| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 9 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.84% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1203 | | totalAiIsmAdverbs | 1 | | 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) | |
| 29.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1203 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "familiar" | | 1 | "weight" | | 2 | "maw" | | 3 | "silence" | | 4 | "footsteps" | | 5 | "echoed" | | 6 | "glint" | | 7 | "clandestine" | | 8 | "velvet" | | 9 | "dancing" | | 10 | "could feel" | | 11 | "silk" | | 12 | "navigated" | | 13 | "tangible" | | 14 | "whisper" |
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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 | 115 | | matches | (empty) | |
| 43.48% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 5 | | hedgeCount | 3 | | narrationSentences | 115 | | filterMatches | | | hedgeMatches | | 0 | "appeared to" | | 1 | "seemed to" | | 2 | "began to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 121 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 51 | | totalWords | 1185 | | ratio | 0.043 | | matches | | 0 | "* Quinn’s boots splashed through a deep puddle under a flickering streetlamp, rain whipping her face. *Go for the tube station," | | 1 | "Herd him underground." | | 2 | "The Raven’s Nest." | | 3 | "If you’re looking for trouble, Detective, that’s where it buys its drinks." | | 4 | "It’s not what we think, Harlow. It’s older." | | 5 | "He’s the only thread." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 17 | | wordCount | 1145 | | uniqueNames | 12 | | maxNameDensity | 0.26 | | worstName | "Morris" | | maxWindowNameDensity | 1 | | worstWindowName | "Camden" | | discoveredNames | | Neal | 1 | | Quinn | 1 | | Soho | 1 | | Camden | 2 | | Morris | 3 | | Raven | 1 | | Detective | 1 | | Tube | 1 | | Veil | 1 | | Market | 1 | | Harlow | 1 | | Protocol | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Raven" | | 3 | "Protocol" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 83.33% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 75 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like shrunken heads under glass do" | | 1 | "symbols that seemed to squirm if you looked too long" |
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| 31.22% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.688 | | wordCount | 1185 | | matches | | 0 | "not his smile, but the confusion in his eyes in their last phone call" | | 1 | "not at her throat, but at her wrist" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 121 | | matches | | 0 | "through that gate" | | 1 | "letting that coat" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 22.36 | | std | 21.16 | | cv | 0.946 | | sampleLengths | | 0 | 52 | | 1 | 59 | | 2 | 46 | | 3 | 25 | | 4 | 3 | | 5 | 30 | | 6 | 29 | | 7 | 5 | | 8 | 9 | | 9 | 73 | | 10 | 4 | | 11 | 11 | | 12 | 14 | | 13 | 37 | | 14 | 2 | | 15 | 38 | | 16 | 4 | | 17 | 47 | | 18 | 25 | | 19 | 3 | | 20 | 91 | | 21 | 40 | | 22 | 30 | | 23 | 53 | | 24 | 15 | | 25 | 4 | | 26 | 2 | | 27 | 42 | | 28 | 46 | | 29 | 5 | | 30 | 72 | | 31 | 8 | | 32 | 15 | | 33 | 8 | | 34 | 4 | | 35 | 16 | | 36 | 49 | | 37 | 4 | | 38 | 14 | | 39 | 12 | | 40 | 11 | | 41 | 9 | | 42 | 12 | | 43 | 16 | | 44 | 19 | | 45 | 3 | | 46 | 9 | | 47 | 8 | | 48 | 14 | | 49 | 10 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 115 | | matches | (empty) | |
| 65.32% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 198 | | matches | | 0 | "was gaining" | | 1 | "was heading" | | 2 | "was, ducking" | | 3 | "was speaking" |
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| 1.18% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 1 | | flaggedSentences | 6 | | totalSentences | 121 | | ratio | 0.05 | | matches | | 0 | "*Herd him underground.* The coat—her only lead in three weeks—was gaining distance into Soho’s labyrinth." | | 1 | "The bookshelf along the back wall—stuffed with leather-bound titles she’d bet a week’s salary were fakes—stood a fraction out of alignment." | | 2 | "The clientele—a mix of figures in heavy coats, some with faces hidden, others with features too sharp, eyes too reflective to be fully human—moved with purposeful indifference." | | 3 | "He was speaking to a woman draped in grey silk, exchanging a small pouch for a bone token—pale, carved." | | 4 | "Morris’s face flashed in her memory—not his smile, but the confusion in his eyes in their last phone call." | | 5 | "A hand brushed her arm; she recoiled, but the gnarled old woman selling dried herbs just smiled with too many teeth." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1163 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.02235597592433362 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.006878761822871883 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 121 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 121 | | mean | 9.79 | | std | 6.36 | | cv | 0.649 | | sampleLengths | | 0 | 28 | | 1 | 9 | | 2 | 15 | | 3 | 20 | | 4 | 1 | | 5 | 5 | | 6 | 7 | | 7 | 12 | | 8 | 9 | | 9 | 5 | | 10 | 16 | | 11 | 10 | | 12 | 6 | | 13 | 6 | | 14 | 8 | | 15 | 3 | | 16 | 9 | | 17 | 10 | | 18 | 3 | | 19 | 3 | | 20 | 5 | | 21 | 19 | | 22 | 6 | | 23 | 5 | | 24 | 13 | | 25 | 7 | | 26 | 4 | | 27 | 5 | | 28 | 4 | | 29 | 5 | | 30 | 16 | | 31 | 15 | | 32 | 15 | | 33 | 15 | | 34 | 12 | | 35 | 4 | | 36 | 11 | | 37 | 5 | | 38 | 9 | | 39 | 5 | | 40 | 21 | | 41 | 11 | | 42 | 2 | | 43 | 6 | | 44 | 4 | | 45 | 13 | | 46 | 2 | | 47 | 13 | | 48 | 1 | | 49 | 3 |
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| 55.92% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.38016528925619836 | | totalSentences | 121 | | uniqueOpeners | 46 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 107 | | matches | (empty) | | ratio | 0 | |
| 92.90% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 107 | | matches | | 0 | "She broke into a sprint," | | 1 | "He was heading towards Camden." | | 2 | "Her radio crackled at her" | | 3 | "She slowed, hand on her" | | 4 | "She edged forward." | | 5 | "Her informant’s scratchy voice echoed." | | 6 | "She paused at the entrance." | | 7 | "Her voice steadied her." | | 8 | "She pushed the heavy door." | | 9 | "She approached the bartender." | | 10 | "Her gaze swept the room." | | 11 | "She moved to the shelf," | | 12 | "He’d gone down." | | 13 | "She descended, the stairs creaking" | | 14 | "He was speaking to a" | | 15 | "He pocketed the token and" | | 16 | "Her breath caught." | | 17 | "*It’s not what we think," | | 18 | "It’s older.* Then static." | | 19 | "She touched the worn leather" |
| | ratio | 0.318 | |
| 86.17% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 80 | | totalSentences | 107 | | matches | | 0 | "The flash of a black" | | 1 | "She broke into a sprint," | | 2 | "He was heading towards Camden." | | 3 | "Her radio crackled at her" | | 4 | "This was off-book, off-grid, and" | | 5 | "Protocol said call for backup," | | 6 | "Protocol got DS Morris killed." | | 7 | "The pavement sloped, slick with" | | 8 | "A metal gate hung open," | | 9 | "She slowed, hand on her" | | 10 | "The absolute silence was worse" | | 11 | "She edged forward." | | 12 | "The alley stank of damp" | | 13 | "A raven shape." | | 14 | "*The Raven’s Nest.*" | | 15 | "Her informant’s scratchy voice echoed." | | 16 | "She paused at the entrance." | | 17 | "A clandestine meeting place, her" | | 18 | "A bookshelf that moved." | | 19 | "Her voice steadied her." |
| | ratio | 0.748 | |
| 46.73% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 107 | | matches | | 0 | "*If you’re looking for trouble," |
| | ratio | 0.009 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 56 | | technicalSentenceCount | 4 | | matches | | 0 | "*If you’re looking for trouble, Detective, that’s where it buys its drinks.* She’d dismissed it as a dead end." | | 1 | "A heavy, oil-cloth drape, stitched with symbols that seemed to squirm if you looked too long." | | 2 | "The second guard shifted, a long, thin blade appearing in its hand as if from nowhere." | | 3 | "Her service pistol was cold comfort against things that sold bottled lightning and required carved bone for entry." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 38.89% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "a voice whispered (whisper)" |
| | dialogueSentences | 9 | | tagDensity | 0.111 | | leniency | 0.222 | | rawRatio | 1 | | effectiveRatio | 0.222 | |