| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 1 | | adverbTags | | 0 | "She looked away [away]" |
| | dialogueSentences | 47 | | tagDensity | 0.191 | | leniency | 0.383 | | rawRatio | 0.111 | | effectiveRatio | 0.043 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1191 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 37.03% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1191 | | totalAiIsms | 15 | | found | | 0 | | | 1 | | | 2 | | word | "down her spine" | | count | 1 |
| | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | |
| | highlights | | 0 | "footsteps" | | 1 | "rhythmic" | | 2 | "down her spine" | | 3 | "gloom" | | 4 | "perfect" | | 5 | "unreadable" | | 6 | "traced" | | 7 | "silence" | | 8 | "determined" | | 9 | "affection" | | 10 | "calculated" | | 11 | "velvet" | | 12 | "tension" | | 13 | "glinting" | | 14 | "pulse" |
| |
| 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 | 83 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 83 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 120 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1177 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 13 | | wordCount | 762 | | uniqueNames | 7 | | maxNameDensity | 0.52 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 4 | | World | 1 | | Okayest | 1 | | Barrister | 1 | | Eva | 1 | | Lucien | 4 | | French | 1 |
| | persons | | 0 | "Aurora" | | 1 | "World" | | 2 | "Eva" | | 3 | "Lucien" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like the same thing" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1177 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 120 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 59 | | mean | 19.95 | | std | 13.62 | | cv | 0.683 | | sampleLengths | | 0 | 71 | | 1 | 14 | | 2 | 30 | | 3 | 6 | | 4 | 44 | | 5 | 16 | | 6 | 49 | | 7 | 6 | | 8 | 30 | | 9 | 12 | | 10 | 47 | | 11 | 8 | | 12 | 23 | | 13 | 43 | | 14 | 27 | | 15 | 39 | | 16 | 27 | | 17 | 9 | | 18 | 8 | | 19 | 12 | | 20 | 13 | | 21 | 23 | | 22 | 26 | | 23 | 22 | | 24 | 27 | | 25 | 18 | | 26 | 10 | | 27 | 18 | | 28 | 5 | | 29 | 12 | | 30 | 13 | | 31 | 18 | | 32 | 15 | | 33 | 40 | | 34 | 25 | | 35 | 18 | | 36 | 13 | | 37 | 33 | | 38 | 16 | | 39 | 11 | | 40 | 14 | | 41 | 27 | | 42 | 11 | | 43 | 12 | | 44 | 11 | | 45 | 44 | | 46 | 19 | | 47 | 9 | | 48 | 29 | | 49 | 28 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 83 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 132 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 120 | | ratio | 0.058 | | matches | | 0 | "She knocked aside an open book on demon linguistics, heart juddering, and snatched up the nearest heavy object—a chipped mug with faded cursive that spelled out World’s Okayest Barrister." | | 1 | "Not Eva’s knock—too rhythmic, too intentional." | | 2 | "One heterochromatic eye assessed her—amber, sly, alive." | | 3 | "She thought about arguing the point—dignity, boundaries, the entire lexicon of ex-lovers who know the shape of each other’s sharp bits." | | 4 | "His knuckles brushed her forearm—the scar—deliberate, like a confession." | | 5 | "A sharp crack cut through the tangled tension—a pane shuddered, glass scored by something metal on the fire escape." | | 6 | "It hissed—a sound halfway between prayer and threat." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 775 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.03225806451612903 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003870967741935484 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 120 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 120 | | mean | 9.81 | | std | 6.63 | | cv | 0.676 | | sampleLengths | | 0 | 13 | | 1 | 29 | | 2 | 29 | | 3 | 8 | | 4 | 6 | | 5 | 15 | | 6 | 8 | | 7 | 3 | | 8 | 4 | | 9 | 6 | | 10 | 7 | | 11 | 9 | | 12 | 28 | | 13 | 10 | | 14 | 6 | | 15 | 28 | | 16 | 8 | | 17 | 7 | | 18 | 6 | | 19 | 6 | | 20 | 10 | | 21 | 20 | | 22 | 5 | | 23 | 4 | | 24 | 3 | | 25 | 15 | | 26 | 26 | | 27 | 6 | | 28 | 8 | | 29 | 9 | | 30 | 14 | | 31 | 6 | | 32 | 32 | | 33 | 5 | | 34 | 11 | | 35 | 16 | | 36 | 5 | | 37 | 27 | | 38 | 7 | | 39 | 21 | | 40 | 6 | | 41 | 5 | | 42 | 4 | | 43 | 5 | | 44 | 3 | | 45 | 7 | | 46 | 5 | | 47 | 4 | | 48 | 9 | | 49 | 18 |
| |
| 58.06% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.38333333333333336 | | totalSentences | 120 | | uniqueOpeners | 46 | |
| 42.19% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 79 | | matches | | 0 | "Instead, she pressed him with" |
| | ratio | 0.013 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 79 | | matches | | 0 | "She knocked aside an open" | | 1 | "She edged the door open" | | 2 | "Her gaze shot to each" | | 3 | "She’d imagined it at her" | | 4 | "She let out her breath" | | 5 | "He stepped into the hall’s" | | 6 | "She sucked her teeth, hand" | | 7 | "She stood aside in a" | | 8 | "He barely glanced at the" | | 9 | "His gaze slid right to" | | 10 | "She set the mug down" | | 11 | "He made a soft, dismissive" | | 12 | "His scarf flared as he" | | 13 | "She flinched at the old" | | 14 | "He chuckled, low and knowing." | | 15 | "His hand swept over the" | | 16 | "She thought about arguing the" | | 17 | "She sat, instead, knees locked" | | 18 | "She laughed, short and hard." | | 19 | "She rolled her eyes." |
| | ratio | 0.57 | |
| 16.96% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 79 | | matches | | 0 | "The clatter from behind the" | | 1 | "She knocked aside an open" | | 2 | "The cat bolted under the" | | 3 | "The knock came again, knuckles" | | 4 | "She edged the door open" | | 5 | "Her gaze shot to each" | | 6 | "Security layered, as always." | | 7 | "The voice sent a hot-cold" | | 8 | "She’d imagined it at her" | | 9 | "She let out her breath" | | 10 | "He stepped into the hall’s" | | 11 | "The ivory-handled cane tap-tapped once" | | 12 | "The other, black as pitch," | | 13 | "She sucked her teeth, hand" | | 14 | "Something in his mouth twitched." | | 15 | "She stood aside in a" | | 16 | "He barely glanced at the" | | 17 | "His gaze slid right to" | | 18 | "The air contracted between them," | | 19 | "She set the mug down" |
| | ratio | 0.886 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 79 | | matches | (empty) | | ratio | 0 | |
| 53.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 3 | | matches | | 0 | "The cat bolted under the sofa as she crept forward, breathing sharp in her ears, trying to keep her footsteps masked by the rattle of curry house pans downstair…" | | 1 | "He stepped into the hall’s sodium gloom, impeccable in his usual charcoal suit, platinum hair swept back as if not a single perfect strand would dare betray him…" | | 2 | "She thought about arguing the point—dignity, boundaries, the entire lexicon of ex-lovers who know the shape of each other’s sharp bits." |
| |
| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 1 | | matches | | 0 | "She flexed, the crescent scar itching" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 47 | | tagDensity | 0.043 | | leniency | 0.085 | | rawRatio | 0.5 | | effectiveRatio | 0.043 | |