| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.571 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1223 | | 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) | |
| 75.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1223 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "tinged" | | 1 | "echoing" | | 2 | "etched" | | 3 | "flickered" | | 4 | "scanned" |
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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 | 37 | | matches | (empty) | |
| 65.64% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 37 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 43 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 69 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1223 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 79.96% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 928 | | uniqueNames | 16 | | maxNameDensity | 1.4 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Harlow" | | discoveredNames | | Morris | 4 | | Regent | 1 | | Canal | 1 | | Harlow | 13 | | Kowalski | 1 | | British | 1 | | Museum | 1 | | Jars | 1 | | Veil | 1 | | Market | 1 | | Charing | 1 | | Cross | 1 | | Camden | 1 | | Town | 1 | | Eva | 6 | | Lila | 2 |
| | persons | | 0 | "Morris" | | 1 | "Regent" | | 2 | "Harlow" | | 3 | "Kowalski" | | 4 | "Museum" | | 5 | "Market" | | 6 | "Eva" | | 7 | "Lila" |
| | places | | | globalScore | 0.8 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 35 | | 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 | 1223 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 43 | | matches | (empty) | |
| 47.84% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 7 | | mean | 174.71 | | std | 55.46 | | cv | 0.317 | | sampleLengths | | 0 | 144 | | 1 | 114 | | 2 | 160 | | 3 | 127 | | 4 | 268 | | 5 | 249 | | 6 | 161 |
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| 76.81% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 37 | | matches | | 0 | "was slumped" | | 1 | "was crusted" | | 2 | "been stored" | | 3 | "was dumped" | | 4 | "been dropped" | | 5 | "been disintegrated" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 149 | | matches | | 0 | "wasn’t opening" | | 1 | "was opening" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 933 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 12 | | adverbRatio | 0.012861736334405145 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0021436227224008574 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 43 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 43 | | mean | 28.44 | | std | 15.1 | | cv | 0.531 | | sampleLengths | | 0 | 32 | | 1 | 54 | | 2 | 20 | | 3 | 38 | | 4 | 30 | | 5 | 45 | | 6 | 39 | | 7 | 8 | | 8 | 31 | | 9 | 30 | | 10 | 43 | | 11 | 27 | | 12 | 21 | | 13 | 22 | | 14 | 6 | | 15 | 43 | | 16 | 23 | | 17 | 33 | | 18 | 11 | | 19 | 38 | | 20 | 37 | | 21 | 4 | | 22 | 11 | | 23 | 25 | | 24 | 21 | | 25 | 56 | | 26 | 65 | | 27 | 33 | | 28 | 29 | | 29 | 19 | | 30 | 20 | | 31 | 29 | | 32 | 8 | | 33 | 22 | | 34 | 69 | | 35 | 20 | | 36 | 22 | | 37 | 22 | | 38 | 43 | | 39 | 27 | | 40 | 32 | | 41 | 8 | | 42 | 7 |
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| 51.94% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.3953488372093023 | | totalSentences | 43 | | uniqueOpeners | 17 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 35 | | matches | (empty) | | ratio | 0 | |
| 82.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 35 | | matches | | 0 | "Her worn leather watch, strapped" | | 1 | "She’d chased this hidden market" | | 2 | "Her worn leather satchel bulged" | | 3 | "She stopped a foot away" | | 4 | "She ran a nail along" | | 5 | "She held the compass up," | | 6 | "She’d written them off as" | | 7 | "She’d missed that, written off" | | 8 | "She pulled a crumpled photo" | | 9 | "she said, tapping the compass’s" | | 10 | "She looked down at the" | | 11 | "It was opening right under" |
| | ratio | 0.343 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 35 | | totalSentences | 35 | | matches | | 0 | "Harlow ducked under the frayed" | | 1 | "Her worn leather watch, strapped" | | 2 | "The space reeked of mildew," | | 3 | "She’d chased this hidden market" | | 4 | "A figure shifted in the" | | 5 | "Eva Kowalski leaned against the" | | 6 | "Her worn leather satchel bulged" | | 7 | "Harlow released her grip on" | | 8 | "Jars of glowing silver mist" | | 9 | "The market had set up" | | 10 | "Harlow had beat the move" | | 11 | "The body was slumped against" | | 12 | "Harlow said, nodding toward the" | | 13 | "Eva pushed off the wall" | | 14 | "She stopped a foot away" | | 15 | "Harlow leaned down and pried" | | 16 | "The brass casing was crusted" | | 17 | "The compass’s needle spun wild," | | 18 | "Eva snorted and reached out" | | 19 | "She ran a nail along" |
| | ratio | 1 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 35 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 1 | | matches | | 0 | "Harlow ducked under the frayed blue crime scene tape she’d strung an hour earlier, her scuffed leather boots catching on a loose strip of rusted track that jutt…" |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "Eva pushed, her boots echoing off the concrete" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0 | | effectiveRatio | 0 | |