| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 142 | | tagDensity | 0.127 | | leniency | 0.254 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.56% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2252 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 84.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2252 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "glint" | | 1 | "weight" | | 2 | "footsteps" | | 3 | "silence" | | 4 | "could feel" | | 5 | "trembled" |
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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 | 161 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 161 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 285 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2250 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 30 | | unquotedAttributions | 2 | | matches | | 0 | "The next year, she called it cowardice." | | 1 | "In every version, she said something clean and final." |
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| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 91 | | wordCount | 1508 | | uniqueNames | 10 | | maxNameDensity | 2.92 | | worstName | "Rory" | | maxWindowNameDensity | 5 | | worstWindowName | "Rory" | | discoveredNames | | Golden | 1 | | Empress | 1 | | Raven | 2 | | Nest | 2 | | Rory | 44 | | Silas | 4 | | Cardiff | 2 | | Eva | 32 | | You | 2 | | London | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Silas" | | 4 | "Eva" | | 5 | "You" |
| | places | | 0 | "Golden" | | 1 | "Cardiff" | | 2 | "London" |
| | globalScore | 0.041 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 100 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.444 | | wordCount | 2250 | | matches | | 0 | "not with age exactly, but with decisions" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 285 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 171 | | mean | 13.16 | | std | 16.14 | | cv | 1.226 | | sampleLengths | | 0 | 20 | | 1 | 65 | | 2 | 27 | | 3 | 6 | | 4 | 22 | | 5 | 4 | | 6 | 5 | | 7 | 86 | | 8 | 13 | | 9 | 51 | | 10 | 3 | | 11 | 84 | | 12 | 3 | | 13 | 8 | | 14 | 15 | | 15 | 6 | | 16 | 34 | | 17 | 7 | | 18 | 2 | | 19 | 4 | | 20 | 4 | | 21 | 19 | | 22 | 18 | | 23 | 4 | | 24 | 4 | | 25 | 5 | | 26 | 4 | | 27 | 1 | | 28 | 1 | | 29 | 18 | | 30 | 38 | | 31 | 5 | | 32 | 2 | | 33 | 3 | | 34 | 16 | | 35 | 4 | | 36 | 5 | | 37 | 4 | | 38 | 36 | | 39 | 8 | | 40 | 3 | | 41 | 3 | | 42 | 5 | | 43 | 18 | | 44 | 6 | | 45 | 9 | | 46 | 2 | | 47 | 7 | | 48 | 24 | | 49 | 19 |
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| 98.73% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 161 | | matches | | 0 | "been submerged" | | 1 | "being carried" | | 2 | "was torn" |
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| 54.55% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 275 | | matches | | 0 | "was still wearing" | | 1 | "was waiting" | | 2 | "were trying" | | 3 | "was making" | | 4 | "was learning" | | 5 | "was taking" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 2 | | flaggedSentences | 4 | | totalSentences | 285 | | ratio | 0.014 | | matches | | 0 | "Her flat was above the bar; the stairs were dry, the kettle was waiting, and there was no sensible reason to step inside." | | 1 | "Black-and-white photographs watched from between them—men in uniforms, women in hats, a street Rory had never recognised." | | 2 | "Her face had sharpened—not with age exactly, but with decisions." | | 3 | "The years had not made a clean line between them; they had gathered in the space, layer upon layer, like dust on a map." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1515 | | adjectiveStacks | 2 | | stackExamples | | 0 | "present settled over her." | | 1 | "longer in front, dark" |
| | adverbCount | 53 | | adverbRatio | 0.03498349834983498 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.005940594059405941 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 285 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 285 | | mean | 7.89 | | std | 6.56 | | cv | 0.831 | | sampleLengths | | 0 | 20 | | 1 | 18 | | 2 | 20 | | 3 | 7 | | 4 | 20 | | 5 | 4 | | 6 | 23 | | 7 | 6 | | 8 | 2 | | 9 | 3 | | 10 | 11 | | 11 | 6 | | 12 | 4 | | 13 | 5 | | 14 | 22 | | 15 | 11 | | 16 | 17 | | 17 | 10 | | 18 | 26 | | 19 | 13 | | 20 | 4 | | 21 | 18 | | 22 | 29 | | 23 | 3 | | 24 | 26 | | 25 | 6 | | 26 | 15 | | 27 | 8 | | 28 | 10 | | 29 | 19 | | 30 | 3 | | 31 | 7 | | 32 | 1 | | 33 | 5 | | 34 | 5 | | 35 | 5 | | 36 | 6 | | 37 | 13 | | 38 | 13 | | 39 | 8 | | 40 | 4 | | 41 | 3 | | 42 | 2 | | 43 | 4 | | 44 | 4 | | 45 | 19 | | 46 | 3 | | 47 | 5 | | 48 | 10 | | 49 | 4 |
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| 41.93% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 23 | | diversityRatio | 0.22456140350877193 | | totalSentences | 285 | | uniqueOpeners | 64 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 143 | | matches | | 0 | "Then someone laughed behind the" | | 1 | "Then the present settled over" | | 2 | "Then Eva had disappeared." | | 3 | "Then the moment passed." | | 4 | "Somewhere below, the bar door" |
| | ratio | 0.035 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 143 | | matches | | 0 | "She had finished the last" | | 1 | "She could go upstairs." | | 2 | "Her flat was above the" | | 3 | "She knew that laugh." | | 4 | "She pushed through the door." | | 5 | "She knew the tilt of" | | 6 | "She had known those things" | | 7 | "Her hair was cut close" | | 8 | "Her face had sharpened—not with" | | 9 | "She wore a charcoal suit" | | 10 | "He set down the glass." | | 11 | "He took his time leaving," | | 12 | "He disappeared behind the bar" | | 13 | "It didn’t quite make it." | | 14 | "Her fingers were cold." | | 15 | "She tugged it down again." | | 16 | "They were also practiced, or" | | 17 | "She kept her hands around" | | 18 | "She had sat on the" | | 19 | "You can stay with me." |
| | ratio | 0.252 | |
| 50.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 117 | | totalSentences | 143 | | matches | | 0 | "The green neon above the" | | 1 | "Rory stood beneath it with" | | 2 | "She had finished the last" | | 3 | "Steam and chilli clung to" | | 4 | "She could go upstairs." | | 5 | "Her flat was above the" | | 6 | "A short, surprised sound, cut" | | 7 | "Rory’s hand tightened on the" | | 8 | "She knew that laugh." | | 9 | "She pushed through the door." | | 10 | "The Raven’s Nest held its" | | 11 | "The place smelled of gin," | | 12 | "The woman on the stool" | | 13 | "Rory knew her shoulders." | | 14 | "She knew the tilt of" | | 15 | "She had known those things" | | 16 | "The woman turned." | | 17 | "Her hair was cut close" | | 18 | "A small gold hoop glinted" | | 19 | "Her face had sharpened—not with" |
| | ratio | 0.818 | |
| 34.97% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 143 | | matches | | 0 | "Now they were here, simple" |
| | ratio | 0.007 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 61 | | technicalSentenceCount | 1 | | matches | | 0 | "The green neon above the door made the rain look faintly green, as if the whole street had been submerged." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 142 | | tagDensity | 0.092 | | leniency | 0.183 | | rawRatio | 0 | | effectiveRatio | 0 | |