| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 86 | | tagDensity | 0.174 | | leniency | 0.349 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2164 | | 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) | |
| 58.41% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2164 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "grave" | | 1 | "familiar" | | 2 | "pulse" | | 3 | "comforting" | | 4 | "trembled" | | 5 | "throbbed" | | 6 | "scanned" | | 7 | "fluttered" | | 8 | "porcelain" | | 9 | "perfect" | | 10 | "flickered" | | 11 | "stomach" | | 12 | "whisper" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 205 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 205 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 276 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2164 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 29.41% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 89 | | wordCount | 1700 | | uniqueNames | 15 | | maxNameDensity | 2.41 | | worstName | "Aurora" | | maxWindowNameDensity | 4 | | worstWindowName | "Aurora" | | discoveredNames | | Carter | 1 | | Nyx | 22 | | Heartstone | 3 | | Pendant | 1 | | Aurora | 41 | | Park | 1 | | London | 2 | | Richmond | 2 | | Hammersmith | 1 | | Cardiff | 1 | | Varga | 1 | | Seer | 3 | | Dymas | 1 | | Isolde | 6 | | One | 3 |
| | persons | | 0 | "Carter" | | 1 | "Nyx" | | 2 | "Aurora" | | 3 | "Varga" | | 4 | "Seer" | | 5 | "Dymas" | | 6 | "Isolde" | | 7 | "One" |
| | places | | 0 | "Park" | | 1 | "London" | | 2 | "Richmond" | | 3 | "Hammersmith" | | 4 | "Cardiff" |
| | globalScore | 0.294 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 128 | | glossingSentenceCount | 2 | | matches | | 0 | "as if breathing" | | 1 | "looked like polished black stone" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.462 | | wordCount | 2164 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 276 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 185 | | mean | 11.7 | | std | 12.8 | | cv | 1.095 | | sampleLengths | | 0 | 38 | | 1 | 2 | | 2 | 13 | | 3 | 4 | | 4 | 9 | | 5 | 29 | | 6 | 33 | | 7 | 27 | | 8 | 7 | | 9 | 4 | | 10 | 16 | | 11 | 5 | | 12 | 5 | | 13 | 11 | | 14 | 3 | | 15 | 1 | | 16 | 5 | | 17 | 5 | | 18 | 20 | | 19 | 59 | | 20 | 7 | | 21 | 3 | | 22 | 7 | | 23 | 7 | | 24 | 3 | | 25 | 53 | | 26 | 3 | | 27 | 11 | | 28 | 51 | | 29 | 21 | | 30 | 5 | | 31 | 5 | | 32 | 8 | | 33 | 12 | | 34 | 2 | | 35 | 6 | | 36 | 1 | | 37 | 50 | | 38 | 5 | | 39 | 4 | | 40 | 3 | | 41 | 5 | | 42 | 3 | | 43 | 6 | | 44 | 42 | | 45 | 6 | | 46 | 6 | | 47 | 3 | | 48 | 3 | | 49 | 10 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 205 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 290 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 276 | | ratio | 0 | | matches | (empty) | |
| 76.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1709 | | adjectiveStacks | 4 | | stackExamples | | 0 | "lay warm against Aurora’s" | | 1 | "white star-shaped flowers" | | 2 | "above, below, behind her" | | 3 | "beneath long wet hair." |
| | adverbCount | 48 | | adverbRatio | 0.028086600351082503 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0011702750146284377 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 276 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 276 | | mean | 7.84 | | std | 5.4 | | cv | 0.689 | | sampleLengths | | 0 | 27 | | 1 | 11 | | 2 | 2 | | 3 | 13 | | 4 | 4 | | 5 | 9 | | 6 | 8 | | 7 | 21 | | 8 | 4 | | 9 | 24 | | 10 | 5 | | 11 | 16 | | 12 | 11 | | 13 | 7 | | 14 | 4 | | 15 | 16 | | 16 | 5 | | 17 | 5 | | 18 | 11 | | 19 | 3 | | 20 | 1 | | 21 | 5 | | 22 | 5 | | 23 | 8 | | 24 | 12 | | 25 | 2 | | 26 | 22 | | 27 | 9 | | 28 | 11 | | 29 | 15 | | 30 | 7 | | 31 | 3 | | 32 | 3 | | 33 | 4 | | 34 | 7 | | 35 | 3 | | 36 | 9 | | 37 | 14 | | 38 | 3 | | 39 | 27 | | 40 | 3 | | 41 | 11 | | 42 | 13 | | 43 | 15 | | 44 | 14 | | 45 | 9 | | 46 | 8 | | 47 | 13 | | 48 | 5 | | 49 | 5 |
| |
| 47.83% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.2753623188405797 | | totalSentences | 276 | | uniqueOpeners | 76 | |
| 35.84% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 186 | | matches | | 0 | "Then the vision snapped away." | | 1 | "Then it swallowed the multitool" |
| | ratio | 0.011 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 186 | | matches | | 0 | "Its crimson centre had brightened" | | 1 | "She looked over her shoulder" | | 2 | "It sounded small and bright," | | 3 | "She stepped between the final" | | 4 | "Her ears popped." | | 5 | "Their branches looped together high" | | 6 | "Their shadow stretched across the" | | 7 | "She lifted one boot, checked" | | 8 | "It came from above, below," | | 9 | "She looked down at the" | | 10 | "It carried roasted pears, burnt" | | 11 | "She slipped it back under" | | 12 | "It circled once, then flew" | | 13 | "It dissolved beneath ferns, reappeared" | | 14 | "Their painted eyes tracked Aurora" | | 15 | "She looked at Nyx." | | 16 | "Their little ceramic throats produced" | | 17 | "Their shoulders scattered into smoke" | | 18 | "She opened the largest blade" | | 19 | "She crouched beneath the nearest" |
| | ratio | 0.242 | |
| 13.76% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 166 | | totalSentences | 186 | | matches | | 0 | "The last oak standing stone" | | 1 | "Aurora Carter pressed her palm" | | 2 | "The Heartstone Pendant lay warm" | | 3 | "Its crimson centre had brightened" | | 4 | "She looked over her shoulder" | | 5 | "Nyx stood beneath a bare" | | 6 | "Violet points watched her from" | | 7 | "Aurora held out the multitool." | | 8 | "Nyx’s silhouette bent towards it," | | 9 | "A laugh came from somewhere" | | 10 | "It sounded small and bright," | | 11 | "Richmond Park lay behind them" | | 12 | "Bluebells, foxgloves, red campion, white" | | 13 | "Frost clung to the grass" | | 14 | "The stream beside the stones" | | 15 | "Aurora’s jaw tightened." | | 16 | "She stepped between the final" | | 17 | "The air caught." | | 18 | "The next, the ground beneath" | | 19 | "Her ears popped." |
| | ratio | 0.892 | |
| 26.88% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 186 | | matches | | 0 | "By the time they reached" |
| | ratio | 0.005 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 63 | | technicalSentenceCount | 2 | | matches | | 0 | "The last oak standing stone rose from the bracken like a broken tooth, its surface ribbed with roots that had grown over it and then forgotten why." | | 1 | "It dissolved beneath ferns, reappeared in a bed of red leaves, then climbed a hill that had not existed two steps earlier." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 80.23% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 6 | | fancyTags | | 0 | "Aurora muttered (mutter)" | | 1 | "they whispered (whisper)" | | 2 | "Nyx murmured (murmur)" | | 3 | "it sang (sing)" | | 4 | "one sang (sing)" | | 5 | "Another added (add)" |
| | dialogueSentences | 86 | | tagDensity | 0.14 | | leniency | 0.279 | | rawRatio | 0.5 | | effectiveRatio | 0.14 | |