| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "her captor continued conversationally [conversationally]" |
| | dialogueSentences | 22 | | tagDensity | 0.318 | | leniency | 0.636 | | rawRatio | 0.143 | | effectiveRatio | 0.091 | |
| 79.29% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1207 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "carefully" | | 1 | "quickly" | | 2 | "gently" | | 3 | "perfectly" | | 4 | "suddenly" |
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| 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) | |
| 46.15% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1207 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "dancing" | | 1 | "quickened" | | 2 | "perfect" | | 3 | "footfall" | | 4 | "silence" | | 5 | "pulsed" | | 6 | "flickered" | | 7 | "footsteps" | | 8 | "wavered" |
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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 | 131 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 131 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 146 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 32 | | totalWords | 1206 | | ratio | 0.027 | | matches | | 0 | "Find the clearing where wildflowers bloom in winter. Leave the order at the centre. Do not look for me. I will find you." | | 1 | "Do not look for me. I will find you." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 92.58% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 1045 | | uniqueNames | 8 | | maxNameDensity | 1.15 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 12 | | Empress | 1 | | Richmond | 1 | | Park | 1 | | London | 2 | | Heartstone | 1 | | Tall | 1 | | Heat | 1 |
| | persons | | | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "London" |
| | globalScore | 0.926 | | windowScore | 1 | |
| 66.67% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 90 | | glossingSentenceCount | 3 | | matches | | 0 | "forest that seemed to shift around her" | | 1 | "quite human" | | 2 | "quite a person gestured to the takeaway bag" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.829 | | wordCount | 1206 | | matches | | 0 | "Not unusual for eccentric clients, but paired with this location" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 146 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 57 | | mean | 21.16 | | std | 14.46 | | cv | 0.683 | | sampleLengths | | 0 | 45 | | 1 | 14 | | 2 | 23 | | 3 | 42 | | 4 | 42 | | 5 | 27 | | 6 | 43 | | 7 | 24 | | 8 | 6 | | 9 | 7 | | 10 | 1 | | 11 | 36 | | 12 | 1 | | 13 | 55 | | 14 | 9 | | 15 | 18 | | 16 | 4 | | 17 | 37 | | 18 | 25 | | 19 | 4 | | 20 | 38 | | 21 | 7 | | 22 | 36 | | 23 | 14 | | 24 | 19 | | 25 | 6 | | 26 | 2 | | 27 | 45 | | 28 | 33 | | 29 | 15 | | 30 | 33 | | 31 | 5 | | 32 | 33 | | 33 | 2 | | 34 | 18 | | 35 | 20 | | 36 | 42 | | 37 | 3 | | 38 | 31 | | 39 | 12 | | 40 | 9 | | 41 | 31 | | 42 | 24 | | 43 | 39 | | 44 | 4 | | 45 | 31 | | 46 | 26 | | 47 | 11 | | 48 | 10 | | 49 | 40 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 131 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 174 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 146 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1046 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 40 | | adverbRatio | 0.03824091778202677 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.008604206500956023 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 146 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 146 | | mean | 8.26 | | std | 4.87 | | cv | 0.59 | | sampleLengths | | 0 | 16 | | 1 | 23 | | 2 | 6 | | 3 | 3 | | 4 | 11 | | 5 | 8 | | 6 | 6 | | 7 | 5 | | 8 | 4 | | 9 | 11 | | 10 | 11 | | 11 | 8 | | 12 | 12 | | 13 | 8 | | 14 | 10 | | 15 | 24 | | 16 | 5 | | 17 | 7 | | 18 | 4 | | 19 | 11 | | 20 | 8 | | 21 | 16 | | 22 | 12 | | 23 | 2 | | 24 | 5 | | 25 | 9 | | 26 | 10 | | 27 | 5 | | 28 | 6 | | 29 | 3 | | 30 | 1 | | 31 | 1 | | 32 | 2 | | 33 | 1 | | 34 | 12 | | 35 | 9 | | 36 | 15 | | 37 | 1 | | 38 | 11 | | 39 | 15 | | 40 | 7 | | 41 | 15 | | 42 | 7 | | 43 | 9 | | 44 | 2 | | 45 | 10 | | 46 | 6 | | 47 | 4 | | 48 | 10 | | 49 | 8 |
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| 68.95% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.4383561643835616 | | totalSentences | 146 | | uniqueOpeners | 64 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 113 | | matches | | 0 | "Just darkness and the rustle" | | 1 | "Even the motorway noise from" | | 2 | "Just that she might need" | | 3 | "Even the time display flickered," | | 4 | "All wearing delivery uniforms from" |
| | ratio | 0.044 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 113 | | matches | | 0 | "I will find you.*" | | 1 | "She pushed through the treeline," | | 2 | "She quickened her pace, eager" | | 3 | "She spun round." | | 4 | "Her voice died quickly in" | | 5 | "She strained to hear traffic," | | 6 | "I will find you.* Not" | | 7 | "She reached the trees and" | | 8 | "she called out" | | 9 | "She'd walked this route five" | | 10 | "She burst through a wall" | | 11 | "She'd been running away from" | | 12 | "It tilted its head, and" | | 13 | "her captor continued conversationally" | | 14 | "It smiled with too many" | | 15 | "Her own voice, calling from" |
| | ratio | 0.142 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 113 | | matches | | 0 | "The delivery bag slipped from" | | 1 | "The grove beyond the stone" | | 2 | "Money was money." | | 3 | "I will find you.*" | | 4 | "She pushed through the treeline," | | 5 | "The trees here grew wrong," | | 6 | "The path wasn't on any" | | 7 | "The scent hit her first." | | 8 | "Jasmine and honeysuckle, thick enough" | | 9 | "She quickened her pace, eager" | | 10 | "The clearing opened before her" | | 11 | "Wildflowers carpeted the ground in" | | 12 | "Aurora set the bag down" | | 13 | "The flowers released more fragrance" | | 14 | "A branch cracked somewhere behind" | | 15 | "She spun round." | | 16 | "Her voice died quickly in" | | 17 | "She strained to hear traffic," | | 18 | "The Heartstone pendant beneath her" | | 19 | "The deep crimson gem rarely" |
| | ratio | 0.655 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 113 | | matches | | 0 | "Even if it came with" | | 1 | "Though something felt wrong about" | | 2 | "Now every direction looked the" |
| | ratio | 0.027 | |
| 93.02% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 3 | | matches | | 0 | "But here she was, following worn earth that shouldn't lead anywhere, carrying beef and black bean sauce to someone who might not even show." | | 1 | "The unknown benefactor who'd left it at her flat had never explained what it did." | | 2 | "Tall and graceful, wrapped in shadows that moved independently of any light source." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "her captor continued conversationally (continue)" |
| | dialogueSentences | 22 | | tagDensity | 0.045 | | leniency | 0.091 | | rawRatio | 1 | | effectiveRatio | 0.091 | |