| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 29 | | adverbTagCount | 2 | | adverbTags | | 0 | "Rory turned away [away]" | | 1 | "Lucien said softly [softly]" |
| | dialogueSentences | 67 | | tagDensity | 0.433 | | leniency | 0.866 | | rawRatio | 0.069 | | effectiveRatio | 0.06 | |
| 94.10% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1695 | | 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) | |
| 52.80% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1695 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "vibrated" | | 1 | "traced" | | 2 | "effortless" | | 3 | "weight" | | 4 | "navigated" | | 5 | "chaotic" | | 6 | "silence" | | 7 | "familiar" | | 8 | "dancing" | | 9 | "could feel" | | 10 | "intensity" | | 11 | "normalcy" | | 12 | "tension" | | 13 | "tracing" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "hung in the air" | | count | 1 |
| | 1 | | label | "sent a shiver through" | | count | 1 |
|
| | highlights | | 0 | "hung in the air" | | 1 | "sent a jolt through" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 92 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 92 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 130 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1687 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 73.44% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 1045 | | uniqueNames | 10 | | maxNameDensity | 1.53 | | worstName | "Lucien" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Chinese | 1 | | Ptolemy | 3 | | Moreau | 1 | | London | 2 | | Lucien | 16 | | Rory | 14 | | Golden | 1 | | Empress | 1 | | Eva | 1 | | French | 1 |
| | persons | | 0 | "Ptolemy" | | 1 | "Moreau" | | 2 | "Lucien" | | 3 | "Rory" | | 4 | "Eva" |
| | places | | 0 | "Chinese" | | 1 | "London" | | 2 | "Golden" |
| | globalScore | 0.734 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 75 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like a held breath, waiting to be" |
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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 | 1687 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 130 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 55 | | mean | 30.67 | | std | 18.56 | | cv | 0.605 | | sampleLengths | | 0 | 48 | | 1 | 71 | | 2 | 19 | | 3 | 40 | | 4 | 10 | | 5 | 62 | | 6 | 28 | | 7 | 39 | | 8 | 71 | | 9 | 35 | | 10 | 50 | | 11 | 21 | | 12 | 45 | | 13 | 31 | | 14 | 33 | | 15 | 54 | | 16 | 4 | | 17 | 4 | | 18 | 46 | | 19 | 6 | | 20 | 2 | | 21 | 33 | | 22 | 3 | | 23 | 35 | | 24 | 30 | | 25 | 22 | | 26 | 44 | | 27 | 3 | | 28 | 4 | | 29 | 43 | | 30 | 28 | | 31 | 26 | | 32 | 29 | | 33 | 59 | | 34 | 34 | | 35 | 8 | | 36 | 23 | | 37 | 39 | | 38 | 3 | | 39 | 66 | | 40 | 23 | | 41 | 43 | | 42 | 17 | | 43 | 51 | | 44 | 32 | | 45 | 14 | | 46 | 28 | | 47 | 34 | | 48 | 2 | | 49 | 27 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 92 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 181 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 130 | | ratio | 0.008 | | matches | | 0 | "He turned, those mismatched eyes—one amber, one void-black—locking onto hers." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1051 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.022835394862036156 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005708848715509039 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 130 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 130 | | mean | 12.98 | | std | 7.92 | | cv | 0.61 | | sampleLengths | | 0 | 15 | | 1 | 33 | | 2 | 20 | | 3 | 19 | | 4 | 18 | | 5 | 14 | | 6 | 6 | | 7 | 13 | | 8 | 7 | | 9 | 4 | | 10 | 5 | | 11 | 24 | | 12 | 5 | | 13 | 5 | | 14 | 5 | | 15 | 21 | | 16 | 19 | | 17 | 17 | | 18 | 15 | | 19 | 10 | | 20 | 3 | | 21 | 17 | | 22 | 3 | | 23 | 13 | | 24 | 6 | | 25 | 38 | | 26 | 20 | | 27 | 13 | | 28 | 23 | | 29 | 12 | | 30 | 20 | | 31 | 5 | | 32 | 19 | | 33 | 6 | | 34 | 21 | | 35 | 16 | | 36 | 10 | | 37 | 19 | | 38 | 6 | | 39 | 25 | | 40 | 16 | | 41 | 17 | | 42 | 25 | | 43 | 29 | | 44 | 4 | | 45 | 4 | | 46 | 10 | | 47 | 20 | | 48 | 10 | | 49 | 6 |
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| 41.54% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.2846153846153846 | | totalSentences | 130 | | uniqueOpeners | 37 | |
| 38.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 86 | | matches | | | ratio | 0.012 | |
| 43.26% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 86 | | matches | | 0 | "His charcoal suit absorbed the" | | 1 | "He leaned on his ivory-handled" | | 2 | "His voice lacked its usual" | | 3 | "She didn't step back." | | 4 | "She didn't invite him in." | | 5 | "He pushed past her anyway." | | 6 | "He stepped into the cramped" | | 7 | "He turned, those mismatched eyes—one" | | 8 | "She left the third off," | | 9 | "He stopped in the center" | | 10 | "He didn't take it off." | | 11 | "He just stood there, radiating" | | 12 | "He took a step toward" | | 13 | "He reached out, his long" | | 14 | "She flinched but didn't pull" | | 15 | "He caught her wrist, his" | | 16 | "He released her wrist but" | | 17 | "His presence filled the room," | | 18 | "Her hands shook as she" | | 19 | "She could feel the heat" |
| | ratio | 0.442 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 86 | | matches | | 0 | "The third deadbolt clacked open," | | 1 | "Rory yanked the door inward," | | 2 | "Lucien Moreau stood on the" | | 3 | "His charcoal suit absorbed the" | | 4 | "Water traced paths through his" | | 5 | "He leaned on his ivory-handled" | | 6 | "His voice lacked its usual" | | 7 | "Rory gripped the doorframe, her" | | 8 | "She didn't step back." | | 9 | "She didn't invite him in." | | 10 | "The smell of curry from" | | 11 | "He pushed past her anyway." | | 12 | "The movement was fluid, effortless," | | 13 | "He stepped into the cramped" | | 14 | "Ptolemy, the tabby cat, hissed" | | 15 | "Lucien observed, tapping his cane" | | 16 | "He turned, those mismatched eyes—one" | | 17 | "Rory slammed the door shut" | | 18 | "She left the third off," | | 19 | "Lucien navigated the obstacle course" |
| | ratio | 0.977 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 4 | | matches | | 0 | "The third deadbolt clacked open, a heavy metallic thunk that vibrated through the thin floorboards." | | 1 | "Rory yanked the door inward, expecting the delivery guy from the Chinese takeout down the street or perhaps her landlord coming to complain about the noise Ptol…" | | 2 | "The movement was fluid, effortless, as if the three deadbolts and her verbal command held no more weight than a cobweb." | | 3 | "She found only exhaustion mirroring her own, and a hunger that made her breath hitch." |
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| 38.79% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 29 | | uselessAdditionCount | 5 | | matches | | 0 | "Lucien's voice dropped, the words landing heavy in the small room" | | 1 | "He caught, his thumb brushing over the crescent scar" | | 2 | "she insisted, though her voice lacked conviction" | | 3 | "He paused, his gaze dropping to her mouth again" | | 4 | "He met, a ghost of a smile touching his lips" |
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| 90.30% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 4 | | fancyTags | | 0 | "Lucien observed (observe)" | | 1 | "he murmured (murmur)" | | 2 | "she whispered (whisper)" | | 3 | "she insisted (insist)" |
| | dialogueSentences | 67 | | tagDensity | 0.134 | | leniency | 0.269 | | rawRatio | 0.444 | | effectiveRatio | 0.119 | |