| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 68 | | tagDensity | 0.309 | | leniency | 0.618 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.61% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1854 | | 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) | |
| 86.52% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1854 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "weight" | | 1 | "etched" | | 2 | "magnetic" | | 3 | "aligned" |
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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 | 144 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 144 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 190 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1854 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 25 | | unquotedAttributions | 1 | | matches | | 0 | "Military precision, Bell called it when he meant that she was being difficult." |
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| 61.50% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 58 | | wordCount | 1243 | | uniqueNames | 11 | | maxNameDensity | 1.77 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 2 | | Quinn | 22 | | Camden | 1 | | Underground | 1 | | Veil | 1 | | Market | 1 | | Bell | 20 | | Sergeant | 1 | | Eva | 6 | | Morris | 1 | | Vale | 2 |
| | persons | | 0 | "Detective" | | 1 | "Quinn" | | 2 | "Underground" | | 3 | "Market" | | 4 | "Bell" | | 5 | "Sergeant" | | 6 | "Eva" | | 7 | "Morris" | | 8 | "Vale" |
| | places | (empty) | | globalScore | 0.615 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 93 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1854 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 190 | | matches | | 0 | "polished that morning" | | 1 | "meant that she" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 86 | | mean | 21.56 | | std | 18.13 | | cv | 0.841 | | sampleLengths | | 0 | 14 | | 1 | 95 | | 2 | 12 | | 3 | 42 | | 4 | 10 | | 5 | 66 | | 6 | 38 | | 7 | 3 | | 8 | 19 | | 9 | 60 | | 10 | 6 | | 11 | 31 | | 12 | 1 | | 13 | 36 | | 14 | 14 | | 15 | 20 | | 16 | 6 | | 17 | 2 | | 18 | 24 | | 19 | 37 | | 20 | 32 | | 21 | 4 | | 22 | 7 | | 23 | 3 | | 24 | 17 | | 25 | 52 | | 26 | 4 | | 27 | 3 | | 28 | 1 | | 29 | 39 | | 30 | 10 | | 31 | 46 | | 32 | 29 | | 33 | 9 | | 34 | 16 | | 35 | 7 | | 36 | 34 | | 37 | 11 | | 38 | 19 | | 39 | 52 | | 40 | 13 | | 41 | 9 | | 42 | 4 | | 43 | 62 | | 44 | 47 | | 45 | 12 | | 46 | 16 | | 47 | 9 | | 48 | 2 | | 49 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 144 | | matches | | 0 | "was curled" | | 1 | "been etched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 208 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 190 | | ratio | 0.005 | | matches | | 0 | "A plain, old-fashioned fixture; the sort used when a lock was too dear or too likely to jam." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1246 | | adjectiveStacks | 1 | | stackExamples | | 0 | "plain, old-fashioned fixture;" |
| | adverbCount | 23 | | adverbRatio | 0.018459069020866775 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.004815409309791332 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 190 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 190 | | mean | 9.76 | | std | 6.33 | | cv | 0.649 | | sampleLengths | | 0 | 14 | | 1 | 28 | | 2 | 13 | | 3 | 19 | | 4 | 8 | | 5 | 11 | | 6 | 16 | | 7 | 12 | | 8 | 4 | | 9 | 14 | | 10 | 1 | | 11 | 10 | | 12 | 13 | | 13 | 10 | | 14 | 14 | | 15 | 13 | | 16 | 15 | | 17 | 9 | | 18 | 15 | | 19 | 6 | | 20 | 12 | | 21 | 20 | | 22 | 3 | | 23 | 15 | | 24 | 4 | | 25 | 4 | | 26 | 14 | | 27 | 7 | | 28 | 14 | | 29 | 10 | | 30 | 11 | | 31 | 6 | | 32 | 31 | | 33 | 1 | | 34 | 11 | | 35 | 25 | | 36 | 6 | | 37 | 8 | | 38 | 3 | | 39 | 17 | | 40 | 6 | | 41 | 2 | | 42 | 9 | | 43 | 12 | | 44 | 3 | | 45 | 2 | | 46 | 14 | | 47 | 6 | | 48 | 15 | | 49 | 11 |
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| 54.50% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3492063492063492 | | totalSentences | 189 | | uniqueOpeners | 66 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 120 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 120 | | matches | | 0 | "Her worn leather watch pressed" | | 1 | "Her steps found the dry" | | 2 | "His face had settled into" | | 3 | "He stood beside the open" | | 4 | "He had been on enough" | | 5 | "He stopped moving." | | 6 | "Its handle was dark wood," | | 7 | "It was no wider than" | | 8 | "She studied the knife again." | | 9 | "She pushed a curl behind" | | 10 | "She stood and looked at" | | 11 | "It sat in its receiver," | | 12 | "She leaned closer." | | 13 | "She waited for each image" | | 14 | "She lowered herself to one" | | 15 | "She pulled the probe back." | | 16 | "She remembered the needle pointing" | | 17 | "It had not wandered." | | 18 | "She leaned over the compass," | | 19 | "It did not feel like" |
| | ratio | 0.192 | |
| 30.83% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 103 | | totalSentences | 120 | | matches | | 0 | "The bone token was warm" | | 1 | "The air changed halfway down:" | | 2 | "A woman sold glass jars" | | 3 | "A man in a silver" | | 4 | "Tonight, the market had gone" | | 5 | "Quinn ducked beneath it." | | 6 | "Her worn leather watch pressed" | | 7 | "Her steps found the dry" | | 8 | "Military precision, Bell called it" | | 9 | "The dead man lay inside" | | 10 | "Someone had pushed the desk" | | 11 | "The body sat on the" | | 12 | "A narrow puncture marked the" | | 13 | "His face had settled into" | | 14 | "He stood beside the open" | | 15 | "Bell lowered his voice" | | 16 | "Quinn looked past him." | | 17 | "The market would move again" | | 18 | "Bell nodded toward the body" | | 19 | "Quinn gave him a level" |
| | ratio | 0.858 | |
| 83.33% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 120 | | matches | | 0 | "Now the cloth hung crooked," | | 1 | "Whoever had staged the locked" |
| | ratio | 0.017 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 1 | | matches | | 0 | "Behind the abandoned ticket hall, the stairs dropped beneath Camden in a tight turn, past flaking Underground tiles and a sign for a line that had never run." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 17 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 68 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |