| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said instead [instead]" |
| | dialogueSentences | 27 | | tagDensity | 0.407 | | leniency | 0.815 | | rawRatio | 0.091 | | effectiveRatio | 0.074 | |
| 97.18% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1775 | | 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) | |
| 57.75% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1775 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "scanning" | | 1 | "glinting" | | 2 | "flicker" | | 3 | "measured" | | 4 | "traced" | | 5 | "silence" | | 6 | "warmth" | | 7 | "weight" | | 8 | "could feel" | | 9 | "reminder" |
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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 | 1 | | narrationSentences | 72 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 72 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 89 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 69 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1775 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 1197 | | uniqueNames | 10 | | maxNameDensity | 1.5 | | worstName | "Aurora" | | maxWindowNameDensity | 3 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Europe | 1 | | Middle | 1 | | East | 1 | | Blackwood | 1 | | Aurora | 18 | | Eva | 17 | | Silas | 4 | | Cardiff | 1 |
| | persons | | 0 | "Raven" | | 1 | "East" | | 2 | "Blackwood" | | 3 | "Aurora" | | 4 | "Eva" | | 5 | "Silas" |
| | places | | 0 | "Europe" | | 1 | "Middle" | | 2 | "Cardiff" |
| | globalScore | 0.748 | | windowScore | 0.667 | |
| 65.25% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like a whiskey, her shoulders squa" | | 1 | "looked like someone who measured every ho" |
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| 87.32% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.127 | | wordCount | 1775 | | matches | | 0 | "not anger, not even simple sadness, but the heavier awareness" | | 1 | "not even simple sadness, but the heavier awareness" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 89 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 59.17 | | std | 37.09 | | cv | 0.627 | | sampleLengths | | 0 | 130 | | 1 | 99 | | 2 | 12 | | 3 | 19 | | 4 | 54 | | 5 | 79 | | 6 | 1 | | 7 | 28 | | 8 | 1 | | 9 | 117 | | 10 | 25 | | 11 | 57 | | 12 | 106 | | 13 | 49 | | 14 | 33 | | 15 | 104 | | 16 | 56 | | 17 | 22 | | 18 | 57 | | 19 | 71 | | 20 | 59 | | 21 | 99 | | 22 | 54 | | 23 | 88 | | 24 | 93 | | 25 | 36 | | 26 | 11 | | 27 | 36 | | 28 | 52 | | 29 | 127 |
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| 90.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 72 | | matches | | 0 | "were gone" | | 1 | "being asked" | | 2 | "been was" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 196 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 89 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1005 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 33 | | adverbRatio | 0.03283582089552239 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006965174129353234 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 89 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 89 | | mean | 19.94 | | std | 13.73 | | cv | 0.688 | | sampleLengths | | 0 | 30 | | 1 | 25 | | 2 | 37 | | 3 | 38 | | 4 | 16 | | 5 | 20 | | 6 | 28 | | 7 | 35 | | 8 | 4 | | 9 | 8 | | 10 | 11 | | 11 | 8 | | 12 | 8 | | 13 | 21 | | 14 | 25 | | 15 | 9 | | 16 | 30 | | 17 | 21 | | 18 | 19 | | 19 | 1 | | 20 | 6 | | 21 | 22 | | 22 | 1 | | 23 | 5 | | 24 | 14 | | 25 | 17 | | 26 | 24 | | 27 | 19 | | 28 | 30 | | 29 | 8 | | 30 | 10 | | 31 | 15 | | 32 | 11 | | 33 | 46 | | 34 | 12 | | 35 | 58 | | 36 | 36 | | 37 | 7 | | 38 | 42 | | 39 | 6 | | 40 | 14 | | 41 | 13 | | 42 | 18 | | 43 | 19 | | 44 | 37 | | 45 | 30 | | 46 | 26 | | 47 | 30 | | 48 | 4 | | 49 | 18 |
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| 52.81% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.33707865168539325 | | totalSentences | 89 | | uniqueOpeners | 30 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 90.59% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 68 | | matches | | 0 | "She paused just inside, her" | | 1 | "He carried the faint hitch" | | 2 | "He saw her coming and" | | 3 | "She took a stool." | | 4 | "He poured without ceremony, setting" | | 5 | "Her left wrist rested on" | | 6 | "She turned the glass stem" | | 7 | "They met in the middle." | | 8 | "She looked like someone who" | | 9 | "She kept the word neutral," | | 10 | "She did not add that" | | 11 | "She traced the scar on" | | 12 | "He caught her eye once," | | 13 | "She gave a small shake" | | 14 | "She paused, and the next" | | 15 | "she said instead" | | 16 | "They sat with that for" | | 17 | "She smoothed her blouse with" | | 18 | "They did not hug again." | | 19 | "He did not ask what" |
| | ratio | 0.324 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 68 | | matches | | 0 | "Aurora pushed through the heavy" | | 1 | "The bar settled around her" | | 2 | "She paused just inside, her" | | 3 | "Silas Blackwood stood behind the" | | 4 | "The grey streaks in his" | | 5 | "He carried the faint hitch" | | 6 | "He saw her coming and" | | 7 | "She took a stool." | | 8 | "He poured without ceremony, setting" | | 9 | "Her left wrist rested on" | | 10 | "She turned the glass stem" | | 11 | "A movement at a corner" | | 12 | "A woman sat alone, nursing" | | 13 | "Something in the line of" | | 14 | "The woman glanced up, and" | | 15 | "The name came out low," | | 16 | "Aurora set her glass down" | | 17 | "They met in the middle." | | 18 | "The embrace was brief, shoulders" | | 19 | "The curls that once reached" |
| | ratio | 0.956 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 15.87% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 8 | | matches | | 0 | "The grey streaks in his auburn hair caught the lamp light, matching the neatly trimmed beard that shadowed his jaw." | | 1 | "He saw her coming and gave a short nod, the kind he reserved for regulars who paid their tabs on time and asked no questions about the back rooms or the stories…" | | 2 | "The cool calm she kept in her voice now was a skill earned in the months that followed, a way of narrating her own life without inviting questions that led to p…" | | 3 | "This Eva held her posture as if every breath required calculation, as if the woman she had been was something she had put into storage along with her old passpo…" | | 4 | "He caught her eye once, a neutral check that asked nothing and offered no more than the possibility of another glass if she needed it." | | 5 | "Eva's shoulders lifted in a small shrug that looked smaller than the one the younger version would have given." | | 6 | "The photographs on the wall seemed to watch them, anonymous witnesses to other conversations that had started in hope and ended in the same measured silence." | | 7 | "She traced the rim of the glass and tried to name the feeling that remained after Eva's changed figure had disappeared into the street: not anger, not even simp…" |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | 0 | "Eva continued, voice lower now" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 1 | | fancyTags | | 0 | "Eva continued (continue)" |
| | dialogueSentences | 27 | | tagDensity | 0.296 | | leniency | 0.593 | | rawRatio | 0.125 | | effectiveRatio | 0.074 | |