| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 34 | | tagDensity | 0.412 | | leniency | 0.824 | | rawRatio | 0.071 | | effectiveRatio | 0.059 | |
| 96.12% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1290 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 45.74% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1290 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "silence" | | 1 | "echo" | | 2 | "weight" | | 3 | "scanning" | | 4 | "flicker" | | 5 | "navigated" | | 6 | "sense of" | | 7 | "tracing" | | 8 | "stark" | | 9 | "familiar" | | 10 | "depths" |
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| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
| | 1 | | label | "air was thick with" | | count | 1 |
| | 2 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "knuckles went white" | | 1 | "the air was thick with" | | 2 | "hung in the air" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 72 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 72 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 89 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1287 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 899 | | uniqueNames | 15 | | maxNameDensity | 0.67 | | worstName | "Silas" | | maxWindowNameDensity | 2 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Carter | 1 | | Evan | 2 | | Aurora | 4 | | Blackwood | 1 | | Scotch | 1 | | Cold | 1 | | War-era | 1 | | Prague | 1 | | Silas | 6 | | Tom | 1 | | Bristol | 1 | | Channel | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Evan" | | 4 | "Aurora" | | 5 | "Blackwood" | | 6 | "War-era" | | 7 | "Silas" | | 8 | "Tom" |
| | places | | 0 | "Soho" | | 1 | "Cold" | | 2 | "Prague" | | 3 | "Bristol" |
| | globalScore | 1 | | windowScore | 1 | |
| 59.09% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like a coffin tonight, the silence" | | 1 | "swallow that seemed to burn" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.777 | | wordCount | 1287 | | matches | | 0 | "not touching her, but his hand hovered near the crescent scar on her wrist, a deli" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 89 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 40.22 | | std | 23.66 | | cv | 0.588 | | sampleLengths | | 0 | 73 | | 1 | 67 | | 2 | 84 | | 3 | 41 | | 4 | 17 | | 5 | 18 | | 6 | 19 | | 7 | 8 | | 8 | 36 | | 9 | 11 | | 10 | 25 | | 11 | 67 | | 12 | 59 | | 13 | 10 | | 14 | 43 | | 15 | 24 | | 16 | 57 | | 17 | 4 | | 18 | 46 | | 19 | 63 | | 20 | 61 | | 21 | 63 | | 22 | 50 | | 23 | 14 | | 24 | 53 | | 25 | 12 | | 26 | 78 | | 27 | 19 | | 28 | 33 | | 29 | 20 | | 30 | 38 | | 31 | 74 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 72 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 132 | | matches | | |
| 14.45% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 1 | | flaggedSentences | 4 | | totalSentences | 89 | | ratio | 0.045 | | matches | | 0 | "“He’s worried. The barrister in him reads danger into every silence.” Silas accepted his glass—a smoky Scotch, neat." | | 1 | "He took a slow sip, his gaze distant, fixed on a photograph across the room—a group of young men in Cold War-era suits, all smiles and bravado." | | 2 | "For a second, the quiet authority he wore like a coat slipped, and she saw the man underneath—the field agent who’d come home from Prague with a ruined knee and, she suspected, a ruin far deeper." | | 3 | "It wasn’t just a story; it was the foundational rock of his existence." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 907 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.026460859977949284 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.008820286659316428 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 89 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 89 | | mean | 14.46 | | std | 10 | | cv | 0.691 | | sampleLengths | | 0 | 29 | | 1 | 21 | | 2 | 23 | | 3 | 12 | | 4 | 6 | | 5 | 36 | | 6 | 13 | | 7 | 11 | | 8 | 10 | | 9 | 22 | | 10 | 18 | | 11 | 21 | | 12 | 1 | | 13 | 1 | | 14 | 13 | | 15 | 16 | | 16 | 12 | | 17 | 3 | | 18 | 14 | | 19 | 6 | | 20 | 12 | | 21 | 15 | | 22 | 4 | | 23 | 8 | | 24 | 16 | | 25 | 8 | | 26 | 12 | | 27 | 3 | | 28 | 8 | | 29 | 18 | | 30 | 3 | | 31 | 4 | | 32 | 9 | | 33 | 30 | | 34 | 12 | | 35 | 13 | | 36 | 3 | | 37 | 27 | | 38 | 32 | | 39 | 10 | | 40 | 12 | | 41 | 31 | | 42 | 9 | | 43 | 10 | | 44 | 5 | | 45 | 32 | | 46 | 25 | | 47 | 4 | | 48 | 46 | | 49 | 12 |
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| 52.43% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.38202247191011235 | | totalSentences | 89 | | uniqueOpeners | 34 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 68 | | matches | | 0 | "It clung to the walls," | | 1 | "She wasn’t here for the" | | 2 | "She was here because the" | | 3 | "He moved with a particular" | | 4 | "They landed on her, and" | | 5 | "He came over, his limp" | | 6 | "He settled onto the one" | | 7 | "She didn’t look at him" | | 8 | "She watched her finger trace" | | 9 | "It wasn’t a question" | | 10 | "His network was absolute." | | 11 | "He flagged down his own" | | 12 | "He turned back to her" | | 13 | "He didn’t drink." | | 14 | "She finally looked at him" | | 15 | "He’d given her the flat," | | 16 | "He took a slow sip," | | 17 | "His eyes, sharp as flint," | | 18 | "She set her glass down" | | 19 | "He gestured with his glass" |
| | ratio | 0.574 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 68 | | matches | | 0 | "The green neon sign of" | | 1 | "It clung to the walls," | | 2 | "Aurora Carter nursed a glass" | | 3 | "She wasn’t here for the" | | 4 | "She was here because the" | | 5 | "Cardiff felt a lifetime away," | | 6 | "The door creaked open, letting" | | 7 | "A man stepped through, shaking" | | 8 | "He moved with a particular" | | 9 | "Silas Blackwood paused at the" | | 10 | "They landed on her, and" | | 11 | "He came over, his limp" | | 12 | "He settled onto the one" | | 13 | "The silver signet ring on" | | 14 | "The old alias, a ghost" | | 15 | "She didn’t look at him" | | 16 | "She watched her finger trace" | | 17 | "It wasn’t a question" | | 18 | "His network was absolute." | | 19 | "He flagged down his own" |
| | ratio | 0.956 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 86.47% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 3 | | matches | | 0 | "The green neon sign of The Raven’s Nest bled onto the damp pavement of the Soho alley, a sickly glow that didn’t so much illuminate as stain the darkness." | | 1 | "Silas Blackwood paused at the bar, his hazel eyes scanning the room in a sweep that missed nothing." | | 2 | "For a second, the quiet authority he wore like a coat slipped, and she saw the man underneath—the field agent who’d come home from Prague with a ruined knee and…" |
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| 53.57% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 2 | | matches | | 0 | "Silas accepted, neat" | | 1 | "she said, the words feeling thin and inadequate" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 34 | | tagDensity | 0.147 | | leniency | 0.294 | | rawRatio | 0 | | effectiveRatio | 0 | |