| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 60 | | tagDensity | 0.267 | | leniency | 0.533 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.77% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1605 | | totalAiIsmAdverbs | 2 | | 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) | |
| 47.04% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1605 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "gloom" | | 1 | "familiar" | | 2 | "silk" | | 3 | "silence" | | 4 | "echoing" | | 5 | "synthetic" | | 6 | "scanned" | | 7 | "complex" | | 8 | "traced" | | 9 | "structure" | | 10 | "pounding" | | 11 | "standard" | | 12 | "could feel" | | 13 | "rhythmic" |
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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 | 163 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 163 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 207 | | 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 | 2 | | markdownWords | 2 | | totalWords | 1602 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 1230 | | uniqueNames | 7 | | maxNameDensity | 1.95 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 24 | | Quinn | 1 | | Foster | 13 | | London | 1 | | North | 1 | | Morris | 2 | | Town | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Foster" | | 3 | "Morris" |
| | places | | | globalScore | 0.524 | | windowScore | 0.5 | |
| 96.81% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 94 | | glossingSentenceCount | 2 | | matches | | 0 | "tasted like a battery terminal on the ton" | | 1 | "looked like a solid blur of silver" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1602 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 207 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 90 | | mean | 17.8 | | std | 13.71 | | cv | 0.77 | | sampleLengths | | 0 | 14 | | 1 | 46 | | 2 | 10 | | 3 | 48 | | 4 | 1 | | 5 | 13 | | 6 | 33 | | 7 | 49 | | 8 | 5 | | 9 | 24 | | 10 | 29 | | 11 | 3 | | 12 | 29 | | 13 | 1 | | 14 | 4 | | 15 | 17 | | 16 | 2 | | 17 | 37 | | 18 | 38 | | 19 | 39 | | 20 | 39 | | 21 | 2 | | 22 | 10 | | 23 | 34 | | 24 | 5 | | 25 | 31 | | 26 | 4 | | 27 | 33 | | 28 | 2 | | 29 | 24 | | 30 | 2 | | 31 | 31 | | 32 | 8 | | 33 | 35 | | 34 | 5 | | 35 | 4 | | 36 | 23 | | 37 | 3 | | 38 | 24 | | 39 | 21 | | 40 | 8 | | 41 | 3 | | 42 | 7 | | 43 | 10 | | 44 | 21 | | 45 | 14 | | 46 | 31 | | 47 | 3 | | 48 | 42 | | 49 | 24 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 163 | | matches | | 0 | "was covered" | | 1 | "was destroyed" |
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| 77.68% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 218 | | matches | | 0 | "wasn't pointing" | | 1 | "was spinning" | | 2 | "was happening" | | 3 | "was rattling" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 207 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1233 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.016220600162206 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.006488240064882401 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 207 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 207 | | mean | 7.74 | | std | 5.5 | | cv | 0.71 | | sampleLengths | | 0 | 14 | | 1 | 18 | | 2 | 16 | | 3 | 1 | | 4 | 11 | | 5 | 10 | | 6 | 14 | | 7 | 3 | | 8 | 18 | | 9 | 13 | | 10 | 1 | | 11 | 13 | | 12 | 3 | | 13 | 15 | | 14 | 3 | | 15 | 1 | | 16 | 11 | | 17 | 18 | | 18 | 22 | | 19 | 7 | | 20 | 1 | | 21 | 1 | | 22 | 5 | | 23 | 24 | | 24 | 2 | | 25 | 6 | | 26 | 4 | | 27 | 8 | | 28 | 2 | | 29 | 2 | | 30 | 5 | | 31 | 3 | | 32 | 14 | | 33 | 15 | | 34 | 1 | | 35 | 4 | | 36 | 8 | | 37 | 4 | | 38 | 1 | | 39 | 4 | | 40 | 2 | | 41 | 7 | | 42 | 30 | | 43 | 26 | | 44 | 4 | | 45 | 8 | | 46 | 7 | | 47 | 27 | | 48 | 1 | | 49 | 4 |
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| 52.66% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.36231884057971014 | | totalSentences | 207 | | uniqueOpeners | 75 | |
| 68.03% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 147 | | matches | | 0 | "Too light to be human" | | 1 | "Too regular to be debris." | | 2 | "Just like Morris." |
| | ratio | 0.02 | |
| 81.22% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 51 | | totalSentences | 147 | | matches | | 0 | "He looked pale." | | 1 | "He gestured towards the centre" | | 2 | "She adjusted her cuffs, the" | | 3 | "She stepped into the pool" | | 4 | "He wore a coat made" | | 5 | "His skin was the colour" | | 6 | "Her knees popped in the" | | 7 | "She leaned in close." | | 8 | "She snapped them on." | | 9 | "She scanned the ground around" | | 10 | "They circled the body, weaving" | | 11 | "She traced a line in" | | 12 | "She patted them down with" | | 13 | "She pulled it out." | | 14 | "It wasn't pointing North." | | 15 | "It wasn't moving at all." | | 16 | "She stood up" | | 17 | "Her sharp jawline tightened as" | | 18 | "She held the compass flat" | | 19 | "It spun, stopped, and pointed" |
| | ratio | 0.347 | |
| 28.03% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 127 | | totalSentences | 147 | | matches | | 0 | "Detective Harlow Quinn ducked under" | | 1 | "The air hung heavy and" | | 2 | "The metallic tang tasted like" | | 3 | "Sergeant Foster stood by a" | | 4 | "He looked pale." | | 5 | "The shadows cast by the" | | 6 | "He gestured towards the centre" | | 7 | "Harlow ignored him." | | 8 | "She adjusted her cuffs, the" | | 9 | "A familiar habit." | | 10 | "She stepped into the pool" | | 11 | "The victim lay sprawled on" | | 12 | "He wore a coat made" | | 13 | "His skin was the colour" | | 14 | "Her knees popped in the" | | 15 | "She leaned in close." | | 16 | "The body smelled of rain" | | 17 | "That was the first anomaly." | | 18 | "Foster stepped closer, his nervousness" | | 19 | "Harlow shone her torch onto" |
| | ratio | 0.864 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 147 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 2 | | matches | | 0 | "He wore a coat made of heavy, quilted silk, the fabric shimmering with an iridescence that didn't belong in a London sewer." | | 1 | "She could feel the rift opening, pulling at her soul, dragging her towards the other side." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 4 | | matches | | 0 | "Foster stepped, his nervousness radiating off him like heat" | | 1 | "Foster sighed, the sound echoing slightly" | | 2 | "Harlow barked, her voice cracking like a whip" | | 3 | "Harlow said, her voice steady despite the pounding of her own heart" |
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| 83.33% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 4 | | fancyTags | | 0 | "Foster sighed (sigh)" | | 1 | "Harlow barked (bark)" | | 2 | "Harlow shouted (shout)" | | 3 | "Foster wheezed (wheeze)" |
| | dialogueSentences | 60 | | tagDensity | 0.083 | | leniency | 0.167 | | rawRatio | 0.8 | | effectiveRatio | 0.133 | |