 32 | 11 | | 33 | 9 | | 34 | 15 | | 35 | 3 | | 36 | 6 | | 37 | 22 | | 38 | 4 | | 39 | 4 | | 40 | 2 | | 41 | 5 | | 42 | 7 | | 43 | 8 | | 44 | 21 | | 45 | 2 | | 46 | 22 | | 47 | 11 | | 48 | 14 | | 49 | 10 |
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| 63.50% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.40082644628099173 | | totalSentences | 242 | | uniqueOpeners | 97 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 136 | | matches | | 0 | "Only they were not chalk." | | 1 | "Then, at the lower corner," | | 2 | "Then she saw it, a" | | 3 | "Then a faint, regular knock" | | 4 | "Then the thing behind her" |
| | ratio | 0.037 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 136 | | matches | | 0 | "Her knees clicked." | | 1 | "She studied the compass first." | | 2 | "She took in the dead" | | 3 | "He shifted his weight and" | | 4 | "Her worn leather watch pressed" | | 5 | "She crossed to the nearest" | | 6 | "He gave a short laugh." | | 7 | "He walked over and looked" | | 8 | "She touched the shoulder seam" | | 9 | "She stepped over the body" | | 10 | "She did, ticking them off" | | 11 | "She lowered the last finger." | | 12 | "He stared at her, then" | | 13 | "She ignored that and nodded" | | 14 | "She looked up." | | 15 | "She ran her hand along" | | 16 | "She shone it at the" | | 17 | "His flippancy cracked." | | 18 | "He stepped closer." | | 19 | "She pressed the frame." |
| | ratio | 0.199 | |
| 62.94% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 108 | | totalSentences | 136 | | matches | | 0 | "Quinn caught the scenes of" | | 1 | "The woman blinked behind her" | | 2 | "Bell only lifted both hands," | | 3 | "Quinn crouched on the cracked" | | 4 | "Her knees clicked." | | 5 | "The dead man lay on" | | 6 | "Blood had soaked his collar" | | 7 | "A fourth had toppled and" | | 8 | "Someone had worked hard to" | | 9 | "Bell nudged a spent torch" | | 10 | "Quinn didn’t look up." | | 11 | "She studied the compass first." | | 12 | "Verdigris crusted the brass casing." | | 13 | "Fine marks, almost letters, crawled" | | 14 | "The needle trembled as if" | | 15 | "She took in the dead" | | 16 | "Thirtys, perhaps early forties." | | 17 | "A silver ring sat on" | | 18 | "Bell folded his arms." | | 19 | "That dragged her eyes up" |
| | ratio | 0.794 | |
| 36.76% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 136 | | matches | | 0 | "Whoever drew them had a" |
| | ratio | 0.007 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 56 | | technicalSentenceCount | 3 | | matches | | 0 | "The needle swung hard to the left, away from the rails, away from the station entrance, and steadied on the tiled wall behind an old advertisement board for a t…" | | 1 | "The bottom edge showed a clean scrape, recent and narrow, as if the board had shifted." | | 2 | "A narrow passage opened beyond, brick-lined and lit by a string of bare bulbs that should not have had power." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 79 | | tagDensity | 0.013 | | leniency | 0.025 | | rawRatio | 1 | | effectiveRatio | 0.025 | |