| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said quietly [quietly]" |
| | dialogueSentences | 33 | | tagDensity | 0.485 | | leniency | 0.97 | | rawRatio | 0.063 | | effectiveRatio | 0.061 | |
| 81.58% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1357 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slowly" | | 1 | "very" | | 2 | "really" | | 3 | "suddenly" | | 4 | "slightly" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 77.89% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1357 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "silence" | | 1 | "weight" | | 2 | "trembled" | | 3 | "pulse" | | 4 | "familiar" |
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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 | 61 | | matches | (empty) | |
| 72.60% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 61 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 79 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1344 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 53 | | wordCount | 1068 | | uniqueNames | 24 | | maxNameDensity | 0.66 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Daniel" | | discoveredNames | | Raven | 3 | | Nest | 3 | | Soho | 2 | | Aurora | 1 | | Carter | 3 | | Rory | 7 | | Laila | 2 | | Evan | 2 | | Silas | 5 | | Blackwood | 2 | | Vance | 1 | | Cardiff | 2 | | Prague | 2 | | London | 1 | | Yu-Fei | 1 | | Cheung | 1 | | Golden | 1 | | Empress | 1 | | Daniel | 7 | | Eva | 2 | | Brendan | 1 | | Irish | 1 | | Jennifer | 1 | | Ellis | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Aurora" | | 3 | "Carter" | | 4 | "Rory" | | 5 | "Laila" | | 6 | "Evan" | | 7 | "Silas" | | 8 | "Blackwood" | | 9 | "Vance" | | 10 | "Yu-Fei" | | 11 | "Cheung" | | 12 | "Daniel" | | 13 | "Eva" | | 14 | "Brendan" | | 15 | "Jennifer" | | 16 | "Ellis" |
| | places | | 0 | "Soho" | | 1 | "Cardiff" | | 2 | "Prague" | | 3 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 94.44% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 45 | | glossingSentenceCount | 1 | | matches | | 0 | "shoulders that seemed to carry an invisible weight" |
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| 51.19% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.488 | | wordCount | 1344 | | matches | | 0 | "not at Eva, but at herself for never writing back" | | 1 | "not a request but a warning dressed as concern" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 79 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 46.34 | | std | 31.21 | | cv | 0.673 | | sampleLengths | | 0 | 128 | | 1 | 51 | | 2 | 83 | | 3 | 19 | | 4 | 66 | | 5 | 27 | | 6 | 3 | | 7 | 40 | | 8 | 19 | | 9 | 53 | | 10 | 18 | | 11 | 38 | | 12 | 9 | | 13 | 17 | | 14 | 49 | | 15 | 86 | | 16 | 11 | | 17 | 28 | | 18 | 70 | | 19 | 1 | | 20 | 62 | | 21 | 62 | | 22 | 39 | | 23 | 31 | | 24 | 93 | | 25 | 14 | | 26 | 62 | | 27 | 93 | | 28 | 72 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 61 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 167 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 3 | | flaggedSentences | 8 | | totalSentences | 79 | | ratio | 0.101 | | matches | | 0 | "The green neon sign of The Raven’s Nest bled through the Soho fog like a vein of poison, and Aurora Carter—Rory, not Laila, never Laila in this life—pushed through the door without expecting anything but a dry place to wait out the rain." | | 1 | "Rory knew that trick—everyone who drank here long enough knew Silas Blackwood kept a hidden room behind the spines of dead languages—but she hadn’t expected the other ghost in the room." | | 2 | "But it was the eyes—once the color of summer lawns, now something drained, something that had seen Prague or worse—that made her freeze with her hand still on the bar rail." | | 3 | "The silver signet ring on Silas’s right hand—wait, no, Daniel wore no ring—caught the low light." | | 4 | "She thought of her father, Brendan Carter, with his Irish barrister’s certainty; of her mother, Jennifer Ellis Carter, teaching poetry to children who forgot it; of the crescent-shaped scar on her left wrist, white against her dark skin, marking the place where she had fallen as a child and promised herself she would never be trapped again." | | 5 | "His hands had been steady once; now they trembled slightly, a fine vibration beneath the skin." | | 6 | "She looked at him—the shaved head, the hollow cheeks, the expensive coat over a body that had forgotten how to be young." | | 7 | "When she finally stood and walked toward the stairs that led to her flat—above the bar, above the secrets, in the only home she had—she did not look back." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 668 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.02844311377245509 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0074850299401197605 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 79 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 79 | | mean | 17.01 | | std | 13.54 | | cv | 0.796 | | sampleLengths | | 0 | 43 | | 1 | 32 | | 2 | 53 | | 3 | 20 | | 4 | 31 | | 5 | 21 | | 6 | 31 | | 7 | 31 | | 8 | 4 | | 9 | 3 | | 10 | 12 | | 11 | 52 | | 12 | 3 | | 13 | 7 | | 14 | 4 | | 15 | 12 | | 16 | 15 | | 17 | 3 | | 18 | 7 | | 19 | 16 | | 20 | 10 | | 21 | 7 | | 22 | 6 | | 23 | 2 | | 24 | 11 | | 25 | 42 | | 26 | 11 | | 27 | 7 | | 28 | 11 | | 29 | 1 | | 30 | 10 | | 31 | 15 | | 32 | 12 | | 33 | 9 | | 34 | 17 | | 35 | 37 | | 36 | 12 | | 37 | 11 | | 38 | 57 | | 39 | 18 | | 40 | 4 | | 41 | 7 | | 42 | 19 | | 43 | 6 | | 44 | 3 | | 45 | 40 | | 46 | 16 | | 47 | 14 | | 48 | 1 | | 49 | 22 |
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| 58.23% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.379746835443038 | | totalSentences | 79 | | uniqueOpeners | 30 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 49 | | matches | (empty) | | ratio | 0 | |
| 40.41% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 49 | | matches | | 0 | "She ordered nothing, only stood" | | 1 | "He was at the back," | | 2 | "He turned his head slowly," | | 3 | "She hadn’t spoken to him" | | 4 | "Her voice sounded steadier than" | | 5 | "He laughed, and it was" | | 6 | "He gestured to the stool" | | 7 | "She sat, because standing suddenly" | | 8 | "She didn’t ask him what" | | 9 | "he said quietly" | | 10 | "She thought of her father," | | 11 | "He ran his thumb along" | | 12 | "His hands had been steady" | | 13 | "She looked at him—the shaved" | | 14 | "She looked at herself in" | | 15 | "He slid it across the" | | 16 | "It showed the two of" | | 17 | "he said, and there was" | | 18 | "She folded the photograph and" | | 19 | "He finished his drink and" |
| | ratio | 0.449 | |
| 41.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 41 | | totalSentences | 49 | | matches | | 0 | "The green neon sign of" | | 1 | "The air inside was thick" | | 2 | "She ordered nothing, only stood" | | 3 | "He was at the back," | | 4 | "Rory knew that trick—everyone who" | | 5 | "Daniel Vance had been beautiful" | | 6 | "He turned his head slowly," | | 7 | "She hadn’t spoken to him" | | 8 | "Her voice sounded steadier than" | | 9 | "He laughed, and it was" | | 10 | "He gestured to the stool" | | 11 | "The silver signet ring on" | | 12 | "Daniel wore nothing but the" | | 13 | "She sat, because standing suddenly" | | 14 | "She didn’t ask him what" | | 15 | "Daniel was not the kind" | | 16 | "he said quietly" | | 17 | "The childhood friend who had" | | 18 | "Rory felt the old anger," | | 19 | "Daniel smiled, and for a" |
| | ratio | 0.837 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 49 | | matches | | | ratio | 0.02 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 11 | | matches | | 0 | "The air inside was thick with pipe smoke and the particular silence of old maps staring down from the walls, black-and-white photographs of strangers who had li…" | | 1 | "She ordered nothing, only stood at the bar’s edge, her straight black hair dripping onto the collar of her delivery jacket, and tried not to think about the fla…" | | 2 | "Rory knew that trick—everyone who drank here long enough knew Silas Blackwood kept a hidden room behind the spines of dead languages—but she hadn’t expected the…" | | 3 | "Now he was gaunt, his hair shaved close to a skull that seemed too large for the skin remaining, and he wore a grey coat that cost more than her rent." | | 4 | "But it was the eyes—once the color of summer lawns, now something drained, something that had seen Prague or worse—that made her freeze with her hand still on t…" | | 5 | "He turned his head slowly, as though her name had physical weight." | | 6 | "She thought of her father, Brendan Carter, with his Irish barrister’s certainty; of her mother, Jennifer Ellis Carter, teaching poetry to children who forgot it…" | | 7 | "She looked at him—the shaved head, the hollow cheeks, the expensive coat over a body that had forgotten how to be young." | | 8 | "But she was safe here, in the dim light, with the maps and the dead strangers and this broken version of a friend who had once been beautiful." | | 9 | "He finished his drink and stood, adjusting the grey coat around shoulders that seemed to carry an invisible weight." | | 10 | "She watched him leave, through the door beneath the green neon, into the Soho night that swallowed people whole." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 33 | | tagDensity | 0.424 | | leniency | 0.848 | | rawRatio | 0.071 | | effectiveRatio | 0.061 | |