| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 45 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1358 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 74.23% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1358 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "familiar" | | 1 | "flicked" | | 2 | "weight" | | 3 | "etched" | | 4 | "trembled" | | 5 | "fluttered" | | 6 | "pulse" |
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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 | 93 | | matches | (empty) | |
| 81.41% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 1 | | narrationSentences | 93 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 123 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1358 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 850 | | uniqueNames | 9 | | maxNameDensity | 1.76 | | worstName | "Eva" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Eva" | | discoveredNames | | Quinn | 14 | | Kowalski | 1 | | Eva | 15 | | Books | 1 | | Market | 2 | | Veil | 2 | | Compass | 1 | | Shade | 1 | | Morris | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Kowalski" | | 2 | "Eva" | | 3 | "Books" | | 4 | "Market" | | 5 | "Compass" | | 6 | "Morris" |
| | places | (empty) | | globalScore | 0.618 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.736 | | wordCount | 1358 | | matches | | 0 | "not at the dead man but at the tiled wall behind the lockers, a blank stretch of whi" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 123 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 67 | | mean | 20.27 | | std | 16.28 | | cv | 0.803 | | sampleLengths | | 0 | 3 | | 1 | 12 | | 2 | 62 | | 3 | 32 | | 4 | 10 | | 5 | 2 | | 6 | 19 | | 7 | 31 | | 8 | 9 | | 9 | 19 | | 10 | 29 | | 11 | 4 | | 12 | 23 | | 13 | 3 | | 14 | 7 | | 15 | 11 | | 16 | 6 | | 17 | 18 | | 18 | 8 | | 19 | 59 | | 20 | 7 | | 21 | 23 | | 22 | 9 | | 23 | 50 | | 24 | 6 | | 25 | 31 | | 26 | 33 | | 27 | 38 | | 28 | 6 | | 29 | 4 | | 30 | 7 | | 31 | 14 | | 32 | 9 | | 33 | 23 | | 34 | 24 | | 35 | 18 | | 36 | 53 | | 37 | 25 | | 38 | 7 | | 39 | 11 | | 40 | 44 | | 41 | 13 | | 42 | 5 | | 43 | 61 | | 44 | 3 | | 45 | 20 | | 46 | 11 | | 47 | 34 | | 48 | 24 | | 49 | 14 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 93 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 146 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 123 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 853 | | adjectiveStacks | 1 | | stackExamples | | 0 | "cold white light split" |
| | adverbCount | 19 | | adverbRatio | 0.022274325908558032 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0035169988276670576 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 123 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 123 | | mean | 11.04 | | std | 7.45 | | cv | 0.675 | | sampleLengths | | 0 | 3 | | 1 | 12 | | 2 | 19 | | 3 | 16 | | 4 | 27 | | 5 | 20 | | 6 | 7 | | 7 | 5 | | 8 | 10 | | 9 | 2 | | 10 | 19 | | 11 | 2 | | 12 | 4 | | 13 | 3 | | 14 | 9 | | 15 | 13 | | 16 | 9 | | 17 | 19 | | 18 | 4 | | 19 | 12 | | 20 | 2 | | 21 | 4 | | 22 | 7 | | 23 | 4 | | 24 | 9 | | 25 | 14 | | 26 | 3 | | 27 | 7 | | 28 | 11 | | 29 | 6 | | 30 | 10 | | 31 | 8 | | 32 | 8 | | 33 | 15 | | 34 | 30 | | 35 | 14 | | 36 | 7 | | 37 | 23 | | 38 | 9 | | 39 | 14 | | 40 | 4 | | 41 | 32 | | 42 | 6 | | 43 | 31 | | 44 | 14 | | 45 | 19 | | 46 | 12 | | 47 | 10 | | 48 | 16 | | 49 | 6 |
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| 56.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.4065040650406504 | | totalSentences | 123 | | uniqueOpeners | 50 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 80 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 80 | | matches | | 0 | "Her closely cropped salt-and-pepper hair" | | 1 | "His throat showed a clean," | | 2 | "She did not touch." | | 3 | "She breathed in." | | 4 | "Her curly red hair had" | | 5 | "She tucked a strand of" | | 6 | "She pointed with a gloved" | | 7 | "Its face bore protective sigils" | | 8 | "It pointed not at the" | | 9 | "Her watch ticked loud in" | | 10 | "She ran her hand near" | | 11 | "She had not looked away" | | 12 | "She indicated the floor again." | | 13 | "Her hand shook." | | 14 | "She pressed the compass flat" | | 15 | "Her voice stayed level, military" |
| | ratio | 0.2 | |
| 35.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 80 | | matches | | 0 | "The command cracked across the" | | 1 | "Harlow Quinn stood over the" | | 2 | "Her closely cropped salt-and-pepper hair" | | 3 | "The dead man lay flat" | | 4 | "His throat showed a clean," | | 5 | "the younger constable said" | | 6 | "She did not touch." | | 7 | "She breathed in." | | 8 | "Copper stung her nostrils, but" | | 9 | "The air smelled of ozone" | | 10 | "Quinn tilted her head." | | 11 | "The stall edge near the" | | 12 | "The man's collar stayed crisp" | | 13 | "The constable lifted the evidence" | | 14 | "Quinn's jaw tightened." | | 15 | "A soft scuff sounded behind" | | 16 | "A familiar voice spoke, breathless" | | 17 | "Eva Kowalski pushed past the" | | 18 | "Her curly red hair had" | | 19 | "She tucked a strand of" |
| | ratio | 0.85 | |
| 62.50% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 80 | | matches | | 0 | "Now Quinn saw the faint" |
| | ratio | 0.013 | |
| 81.63% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 3 | | matches | | 0 | "Eva unbuckled her satchel and lifted something that caught the low amber light of the Market's strung bulbs." | | 1 | "The Shade artisan who crafted it had left tool marks on the back, tiny hammer points." | | 2 | "The needle spun, fast, then faster, a tick-tock blur that buzzed against the glass." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 1 | | fancyTags | | 0 | "Eva whispered (whisper)" |
| | dialogueSentences | 45 | | tagDensity | 0.244 | | leniency | 0.489 | | rawRatio | 0.091 | | effectiveRatio | 0.044 | |