| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1948 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 94.87% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1948 | | 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 | 0 | | narrationSentences | 115 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 115 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 286 | | 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 | 1948 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 83 | | wordCount | 1125 | | uniqueNames | 8 | | maxNameDensity | 3.2 | | worstName | "Nia" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Nia" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Silas | 7 | | Price | 1 | | Baltic | 1 | | Rory | 34 | | Nia | 36 | | Evan | 2 |
| | persons | | 0 | "Silas" | | 1 | "Price" | | 2 | "Rory" | | 3 | "Nia" | | 4 | "Evan" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 85 | | 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 | 1948 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 286 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 237 | | mean | 8.22 | | std | 10.16 | | cv | 1.236 | | sampleLengths | | 0 | 49 | | 1 | 4 | | 2 | 9 | | 3 | 3 | | 4 | 7 | | 5 | 3 | | 6 | 39 | | 7 | 6 | | 8 | 6 | | 9 | 19 | | 10 | 8 | | 11 | 1 | | 12 | 48 | | 13 | 1 | | 14 | 56 | | 15 | 9 | | 16 | 3 | | 17 | 11 | | 18 | 5 | | 19 | 18 | | 20 | 4 | | 21 | 5 | | 22 | 2 | | 23 | 1 | | 24 | 7 | | 25 | 4 | | 26 | 3 | | 27 | 2 | | 28 | 31 | | 29 | 6 | | 30 | 2 | | 31 | 30 | | 32 | 7 | | 33 | 2 | | 34 | 8 | | 35 | 5 | | 36 | 7 | | 37 | 3 | | 38 | 2 | | 39 | 35 | | 40 | 8 | | 41 | 3 | | 42 | 11 | | 43 | 2 | | 44 | 2 | | 45 | 4 | | 46 | 9 | | 47 | 5 | | 48 | 10 | | 49 | 15 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 115 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 186 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 286 | | ratio | 0.003 | | matches | | 0 | "His left knee caught as he turned towards the sink; he shifted his weight without touching the counter." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1126 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.018650088809946713 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 286 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 286 | | mean | 6.81 | | std | 5.46 | | cv | 0.802 | | sampleLengths | | 0 | 18 | | 1 | 8 | | 2 | 23 | | 3 | 4 | | 4 | 9 | | 5 | 3 | | 6 | 7 | | 7 | 3 | | 8 | 5 | | 9 | 14 | | 10 | 9 | | 11 | 11 | | 12 | 6 | | 13 | 6 | | 14 | 7 | | 15 | 12 | | 16 | 8 | | 17 | 1 | | 18 | 7 | | 19 | 13 | | 20 | 28 | | 21 | 1 | | 22 | 13 | | 23 | 21 | | 24 | 9 | | 25 | 13 | | 26 | 5 | | 27 | 4 | | 28 | 3 | | 29 | 11 | | 30 | 5 | | 31 | 18 | | 32 | 4 | | 33 | 5 | | 34 | 2 | | 35 | 1 | | 36 | 7 | | 37 | 4 | | 38 | 3 | | 39 | 2 | | 40 | 5 | | 41 | 18 | | 42 | 8 | | 43 | 6 | | 44 | 2 | | 45 | 5 | | 46 | 25 | | 47 | 7 | | 48 | 2 | | 49 | 8 |
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| 46.85% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.23776223776223776 | | totalSentences | 286 | | uniqueOpeners | 68 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 112 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 112 | | matches | | 0 | "His silver signet ring held" | | 1 | "She knew the voice before" | | 2 | "Her hair, once a red" | | 3 | "She wore a charcoal suit" | | 4 | "Her mouth made the old" | | 5 | "He took down two glasses." | | 6 | "His left knee caught as" | | 7 | "They stood with the empty" | | 8 | "They chose opposite chairs, as" | | 9 | "She had wrapped a belt" | | 10 | "She pressed her lips together," | | 11 | "She remembered sitting on their" | | 12 | "She could hear where the" | | 13 | "Her coat slid from the" | | 14 | "He set each one on" | | 15 | "She had rehearsed arguments for" | | 16 | "She wanted some visible remnant" | | 17 | "Her jacket stuck to the" | | 18 | "He gave up and carried" | | 19 | "He lifted the bottle." |
| | ratio | 0.179 | |
| 0.18% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 103 | | totalSentences | 112 | | matches | | 0 | "Rory carried the empty delivery" | | 1 | "Rain had darkened the shoulders" | | 2 | "Rory pushed the door with" | | 3 | "The woman followed her inside." | | 4 | "Rory heard the click of" | | 5 | "His silver signet ring held" | | 6 | "Rory lifted the bags onto" | | 7 | "Water slid from her cuff" | | 8 | "She knew the voice before" | | 9 | "The second syllable lifted, as" | | 10 | "Nia Price stood beside a" | | 11 | "Her hair, once a red" | | 12 | "She wore a charcoal suit" | | 13 | "A pale band marked the" | | 14 | "Rory looked at her shoes." | | 15 | "Nia followed her glance." | | 16 | "Her mouth made the old" | | 17 | "Silas closed the ledger." | | 18 | "Nia looked at the bottles" | | 19 | "He took down two glasses." |
| | ratio | 0.92 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 112 | | matches | (empty) | | ratio | 0 | |
| 94.16% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 3 | | matches | | 0 | "Six years before, that voice had travelled through thin bedroom walls, shouted over boiling kettles, demanded a second verse from musicians who had begun packin…" | | 1 | "She had rehearsed arguments for this admission while walking to lectures, while washing plates, while sitting beside Evan on the bus with his hand gripping her …" | | 2 | "Rory looked at the woman opposite her: the clipped hair, the good coat with a frayed buttonhole, the hands that had once hauled a violin case and now lay flat o…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |