| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 3 | | adverbTags | | 0 | "he said quietly [quietly]" | | 1 | "she said softly [softly]" | | 2 | "he said softly [softly]" |
| | dialogueSentences | 72 | | tagDensity | 0.278 | | leniency | 0.556 | | rawRatio | 0.15 | | effectiveRatio | 0.083 | |
| 76.12% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1675 | | totalAiIsmAdverbs | 8 | | found | | | highlights | | 0 | "sharply" | | 1 | "slowly" | | 2 | "suddenly" | | 3 | "softly" | | 4 | "really" |
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| 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) | |
| 37.31% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1675 | | totalAiIsms | 21 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | word | "down her spine" | | count | 1 |
| | 13 | |
| | highlights | | 0 | "pulse" | | 1 | "scanning" | | 2 | "stomach" | | 3 | "flicker" | | 4 | "silence" | | 5 | "unspoken" | | 6 | "flickered" | | 7 | "unreadable" | | 8 | "trembled" | | 9 | "could feel" | | 10 | "warmth" | | 11 | "electric" | | 12 | "down her spine" | | 13 | "desire" |
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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 | 143 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 143 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 194 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1663 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 1216 | | uniqueNames | 9 | | maxNameDensity | 0.58 | | worstName | "Lucien" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 6 | | Eva | 4 | | Lucien | 7 | | London | 1 | | Soho | 1 | | Evan | 2 | | Luc | 2 | | Ptolemy | 3 | | Wanted | 3 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Lucien" | | 3 | "Evan" | | 4 | "Luc" | | 5 | "Ptolemy" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 75 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed smaller with him inside it" |
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| 79.74% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.203 | | wordCount | 1663 | | matches | | 0 | "not as a ghost, not as a man who’d left her in the dark, but as a partner" | | 1 | "not as a man who’d left her in the dark, but as a partner" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 194 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 101 | | mean | 16.47 | | std | 14.96 | | cv | 0.909 | | sampleLengths | | 0 | 90 | | 1 | 32 | | 2 | 15 | | 3 | 60 | | 4 | 13 | | 5 | 26 | | 6 | 12 | | 7 | 44 | | 8 | 1 | | 9 | 12 | | 10 | 23 | | 11 | 40 | | 12 | 2 | | 13 | 14 | | 14 | 10 | | 15 | 15 | | 16 | 41 | | 17 | 43 | | 18 | 42 | | 19 | 1 | | 20 | 2 | | 21 | 29 | | 22 | 63 | | 23 | 8 | | 24 | 1 | | 25 | 2 | | 26 | 22 | | 27 | 4 | | 28 | 24 | | 29 | 26 | | 30 | 7 | | 31 | 24 | | 32 | 29 | | 33 | 20 | | 34 | 1 | | 35 | 4 | | 36 | 15 | | 37 | 27 | | 38 | 20 | | 39 | 16 | | 40 | 22 | | 41 | 17 | | 42 | 2 | | 43 | 6 | | 44 | 23 | | 45 | 13 | | 46 | 39 | | 47 | 9 | | 48 | 3 | | 49 | 37 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 143 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 229 | | matches | | 0 | "was peeling" | | 1 | "was preparing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 2 | | flaggedSentences | 12 | | totalSentences | 194 | | ratio | 0.062 | | matches | | 0 | "She froze mid-motion, automatically cataloguing the sound—three sharp taps, a pause, then two more." | | 1 | "Not Eva herself; her friend never knocked like that." | | 2 | "The flat smelled of curry and old books and Eva’s jasmine incense—faint this late, but still there." | | 3 | "A flicker—ambiguous—crossed his face." | | 4 | "Eva had never been loyal; she’d just been Rory’s oldest friend, the one who’d helped her pack a single suitcase and flee to London with nothing but the clothes on her back." | | 5 | "The scent of bergamot and burnt herbs—something alchemical—rolled off him in waves." | | 6 | "Lucien’s left eye—black, depthless—flickered with something unreadable." | | 7 | "Close enough that she could feel the heat of him, smell the metallic tang of his skin—like ozone before a storm." | | 8 | "He stood close—too close." | | 9 | "“I know.” He reached into his coat, pulled out a folded sheet of paper—aged, yellowed at the edges." | | 10 | "For the first time, she let herself look at him—not as a ghost, not as a man who’d left her in the dark, but as a partner." | | 11 | "His black eye glazed over for a second—demonic instinct, reacting to her pulse, her desire." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1232 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 42 | | adverbRatio | 0.03409090909090909 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.00974025974025974 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 194 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 194 | | mean | 8.57 | | std | 7.12 | | cv | 0.83 | | sampleLengths | | 0 | 22 | | 1 | 14 | | 2 | 2 | | 3 | 9 | | 4 | 43 | | 5 | 6 | | 6 | 7 | | 7 | 19 | | 8 | 15 | | 9 | 23 | | 10 | 19 | | 11 | 18 | | 12 | 13 | | 13 | 3 | | 14 | 2 | | 15 | 21 | | 16 | 12 | | 17 | 17 | | 18 | 27 | | 19 | 1 | | 20 | 11 | | 21 | 1 | | 22 | 5 | | 23 | 5 | | 24 | 13 | | 25 | 32 | | 26 | 4 | | 27 | 4 | | 28 | 2 | | 29 | 4 | | 30 | 2 | | 31 | 2 | | 32 | 6 | | 33 | 6 | | 34 | 4 | | 35 | 9 | | 36 | 6 | | 37 | 2 | | 38 | 32 | | 39 | 7 | | 40 | 9 | | 41 | 14 | | 42 | 20 | | 43 | 15 | | 44 | 8 | | 45 | 7 | | 46 | 12 | | 47 | 1 | | 48 | 2 | | 49 | 17 |
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| 44.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.28865979381443296 | | totalSentences | 194 | | uniqueOpeners | 56 | |
| 78.13% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 128 | | matches | | 0 | "Instead, she walked to the" | | 1 | "Just before he stepped into" | | 2 | "Then she said, quieter than" |
| | ratio | 0.023 | |
| 26.25% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 62 | | totalSentences | 128 | | matches | | 0 | "She froze mid-motion, automatically cataloguing" | | 1 | "She slipped on a fresh" | | 2 | "She could pretend not to" | | 3 | "She undid the locks one" | | 4 | "His coat was damp at" | | 5 | "she said, her voice cooler" | | 6 | "He didn’t smile." | | 7 | "he said, stepping forward before" | | 8 | "She closed the door, the" | | 9 | "He didn’t remove his coat." | | 10 | "he said, though his gaze" | | 11 | "She exhaled sharply through her" | | 12 | "He shifted the cane to" | | 13 | "She wouldn’t betray her, not" | | 14 | "She grabbed a towel from" | | 15 | "Her reflection in the microwave" | | 16 | "She tossed the towel onto" | | 17 | "he said quietly" | | 18 | "She turned slowly." | | 19 | "His fingers tightened around the" |
| | ratio | 0.484 | |
| 45.94% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 106 | | totalSentences | 128 | | matches | | 0 | "The knock came just as" | | 1 | "She froze mid-motion, automatically cataloguing" | | 2 | "She slipped on a fresh" | | 3 | "Rory’s fingers hesitated over the" | | 4 | "She could pretend not to" | | 5 | "She undid the locks one" | | 6 | "Lucien stood framed in the" | | 7 | "His coat was damp at" | | 8 | "The ivory handle of his" | | 9 | "she said, her voice cooler" | | 10 | "He didn’t smile." | | 11 | "he said, stepping forward before" | | 12 | "The flat smelled of curry" | | 13 | "Ptolemy the tabby lifted his" | | 14 | "She closed the door, the" | | 15 | "He didn’t remove his coat." | | 16 | "That was a bad sign." | | 17 | "Lucien didn’t keep his coat" | | 18 | "he said, though his gaze" | | 19 | "A raised, permanent mark." |
| | ratio | 0.828 | |
| 39.06% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 128 | | matches | | | ratio | 0.008 | |
| 48.87% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 5 | | matches | | 0 | "She slipped on a fresh t-shirt before padding to the door in socks, her pulse hiccuping when she saw the silhouette through the peephole: broad shoulders, a cha…" | | 1 | "But there was something in the set of his jaw, something raw beneath the polished veneer, that made her stomach clench." | | 2 | "The way his hands had tangled in her hair, his mouth hot against hers, only for him to pull back seconds later as if burned." | | 3 | "A flawed, arrogant, terrifyingly intelligent partner who understood more about the world’s shadows than she ever wanted to." | | 4 | "A spark that traveled up her arm, through her shoulder, down her spine." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 6 | | matches | | 0 | "she said, her voice cooler than she felt" | | 1 | "he said, though his gaze lingered on her left wrist, where the crescent scar from the kitchen knife accident when she was eleven stood out pale against her skin" | | 2 | "He stepped, the cane tapping softly on the laminate floor" | | 3 | "he said, his voice low, dangerous" | | 4 | "She laughed, bitter" | | 5 | "she said, voice steadier than she felt" |
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| 80.56% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 5 | | fancyTags | | 0 | "Rory muttered (mutter)" | | 1 | "Luc continued (continue)" | | 2 | "she whispered (whisper)" | | 3 | "She laughed (laugh)" | | 4 | "she muttered (mutter)" |
| | dialogueSentences | 72 | | tagDensity | 0.208 | | leniency | 0.417 | | rawRatio | 0.333 | | effectiveRatio | 0.139 | |