| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "Her voice landed unevenly [unevenly]" | | 1 | "Carys’s words came fast [fast]" |
| | dialogueSentences | 61 | | tagDensity | 0.213 | | leniency | 0.426 | | rawRatio | 0.154 | | effectiveRatio | 0.066 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1299 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 57.66% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1299 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "pulsed" | | 1 | "flickered" | | 2 | "traced" | | 3 | "flicker" | | 4 | "silence" | | 5 | "trembled" | | 6 | "flicked" | | 7 | "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 | 149 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 149 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 194 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 22 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1290 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 88 | | wordCount | 969 | | uniqueNames | 10 | | maxNameDensity | 4.13 | | worstName | "Aurora" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 40 | | Nest | 1 | | Soho | 1 | | Prague | 3 | | Cairo | 1 | | Seoul | 1 | | Silas | 7 | | Soft | 1 | | Carys | 32 | | Showed | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Silas" | | 2 | "Carys" |
| | places | | 0 | "Nest" | | 1 | "Soho" | | 2 | "Prague" | | 3 | "Cairo" | | 4 | "Seoul" |
| | globalScore | 0 | | windowScore | 0 | |
| 86.71% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 79 | | glossingSentenceCount | 2 | | matches | | 0 | "as if seeing the scar for the first time" | | 1 | "felt like a promise written in flesh" |
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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 | 1290 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 194 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 68 | | mean | 18.97 | | std | 13.5 | | cv | 0.712 | | sampleLengths | | 0 | 85 | | 1 | 43 | | 2 | 67 | | 3 | 13 | | 4 | 13 | | 5 | 21 | | 6 | 19 | | 7 | 24 | | 8 | 7 | | 9 | 8 | | 10 | 13 | | 11 | 9 | | 12 | 27 | | 13 | 14 | | 14 | 28 | | 15 | 10 | | 16 | 18 | | 17 | 16 | | 18 | 16 | | 19 | 28 | | 20 | 29 | | 21 | 22 | | 22 | 2 | | 23 | 10 | | 24 | 14 | | 25 | 16 | | 26 | 40 | | 27 | 14 | | 28 | 4 | | 29 | 29 | | 30 | 19 | | 31 | 7 | | 32 | 21 | | 33 | 27 | | 34 | 24 | | 35 | 18 | | 36 | 15 | | 37 | 19 | | 38 | 25 | | 39 | 10 | | 40 | 6 | | 41 | 9 | | 42 | 10 | | 43 | 10 | | 44 | 33 | | 45 | 20 | | 46 | 12 | | 47 | 11 | | 48 | 13 | | 49 | 35 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 149 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 186 | | matches | (empty) | |
| 39.76% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 194 | | ratio | 0.036 | | matches | | 0 | "Walls bore brittle maps of Prague, Cairo, Seoul—wherever Silas had once slipped in and out of shadow." | | 1 | "Soft—but it cut the distance in half." | | 2 | "Sunken light in Carys’s eyes glinted—like seeing the wrong side of a mirror." | | 3 | "Aurora let her gaze drift to the photos—Silas in Prague, flanked by operatives with dead-eyes." | | 4 | "The scar peeped from beneath her sleeve—a pale crescent, silent witness." | | 5 | "The apology had edges—a blade sharpened on regret." | | 6 | "Carys smiled—real this time." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 978 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.027607361963190184 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003067484662576687 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 194 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 194 | | mean | 6.65 | | std | 4.12 | | cv | 0.62 | | sampleLengths | | 0 | 21 | | 1 | 10 | | 2 | 8 | | 3 | 17 | | 4 | 19 | | 5 | 10 | | 6 | 5 | | 7 | 14 | | 8 | 5 | | 9 | 3 | | 10 | 7 | | 11 | 9 | | 12 | 10 | | 13 | 14 | | 14 | 11 | | 15 | 9 | | 16 | 17 | | 17 | 2 | | 18 | 2 | | 19 | 2 | | 20 | 4 | | 21 | 5 | | 22 | 4 | | 23 | 6 | | 24 | 7 | | 25 | 10 | | 26 | 3 | | 27 | 2 | | 28 | 2 | | 29 | 4 | | 30 | 5 | | 31 | 7 | | 32 | 7 | | 33 | 4 | | 34 | 7 | | 35 | 13 | | 36 | 7 | | 37 | 2 | | 38 | 3 | | 39 | 3 | | 40 | 7 | | 41 | 6 | | 42 | 5 | | 43 | 4 | | 44 | 2 | | 45 | 12 | | 46 | 5 | | 47 | 8 | | 48 | 7 | | 49 | 7 |
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| 50.17% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.31958762886597936 | | totalSentences | 194 | | uniqueOpeners | 62 | |
| 49.75% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 134 | | matches | | 0 | "Then she turned." | | 1 | "Then she said," |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 134 | | matches | | 0 | "She recognized that dry curve" | | 1 | "He glanced up, paused on" | | 2 | "Her boots scuffed the floorboards." | | 3 | "Her voice landed unevenly" | | 4 | "She stood so fast the" | | 5 | "She smoothed her skirt and" | | 6 | "They settled onto stools side" | | 7 | "He limped back to the" | | 8 | "She traced tiny whirlpools in" | | 9 | "She wrapped both hands around" | | 10 | "She bent forward." | | 11 | "She glanced at her wrist." | | 12 | "She shook her head" | | 13 | "Her hair caught the lamplight," | | 14 | "She remembered the operation Silas" | | 15 | "She turned back to Carys." | | 16 | "She stared at Aurora as" | | 17 | "She felt small for a" | | 18 | "She pictured the wedding announcement" | | 19 | "She blinked twice." |
| | ratio | 0.231 | |
| 34.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 114 | | totalSentences | 134 | | matches | | 0 | "The green neon above the" | | 1 | "The door thunked shut behind" | | 2 | "Smoke drifted in low ribbons" | | 3 | "Walls bore brittle maps of" | | 4 | "The bar’s hush folded around" | | 5 | "Aurora paused at the threshold." | | 6 | "The stool at the far" | | 7 | "Glass sweating on polished wood." | | 8 | "A woman’s back." | | 9 | "She recognized that dry curve" | | 10 | "Aurora tightened the strap of" | | 11 | "The bar hummed on either" | | 12 | "Silas stood behind the bar," | | 13 | "He glanced up, paused on" | | 14 | "Aurora cleared her throat." | | 15 | "Her boots scuffed the floorboards." | | 16 | "The woman didn’t turn." | | 17 | "A name from another life" | | 18 | "The woman’s hand froze at" | | 19 | "A breath of surprise." |
| | ratio | 0.851 | |
| 37.31% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 134 | | matches | | | ratio | 0.007 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 61 | | tagDensity | 0.049 | | leniency | 0.098 | | rawRatio | 0 | | effectiveRatio | 0 | |