| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 2 | | adverbTags | | 0 | "the man said quietly [quietly]" | | 1 | "she said quietly [quietly]" |
| | dialogueSentences | 80 | | tagDensity | 0.288 | | leniency | 0.575 | | rawRatio | 0.087 | | effectiveRatio | 0.05 | |
| 82.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1166 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slowly" | | 1 | "really" | | 2 | "slightly" | | 3 | "softly" |
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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) | |
| 78.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1166 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "scanned" | | 1 | "warmth" | | 2 | "charm" | | 3 | "scanning" | | 4 | "silence" |
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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 | 98 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 98 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 155 | | 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 | 3 | | markdownWords | 10 | | totalWords | 1173 | | ratio | 0.009 | | matches | | 0 | "us" | | 1 | "your" | | 2 | "‘Wish you were here to ruin the view.’" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 24 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 690 | | uniqueNames | 16 | | maxNameDensity | 2.46 | | worstName | "Silas" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | London | 1 | | Chet | 1 | | Baker | 1 | | Silas | 17 | | Prague | 1 | | Soho | 1 | | Tuesday | 1 | | Oban | 1 | | Elias | 11 | | Voss | 1 | | Golden | 1 | | Empress | 1 | | Silence | 1 | | Rory | 6 |
| | persons | | 0 | "Chet" | | 1 | "Baker" | | 2 | "Silas" | | 3 | "Elias" | | 4 | "Voss" | | 5 | "Rory" |
| | places | | 0 | "Raven" | | 1 | "London" | | 2 | "Prague" | | 3 | "Soho" |
| | globalScore | 0.268 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 36 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 29.50% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.705 | | wordCount | 1173 | | matches | | 0 | "not from laughter anymore, but calculation" | | 1 | "not with curiosity, but appraisal" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 155 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 74 | | mean | 15.85 | | std | 16.57 | | cv | 1.045 | | sampleLengths | | 0 | 97 | | 1 | 65 | | 2 | 8 | | 3 | 26 | | 4 | 14 | | 5 | 15 | | 6 | 2 | | 7 | 61 | | 8 | 9 | | 9 | 5 | | 10 | 14 | | 11 | 24 | | 12 | 11 | | 13 | 19 | | 14 | 11 | | 15 | 36 | | 16 | 2 | | 17 | 3 | | 18 | 30 | | 19 | 15 | | 20 | 7 | | 21 | 7 | | 22 | 20 | | 23 | 6 | | 24 | 60 | | 25 | 7 | | 26 | 6 | | 27 | 8 | | 28 | 20 | | 29 | 3 | | 30 | 11 | | 31 | 16 | | 32 | 18 | | 33 | 57 | | 34 | 5 | | 35 | 2 | | 36 | 9 | | 37 | 11 | | 38 | 10 | | 39 | 9 | | 40 | 7 | | 41 | 32 | | 42 | 5 | | 43 | 21 | | 44 | 6 | | 45 | 17 | | 46 | 8 | | 47 | 8 | | 48 | 7 | | 49 | 36 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 98 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 134 | | matches | | 0 | "was bracing" | | 1 | "was recalibrating" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 12 | | totalSentences | 155 | | ratio | 0.077 | | matches | | 0 | "Jazz hummed from a vintage record player behind the counter — Chet Baker, late ‘50s, something melancholy and slow." | | 1 | "He looked too sharp for Soho on a Tuesday — charcoal suit, polished brogues, a trench folded over one arm like it weighed nothing." | | 2 | "Then, slowly, he smiled — a thing not meant for strangers." | | 3 | "Silas saw the lines around the man’s eyes — not from laughter anymore, but calculation." | | 4 | "The man — Elias Voss — didn’t answer." | | 5 | "Elias glanced at the bookshelf behind the bar — floor-to-ceiling, leather-bound, a little too symmetrical." | | 6 | "Light from the landing haloed her — black hair falling flat against her collar, blue eyes scanning the room not with curiosity, but appraisal." | | 7 | "He flinched — not dramatically, just a tightening around the eyes." | | 8 | "He looked different — older, yes, but also hollowed out, as if someone had taken the boy who screamed at her in kitchens, who left fingerprints like bruises on her arms, and sanded him down to something almost civil." | | 9 | "The crescent scar on her wrist caught the light — white, thin, a secret the sleeve usually hid." | | 10 | "Silas placed a hand on the bar — not heavy, just present." | | 11 | "Rory moved then — turned on her heel." |
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| 95.33% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 397 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.04534005037783375 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.007556675062972292 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 155 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 155 | | mean | 7.57 | | std | 6.28 | | cv | 0.83 | | sampleLengths | | 0 | 25 | | 1 | 11 | | 2 | 19 | | 3 | 24 | | 4 | 18 | | 5 | 4 | | 6 | 11 | | 7 | 24 | | 8 | 14 | | 9 | 12 | | 10 | 4 | | 11 | 4 | | 12 | 3 | | 13 | 11 | | 14 | 12 | | 15 | 8 | | 16 | 6 | | 17 | 3 | | 18 | 8 | | 19 | 4 | | 20 | 2 | | 21 | 14 | | 22 | 15 | | 23 | 17 | | 24 | 5 | | 25 | 5 | | 26 | 5 | | 27 | 5 | | 28 | 1 | | 29 | 3 | | 30 | 5 | | 31 | 6 | | 32 | 8 | | 33 | 4 | | 34 | 20 | | 35 | 8 | | 36 | 3 | | 37 | 5 | | 38 | 14 | | 39 | 7 | | 40 | 4 | | 41 | 18 | | 42 | 18 | | 43 | 2 | | 44 | 3 | | 45 | 8 | | 46 | 13 | | 47 | 9 | | 48 | 6 | | 49 | 9 |
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| 52.69% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3548387096774194 | | totalSentences | 155 | | uniqueOpeners | 55 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 73 | | matches | | 0 | "Then, slowly, he smiled —" | | 1 | "Then she descended, slow, deliberate." | | 2 | "Then she looked away." | | 3 | "Then she climbed the stairs" |
| | ratio | 0.055 | |
| 93.97% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 73 | | matches | | 0 | "His limp was more pronounced" | | 1 | "He looked too sharp for" | | 2 | "His hair, once shaggy and" | | 3 | "He scanned the room with" | | 4 | "They looked at each other," | | 5 | "He laughed, but it didn’t" | | 6 | "He swirled the whiskey, watching" | | 7 | "She wore a damp navy" | | 8 | "His breath caught, just slightly." | | 9 | "She didn’t smile." | | 10 | "Her gaze landed on him" | | 11 | "Her voice was flat" | | 12 | "He flinched — not dramatically," | | 13 | "She set a brown paper" | | 14 | "She stared at Elias like" | | 15 | "He looked different — older," | | 16 | "She pulled off her gloves" | | 17 | "He touched his side instinctively." | | 18 | "She stepped closer" | | 19 | "He reached into his coat." |
| | ratio | 0.315 | |
| 55.89% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 73 | | matches | | 0 | "Rain drummed a steady rhythm" | | 1 | "Jazz hummed from a vintage" | | 2 | "Silas stood behind the bar," | | 3 | "His limp was more pronounced" | | 4 | "The door creaked open." | | 5 | "A man stepped in, shaking" | | 6 | "He looked too sharp for" | | 7 | "His hair, once shaggy and" | | 8 | "He scanned the room with" | | 9 | "Silas didn’t look up." | | 10 | "The man froze." | | 11 | "The man approached." | | 12 | "They looked at each other," | | 13 | "Silas saw the lines around" | | 14 | "The easy warmth in his" | | 15 | "Silas set the tumbler down." | | 16 | "The man picked it up." | | 17 | "He laughed, but it didn’t" | | 18 | "the man said quietly" | | 19 | "Silas exhaled through his nose." |
| | ratio | 0.808 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 2 | | matches | | 0 | "Rain drummed a steady rhythm against the pavement outside The Raven’s Nest, the kind of persistent London drizzle that seeped into coats and moods alike." | | 1 | "He looked different — older, yes, but also hollowed out, as if someone had taken the boy who screamed at her in kitchens, who left fingerprints like bruises on …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 17 | | fancyCount | 1 | | fancyTags | | 0 | "Silas corrected (correct)" |
| | dialogueSentences | 80 | | tagDensity | 0.213 | | leniency | 0.425 | | rawRatio | 0.059 | | effectiveRatio | 0.025 | |