| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 49 | | tagDensity | 0.388 | | leniency | 0.776 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1381 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 92.76% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1381 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 57 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 57 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 87 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 96 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1385 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 806 | | uniqueNames | 10 | | maxNameDensity | 2.11 | | worstName | "Silas" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Marcus" | | discoveredNames | | Tuesday | 1 | | Silas | 17 | | Blackwood | 1 | | Raven | 1 | | Nest | 1 | | Prague | 1 | | Trieste | 1 | | Budapest | 1 | | Wray | 1 | | Marcus | 13 |
| | persons | | 0 | "Tuesday" | | 1 | "Silas" | | 2 | "Blackwood" | | 3 | "Wray" | | 4 | "Marcus" |
| | places | | 0 | "Raven" | | 1 | "Prague" | | 2 | "Trieste" | | 3 | "Budapest" |
| | globalScore | 0.445 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | 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 | 1385 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 87 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 31.48 | | std | 30.43 | | cv | 0.967 | | sampleLengths | | 0 | 93 | | 1 | 29 | | 2 | 39 | | 3 | 10 | | 4 | 21 | | 5 | 24 | | 6 | 71 | | 7 | 36 | | 8 | 1 | | 9 | 37 | | 10 | 3 | | 11 | 48 | | 12 | 6 | | 13 | 24 | | 14 | 13 | | 15 | 6 | | 16 | 7 | | 17 | 71 | | 18 | 30 | | 19 | 27 | | 20 | 2 | | 21 | 54 | | 22 | 5 | | 23 | 58 | | 24 | 22 | | 25 | 5 | | 26 | 15 | | 27 | 78 | | 28 | 10 | | 29 | 39 | | 30 | 4 | | 31 | 131 | | 32 | 2 | | 33 | 52 | | 34 | 3 | | 35 | 17 | | 36 | 108 | | 37 | 60 | | 38 | 35 | | 39 | 6 | | 40 | 23 | | 41 | 8 | | 42 | 1 | | 43 | 51 |
| |
| 99.11% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 57 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 129 | | matches | (empty) | |
| 11.49% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 87 | | ratio | 0.046 | | matches | | 0 | "Above the shelves, the black-and-white photographs watched the empty room — Prague in winter, Trieste harbour, a bridge in Budapest he had never named to anyone who asked." | | 1 | "He was thin in a way that had nothing to do with health — a face worn down to its architecture, a grey beard cropped close, a suit that had cost money once and kept the memory of it." | | 2 | "\"I hated it less than the alternative.\" Marcus's hand came up and wrapped the glass, and Silas saw the tremor then — a small, constant weather in the fingers." | | 3 | "Across the bar, beneath the photographs, his reflection in the mirror behind the bottles showed a man of fifty-eight with a neat beard and a ruined knee and a ring he had never once taken off, and for a moment he could not have said which of the two of them had changed more — the man in the mirror, who had built a life out of standing still, or the man on the stool, who had never once stood still and had worn himself down to the bone doing it." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 808 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.024752475247524754 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 87 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 87 | | mean | 15.92 | | std | 15.83 | | cv | 0.994 | | sampleLengths | | 0 | 15 | | 1 | 33 | | 2 | 28 | | 3 | 17 | | 4 | 4 | | 5 | 25 | | 6 | 23 | | 7 | 16 | | 8 | 6 | | 9 | 4 | | 10 | 21 | | 11 | 5 | | 12 | 19 | | 13 | 24 | | 14 | 39 | | 15 | 8 | | 16 | 9 | | 17 | 16 | | 18 | 11 | | 19 | 1 | | 20 | 15 | | 21 | 9 | | 22 | 13 | | 23 | 3 | | 24 | 24 | | 25 | 10 | | 26 | 11 | | 27 | 3 | | 28 | 6 | | 29 | 20 | | 30 | 4 | | 31 | 9 | | 32 | 4 | | 33 | 6 | | 34 | 7 | | 35 | 29 | | 36 | 5 | | 37 | 18 | | 38 | 19 | | 39 | 15 | | 40 | 15 | | 41 | 11 | | 42 | 16 | | 43 | 2 | | 44 | 9 | | 45 | 45 | | 46 | 5 | | 47 | 42 | | 48 | 5 | | 49 | 11 |
| |
| 58.24% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.39080459770114945 | | totalSentences | 87 | | uniqueOpeners | 34 | |
| 66.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 50 | | matches | | 0 | "Somewhere upstairs, water moved through" |
| | ratio | 0.02 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 50 | | matches | | 0 | "He stood behind the bar" | | 1 | "She tugged the zip up" | | 2 | "He had almost finished the" | | 3 | "He was thin in a" | | 4 | "His mouth moved around a" | | 5 | "His eyes had gone pale," | | 6 | "He lifted the glass and" | | 7 | "He drank the other half." | | 8 | "He looked up" | | 9 | "His hand did not shake," | | 10 | "He rubbed his thumb along" | | 11 | "He gestured at the maps," | | 12 | "His washed-out eyes fixed on" | | 13 | "His thumb moved over the" |
| | ratio | 0.28 | |
| 20.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 50 | | matches | | 0 | "The rain had kept the" | | 1 | "He stood behind the bar" | | 2 | "The green neon out front" | | 3 | "Aurora's footsteps crossed the ceiling," | | 4 | "She tugged the zip up" | | 5 | "Silas set the glass down" | | 6 | "The door swung shut behind" | | 7 | "Silas reached for another glass." | | 8 | "He had almost finished the" | | 9 | "The man stood in the" | | 10 | "He was thin in a" | | 11 | "Water ran off his shoulders" | | 12 | "Silas knew the limp before" | | 13 | "The man favoured his right" | | 14 | "Silas had watched that hitch" | | 15 | "Marcus Wray closed the door" | | 16 | "His mouth moved around a" | | 17 | "Marcus came forward and took" | | 18 | "His eyes had gone pale," | | 19 | "Marcus turned the signet ring" |
| | ratio | 0.88 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 50 | | matches | (empty) | | ratio | 0 | |
| 80.75% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 2 | | matches | | 0 | "Above the shelves, the black-and-white photographs watched the empty room — Prague in winter, Trieste harbour, a bridge in Budapest he had never named to anyone…" | | 1 | "Across the bar, beneath the photographs, his reflection in the mirror behind the bottles showed a man of fifty-eight with a neat beard and a ruined knee and a r…" |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "Marcus came forward (come forward)" | | 1 | "Marcus laughed (laugh)" |
| | dialogueSentences | 49 | | tagDensity | 0.122 | | leniency | 0.245 | | rawRatio | 0.333 | | effectiveRatio | 0.082 | |