| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 1 | | adverbTags | | 0 | "Aurora said quietly [quietly]" |
| | dialogueSentences | 6 | | tagDensity | 0.667 | | leniency | 1 | | rawRatio | 0.25 | | effectiveRatio | 0.25 | |
| 84.38% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 320 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 21.88% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 320 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "flickered" | | 1 | "tracing" | | 2 | "familiar" | | 3 | "silence" | | 4 | "unspoken" |
| |
| 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 | 38 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 38 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 39 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 317 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 81.97% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 14 | | wordCount | 294 | | uniqueNames | 11 | | maxNameDensity | 1.36 | | worstName | "Marcus" | | maxWindowNameDensity | 2 | | worstWindowName | "Marcus" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Carter | 1 | | Rougher | 1 | | Marcus | 4 | | Webb | 1 | | Blackwood | 1 | | Golden | 1 | | Empress | 1 | | Cardiff | 1 | | Evan | 1 |
| | persons | | 0 | "Nest" | | 1 | "Carter" | | 2 | "Marcus" | | 3 | "Webb" | | 4 | "Blackwood" | | 5 | "Empress" | | 6 | "Evan" |
| | places | | 0 | "Raven" | | 1 | "Golden" | | 2 | "Cardiff" |
| | globalScore | 0.82 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 19 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 317 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 39 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 15 | | mean | 21.13 | | std | 14.46 | | cv | 0.684 | | sampleLengths | | 0 | 38 | | 1 | 51 | | 2 | 10 | | 3 | 8 | | 4 | 32 | | 5 | 8 | | 6 | 36 | | 7 | 4 | | 8 | 35 | | 9 | 9 | | 10 | 27 | | 11 | 12 | | 12 | 7 | | 13 | 30 | | 14 | 10 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 38 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 45 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 39 | | ratio | 0.077 | | matches | | 0 | "The bar's dim light caught the small crescent-shaped scar on her left wrist—a remnant of childhood, of things long past." | | 1 | "When she turned, Marcus Webb stood there—taller, leaner, with silver threading his dark hair where once it had been pure midnight black." | | 2 | "The silence between them was geographical—vast and unmapped, filled with the topography of years and unspoken things." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 299 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 8 | | adverbRatio | 0.026755852842809364 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.010033444816053512 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 39 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 39 | | mean | 8.13 | | std | 6.27 | | cv | 0.772 | | sampleLengths | | 0 | 16 | | 1 | 22 | | 2 | 11 | | 3 | 20 | | 4 | 20 | | 5 | 6 | | 6 | 4 | | 7 | 7 | | 8 | 1 | | 9 | 3 | | 10 | 22 | | 11 | 4 | | 12 | 3 | | 13 | 3 | | 14 | 3 | | 15 | 2 | | 16 | 11 | | 17 | 10 | | 18 | 15 | | 19 | 3 | | 20 | 1 | | 21 | 17 | | 22 | 3 | | 23 | 1 | | 24 | 14 | | 25 | 5 | | 26 | 4 | | 27 | 13 | | 28 | 8 | | 29 | 3 | | 30 | 3 | | 31 | 5 | | 32 | 7 | | 33 | 7 | | 34 | 7 | | 35 | 1 | | 36 | 6 | | 37 | 16 | | 38 | 10 |
| |
| 93.16% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5897435897435898 | | totalSentences | 39 | | uniqueOpeners | 23 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 31 | | matches | | 0 | "Away from Cardiff." | | 1 | "Away from Evan." |
| | ratio | 0.065 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 6 | | totalSentences | 31 | | matches | | 0 | "She'd been nursing the same" | | 1 | "She didn't look up." | | 2 | "Her breath caught." | | 3 | "He gestured to the empty" | | 4 | "His hazel eyes missed nothing," | | 5 | "Her delivery job at Golden" |
| | ratio | 0.194 | |
| 72.90% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 24 | | totalSentences | 31 | | matches | | 0 | "The neon green sign flickered" | | 1 | "Aurora Carter gripped her pint" | | 2 | "The bar's dim light caught" | | 3 | "She'd been nursing the same" | | 4 | "The bell above the door" | | 5 | "She didn't look up." | | 6 | "The voice was familiar, but" | | 7 | "Her breath caught." | | 8 | "The same eyes, though." | | 9 | "Those hadn't changed." | | 10 | "He gestured to the empty" | | 11 | "Silas Blackwood, the bar's owner," | | 12 | "His hazel eyes missed nothing," | | 13 | "Marcus ordered whiskey." | | 14 | "The silence between them was" | | 15 | "Marcus looked different." | | 16 | "Her delivery job at Golden" | | 17 | "The flat above this bar" | | 18 | "Marcus took a long drink." | | 19 | "The whiskey didn't seem to" |
| | ratio | 0.774 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 31 | | matches | (empty) | | ratio | 0 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 12 | | technicalSentenceCount | 1 | | matches | | 0 | "The mission that had broken something fundamental in their friendship, in their understanding of each other." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |