| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 34 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 86.14% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1082 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "utterly" | | 1 | "slowly" | | 2 | "hesitantly" |
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| 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) | |
| 16.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1082 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "familiar" | | 1 | "scanned" | | 2 | "comforting" | | 3 | "perfect" | | 4 | "eyebrow" | | 5 | "determined" | | 6 | "tension" | | 7 | "palpable" | | 8 | "unspoken" | | 9 | "etched" | | 10 | "weight" | | 11 | "tracing" | | 12 | "flicker" | | 13 | "silence" | | 14 | "delving" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "flicker of emotion" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 71 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 71 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 88 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1080 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 52 | | wordCount | 833 | | uniqueNames | 9 | | maxNameDensity | 2.52 | | worstName | "Eva" | | maxWindowNameDensity | 6 | | worstWindowName | "Eva" | | discoveredNames | | Carter | 1 | | Raven | 2 | | Nest | 2 | | Eva | 21 | | London | 2 | | Rory | 17 | | Silas | 5 | | Cardiff | 1 | | Evan | 1 |
| | persons | | 0 | "Carter" | | 1 | "Raven" | | 2 | "Eva" | | 3 | "Rory" | | 4 | "Silas" | | 5 | "Evan" |
| | places | | | globalScore | 0.239 | | windowScore | 0 | |
| 66.67% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 2 | | matches | | 0 | "quite reach her eyes" | | 1 | "as if shedding an invisible burden" |
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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 | 1080 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 88 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 27.69 | | std | 18.53 | | cv | 0.669 | | sampleLengths | | 0 | 74 | | 1 | 93 | | 2 | 28 | | 3 | 18 | | 4 | 41 | | 5 | 20 | | 6 | 17 | | 7 | 10 | | 8 | 68 | | 9 | 13 | | 10 | 20 | | 11 | 19 | | 12 | 15 | | 13 | 23 | | 14 | 12 | | 15 | 45 | | 16 | 19 | | 17 | 30 | | 18 | 15 | | 19 | 11 | | 20 | 44 | | 21 | 27 | | 22 | 50 | | 23 | 18 | | 24 | 22 | | 25 | 9 | | 26 | 32 | | 27 | 20 | | 28 | 17 | | 29 | 20 | | 30 | 25 | | 31 | 21 | | 32 | 22 | | 33 | 17 | | 34 | 38 | | 35 | 43 | | 36 | 9 | | 37 | 10 | | 38 | 45 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 71 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 136 | | matches | (empty) | |
| 45.45% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 1 | | flaggedSentences | 3 | | totalSentences | 88 | | ratio | 0.034 | | matches | | 0 | "She had almost laughed at the absurdity of it all; meeting Eva here of all places." | | 1 | "She tugged at the sleeve of her worn leather jacket, a defense against the cold night outside—and perhaps the memories drifting through the room." | | 2 | "Eva’s green eyes, however, were unmistakably the same—determined and sharp." |
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| 92.50% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 839 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 35 | | adverbRatio | 0.041716328963051254 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.0166865315852205 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 88 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 88 | | mean | 12.27 | | std | 6.19 | | cv | 0.504 | | sampleLengths | | 0 | 22 | | 1 | 21 | | 2 | 15 | | 3 | 16 | | 4 | 21 | | 5 | 5 | | 6 | 24 | | 7 | 11 | | 8 | 20 | | 9 | 12 | | 10 | 13 | | 11 | 15 | | 12 | 10 | | 13 | 8 | | 14 | 20 | | 15 | 21 | | 16 | 20 | | 17 | 12 | | 18 | 5 | | 19 | 4 | | 20 | 6 | | 21 | 15 | | 22 | 1 | | 23 | 6 | | 24 | 10 | | 25 | 14 | | 26 | 12 | | 27 | 10 | | 28 | 13 | | 29 | 10 | | 30 | 4 | | 31 | 6 | | 32 | 6 | | 33 | 13 | | 34 | 15 | | 35 | 9 | | 36 | 14 | | 37 | 12 | | 38 | 8 | | 39 | 21 | | 40 | 16 | | 41 | 15 | | 42 | 4 | | 43 | 16 | | 44 | 14 | | 45 | 3 | | 46 | 12 | | 47 | 7 | | 48 | 4 | | 49 | 8 |
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| 73.11% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.4659090909090909 | | totalSentences | 88 | | uniqueOpeners | 41 | |
| 96.62% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 69 | | matches | | 0 | "Then she looked up, meeting" | | 1 | "Then to Eva’s call that" |
| | ratio | 0.029 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 69 | | matches | | 0 | "She had almost laughed at" | | 1 | "Her bright blue eyes scanned" | | 2 | "She tugged at the sleeve" | | 3 | "He glanced up, his hazel" | | 4 | "he greeted, using the nickname" | | 5 | "His voice was warm, if" | | 6 | "She smiled back, though it" | | 7 | "she replied, her voice soft" | | 8 | "he asked, his tone a" | | 9 | "She offered a half-smile." | | 10 | "he said before disappearing into" | | 11 | "It was the kind of" | | 12 | "Their conversation wove through the" | | 13 | "he said, his eyes twinkling" | | 14 | "They clinked glasses, the soft" |
| | ratio | 0.217 | |
| 25.22% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 69 | | matches | | 0 | "Aurora Carter pushed open the" | | 1 | "The atmosphere inside was rich" | | 2 | "The green neon sign outside" | | 3 | "She had almost laughed at" | | 4 | "Her bright blue eyes scanned" | | 5 | "Secrets hidden in plain sight." | | 6 | "She tugged at the sleeve" | | 7 | "Silas was at the bar," | | 8 | "The dim light caught the" | | 9 | "He glanced up, his hazel" | | 10 | "he greeted, using the nickname" | | 11 | "His voice was warm, if" | | 12 | "She smiled back, though it" | | 13 | "she replied, her voice soft" | | 14 | "Silas set the glass down" | | 15 | "he asked, his tone a" | | 16 | "Rory said, her eyes searching" | | 17 | "Silas raised an eyebrow." | | 18 | "Rory’s breath caught in her" | | 19 | "The woman approaching her was" |
| | ratio | 0.87 | |
| 72.46% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 69 | | matches | | 0 | "Before Rory could respond, a" |
| | ratio | 0.014 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 1 | | matches | | 0 | "Eva sighed, her shoulders dropping as if shedding an invisible burden." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 7 | | matches | | 0 | "she replied, her voice soft but clear" | | 1 | "he asked, his tone a perfect blend of curiosity and playful concern" | | 2 | "Rory said, her eyes searching" | | 3 | "Eva said, the name sounding almost strange in her clipped, polished accent" | | 4 | "Rory replied, her voice faltering for only a heartbeat" | | 5 | "Rory asked, her voice softer, laced with an unspoken plea for honesty" | | 6 | "Rory agreed, her smile genuine this time" |
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| 61.76% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 3 | | fancyTags | | 0 | "Eva suggested (suggest)" | | 1 | "Eva whispered (whisper)" | | 2 | "Rory agreed (agree)" |
| | dialogueSentences | 34 | | tagDensity | 0.382 | | leniency | 0.765 | | rawRatio | 0.231 | | effectiveRatio | 0.176 | |