| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 176 | | tagDensity | 0.057 | | leniency | 0.114 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.44% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1953 | | totalAiIsmAdverbs | 1 | | 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) | |
| 92.32% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1953 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "familiar" | | 1 | "flicked" | | 2 | "warmth" |
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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 | 107 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 107 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 273 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1953 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 30 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 85 | | wordCount | 1002 | | uniqueNames | 7 | | maxNameDensity | 3.69 | | worstName | "Rory" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 2 | | Nest | 1 | | Silas | 8 | | Rory | 37 | | Cardiff | 2 | | Eva | 34 | | London | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Rory" | | 4 | "Eva" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1953 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 273 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 188 | | mean | 10.39 | | std | 12.46 | | cv | 1.2 | | sampleLengths | | 0 | 53 | | 1 | 7 | | 2 | 5 | | 3 | 5 | | 4 | 5 | | 5 | 4 | | 6 | 34 | | 7 | 54 | | 8 | 1 | | 9 | 10 | | 10 | 2 | | 11 | 94 | | 12 | 1 | | 13 | 12 | | 14 | 3 | | 15 | 21 | | 16 | 8 | | 17 | 6 | | 18 | 15 | | 19 | 13 | | 20 | 2 | | 21 | 8 | | 22 | 7 | | 23 | 2 | | 24 | 3 | | 25 | 38 | | 26 | 9 | | 27 | 3 | | 28 | 4 | | 29 | 11 | | 30 | 29 | | 31 | 3 | | 32 | 4 | | 33 | 11 | | 34 | 2 | | 35 | 4 | | 36 | 12 | | 37 | 10 | | 38 | 18 | | 39 | 11 | | 40 | 5 | | 41 | 3 | | 42 | 3 | | 43 | 27 | | 44 | 23 | | 45 | 6 | | 46 | 31 | | 47 | 2 | | 48 | 11 | | 49 | 15 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 107 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 170 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 1 | | totalSentences | 273 | | ratio | 0.004 | | matches | | 0 | "Rory had imagined this meeting in scraps, never as a conversation, more as a sequence of images: Eva’s face at the door; her own hand on a phone; the message she had typed and deleted so many times she’d lost track of its exact words." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1004 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.01593625498007968 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 273 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 273 | | mean | 7.15 | | std | 5.76 | | cv | 0.805 | | sampleLengths | | 0 | 19 | | 1 | 19 | | 2 | 15 | | 3 | 7 | | 4 | 5 | | 5 | 5 | | 6 | 5 | | 7 | 4 | | 8 | 5 | | 9 | 18 | | 10 | 11 | | 11 | 12 | | 12 | 9 | | 13 | 19 | | 14 | 14 | | 15 | 1 | | 16 | 10 | | 17 | 2 | | 18 | 18 | | 19 | 32 | | 20 | 4 | | 21 | 21 | | 22 | 10 | | 23 | 9 | | 24 | 1 | | 25 | 8 | | 26 | 4 | | 27 | 3 | | 28 | 17 | | 29 | 4 | | 30 | 4 | | 31 | 4 | | 32 | 6 | | 33 | 10 | | 34 | 5 | | 35 | 6 | | 36 | 7 | | 37 | 2 | | 38 | 8 | | 39 | 7 | | 40 | 2 | | 41 | 3 | | 42 | 11 | | 43 | 23 | | 44 | 4 | | 45 | 2 | | 46 | 4 | | 47 | 3 | | 48 | 3 | | 49 | 4 |
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| 43.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.19047619047619047 | | totalSentences | 273 | | uniqueOpeners | 52 | |
| 69.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 96 | | matches | | 0 | "Then the picture slipped." | | 1 | "Somewhere in the back, a" |
| | ratio | 0.021 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 96 | | matches | | 0 | "He set the glass down." | | 1 | "She carried herself with a" | | 2 | "His attention stayed on them." | | 3 | "She let it pass." | | 4 | "Her coat remained buttoned." | | 5 | "He poured without asking." | | 6 | "She remembered the taxi idling" | | 7 | "She had called it a" | | 8 | "She had let herself believe" | | 9 | "Her hands looked older than" | | 10 | "He didn’t look at them." | | 11 | "She looked towards the dark" | | 12 | "It carried all the small" |
| | ratio | 0.135 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 92 | | totalSentences | 96 | | matches | | 0 | "The green neon Raven above" | | 1 | "Rory pushed inside with her" | | 2 | "The bar smelled of orange" | | 3 | "Silas looked up from polishing" | | 4 | "He set the glass down." | | 5 | "A silver signet ring flashed" | | 6 | "Rory took it from him" | | 7 | "The Raven’s Nest had quieted" | | 8 | "A woman in a red" | | 9 | "Rory had just shrugged out" | | 10 | "The voice caught her between" | | 11 | "Eva stood by the far" | | 12 | "Eva wore a sharp grey" | | 13 | "A pale seam ran from" | | 14 | "She carried herself with a" | | 15 | "A small smile crossed Eva’s" | | 16 | "Eva’s eyes moved over Rory’s" | | 17 | "Rory folded the towel." | | 18 | "Silas lifted his glass again" | | 19 | "His attention stayed on them." |
| | ratio | 0.958 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 96 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 1 | | matches | | 0 | "She remembered the taxi idling outside, the cold pressing through her coat, her mother calling from upstairs that the kettle had boiled." |
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| 75.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 1 | | matches | | 0 | "Eva’s eyes moved, the bag, the crescent scar on her wrist" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | 0 | "Eva continued (continue)" |
| | dialogueSentences | 176 | | tagDensity | 0.034 | | leniency | 0.068 | | rawRatio | 0.167 | | effectiveRatio | 0.011 | |