| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said finally [finally]" | | 1 | "Silas said quietly [quietly]" |
| | dialogueSentences | 69 | | tagDensity | 0.319 | | leniency | 0.638 | | rawRatio | 0.091 | | effectiveRatio | 0.058 | |
| 83.29% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1197 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "softly" | | 1 | "really" | | 2 | "slightly" |
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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) | |
| 41.52% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1197 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "pulsed" | | 1 | "beacon" | | 2 | "silence" | | 3 | "familiar" | | 4 | "throb" | | 5 | "chill" | | 6 | "scanning" | | 7 | "velvet" | | 8 | "traced" | | 9 | "weight" | | 10 | "unspoken" | | 11 | "flickered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 85 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 85 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 132 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1185 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 30 | | unquotedAttributions | 0 | | matches | (empty) | |
| 93.10% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 703 | | uniqueNames | 12 | | maxNameDensity | 1.14 | | worstName | "Silas" | | maxWindowNameDensity | 2 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Chet | 1 | | Baker | 1 | | Silas | 8 | | Blackwood | 1 | | Rory | 3 | | Prague | 1 | | Charles | 1 | | Bridge | 1 | | Silence | 2 |
| | persons | | 0 | "Raven" | | 1 | "Chet" | | 2 | "Baker" | | 3 | "Silas" | | 4 | "Blackwood" | | 5 | "Rory" | | 6 | "Silence" |
| | places | | 0 | "Soho" | | 1 | "Prague" | | 2 | "Charles" | | 3 | "Bridge" |
| | globalScore | 0.931 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.844 | | wordCount | 1185 | | matches | | 0 | "not touching but close" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 132 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 73 | | mean | 16.23 | | std | 17.45 | | cv | 1.075 | | sampleLengths | | 0 | 109 | | 1 | 16 | | 2 | 58 | | 3 | 24 | | 4 | 24 | | 5 | 17 | | 6 | 21 | | 7 | 43 | | 8 | 10 | | 9 | 4 | | 10 | 15 | | 11 | 49 | | 12 | 6 | | 13 | 2 | | 14 | 4 | | 15 | 5 | | 16 | 27 | | 17 | 10 | | 18 | 9 | | 19 | 33 | | 20 | 6 | | 21 | 7 | | 22 | 5 | | 23 | 21 | | 24 | 3 | | 25 | 6 | | 26 | 14 | | 27 | 6 | | 28 | 12 | | 29 | 11 | | 30 | 8 | | 31 | 14 | | 32 | 62 | | 33 | 7 | | 34 | 5 | | 35 | 2 | | 36 | 33 | | 37 | 2 | | 38 | 6 | | 39 | 21 | | 40 | 14 | | 41 | 4 | | 42 | 6 | | 43 | 1 | | 44 | 3 | | 45 | 9 | | 46 | 12 | | 47 | 31 | | 48 | 6 | | 49 | 9 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 85 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 123 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 132 | | ratio | 0.061 | | matches | | 0 | "Inside, the bar breathed in low murmurs and the crackle of vinyl—Chet Baker, maybe, or someone aping his melancholy." | | 1 | "She paused, scanning the room with bright blue eyes—sharp, assessing, like she wasn’t just looking for a seat but measuring the air itself." | | 2 | "As he poured the bourbon—neat, no ice—his gaze lingered on her left wrist." | | 3 | "This was the kind that knows each other too well—worn in like the grooves of the floor beneath boots and time." | | 4 | "A new song, softer—piano, distant strings." | | 5 | "He knew what that invitation carried—the weight of unspoken apologies, the guilt of absence, the fear of reopening doors best left shut." | | 6 | "She looked at his hand—the signet ring, the scar across his knuckle, the quiet strength in his fingers." | | 7 | "Somewhere beyond the shelves, a door clicked shut in the secret room—someone leaving, or arriving." |
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| 88.78% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 718 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 33 | | adverbRatio | 0.04596100278551532 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.011142061281337047 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 132 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 132 | | mean | 8.98 | | std | 7.55 | | cv | 0.841 | | sampleLengths | | 0 | 27 | | 1 | 19 | | 2 | 25 | | 3 | 22 | | 4 | 16 | | 5 | 16 | | 6 | 17 | | 7 | 18 | | 8 | 23 | | 9 | 6 | | 10 | 18 | | 11 | 7 | | 12 | 17 | | 13 | 5 | | 14 | 11 | | 15 | 1 | | 16 | 7 | | 17 | 14 | | 18 | 13 | | 19 | 13 | | 20 | 13 | | 21 | 4 | | 22 | 9 | | 23 | 1 | | 24 | 4 | | 25 | 12 | | 26 | 3 | | 27 | 3 | | 28 | 8 | | 29 | 19 | | 30 | 12 | | 31 | 4 | | 32 | 3 | | 33 | 6 | | 34 | 2 | | 35 | 4 | | 36 | 2 | | 37 | 3 | | 38 | 3 | | 39 | 1 | | 40 | 13 | | 41 | 10 | | 42 | 10 | | 43 | 6 | | 44 | 3 | | 45 | 12 | | 46 | 21 | | 47 | 6 | | 48 | 7 | | 49 | 3 |
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| 54.55% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.36363636363636365 | | totalSentences | 132 | | uniqueOpeners | 48 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 66 | | matches | | 0 | "Instead, she asked," | | 1 | "Then she placed her palm" | | 2 | "Somewhere beyond the shelves, a" |
| | ratio | 0.045 | |
| 20.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 66 | | matches | | 0 | "His knee ached tonight, a" | | 1 | "She stepped in, shoulders hunched" | | 2 | "Her leather jacket was worn" | | 3 | "She paused, scanning the room" | | 4 | "he asked, voice low, rough" | | 5 | "He gestured to her usual" | | 6 | "She nodded, sliding onto the" | | 7 | "He remembered the story: a" | | 8 | "She took the glass, fingers" | | 9 | "She exhaled, long and slow," | | 10 | "He leaned back, watching her" | | 11 | "Her eyes paused on the" | | 12 | "He’d hung it there years" | | 13 | "She noticed everything now." | | 14 | "She hadn’t before." | | 15 | "she said finally" | | 16 | "She almost smiled." | | 17 | "She looked down at her" | | 18 | "Her brow lifted." | | 19 | "He didn’t flinch." |
| | ratio | 0.5 | |
| 81.21% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 50 | | totalSentences | 66 | | matches | | 0 | "The green neon glow of" | | 1 | "The air was thick with" | | 2 | "His knee ached tonight, a" | | 3 | "The door opened with a" | | 4 | "She stepped in, shoulders hunched" | | 5 | "Her leather jacket was worn" | | 6 | "She paused, scanning the room" | | 7 | "Silas didn’t look up right" | | 8 | "he asked, voice low, rough" | | 9 | "Rory closed the door softly" | | 10 | "Silas finally raised his eyes." | | 11 | "He gestured to her usual" | | 12 | "She nodded, sliding onto the" | | 13 | "The small crescent-shaped scar peeked" | | 14 | "He remembered the story: a" | | 15 | "She took the glass, fingers" | | 16 | "She exhaled, long and slow," | | 17 | "Silas didn’t press." | | 18 | "He leaned back, watching her" | | 19 | "Her eyes paused on the" |
| | ratio | 0.758 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 66 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 1 | | matches | | 0 | "His knee ached tonight, a familiar throb that kept time with the rain against the windows." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 1 | | matches | | 0 | "She took, fingers brushing his" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 18 | | fancyCount | 2 | | fancyTags | | 0 | "she agreed (agree)" | | 1 | "she whispered (whisper)" |
| | dialogueSentences | 69 | | tagDensity | 0.261 | | leniency | 0.522 | | rawRatio | 0.111 | | effectiveRatio | 0.058 | |