| 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 | 2037 | | 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) | |
| 90.18% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2037 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "mechanical" | | 1 | "weight" | | 2 | "glint" |
| |
| 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 | 91 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 91 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 159 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 95 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2037 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 902 | | uniqueNames | 9 | | maxNameDensity | 0.67 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Golden | 1 | | Empress | 1 | | Blackwood | 1 | | Cardiff | 2 | | Baltic | 2 | | Rory | 6 | | Silas | 5 |
| | persons | | 0 | "Raven" | | 1 | "Blackwood" | | 2 | "Rory" | | 3 | "Silas" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | 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 | 2037 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 159 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 103 | | mean | 19.78 | | std | 17.65 | | cv | 0.892 | | sampleLengths | | 0 | 65 | | 1 | 41 | | 2 | 61 | | 3 | 13 | | 4 | 23 | | 5 | 1 | | 6 | 3 | | 7 | 19 | | 8 | 4 | | 9 | 39 | | 10 | 1 | | 11 | 22 | | 12 | 4 | | 13 | 26 | | 14 | 35 | | 15 | 16 | | 16 | 9 | | 17 | 24 | | 18 | 13 | | 19 | 4 | | 20 | 6 | | 21 | 69 | | 22 | 18 | | 23 | 37 | | 24 | 36 | | 25 | 1 | | 26 | 1 | | 27 | 14 | | 28 | 2 | | 29 | 49 | | 30 | 12 | | 31 | 15 | | 32 | 12 | | 33 | 43 | | 34 | 5 | | 35 | 25 | | 36 | 25 | | 37 | 11 | | 38 | 25 | | 39 | 2 | | 40 | 11 | | 41 | 3 | | 42 | 10 | | 43 | 66 | | 44 | 12 | | 45 | 4 | | 46 | 22 | | 47 | 8 | | 48 | 41 | | 49 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 91 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 140 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 159 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 906 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 11 | | adverbRatio | 0.012141280353200883 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 159 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 159 | | mean | 12.81 | | std | 12.18 | | cv | 0.951 | | sampleLengths | | 0 | 11 | | 1 | 28 | | 2 | 6 | | 3 | 10 | | 4 | 10 | | 5 | 8 | | 6 | 16 | | 7 | 12 | | 8 | 5 | | 9 | 27 | | 10 | 8 | | 11 | 7 | | 12 | 19 | | 13 | 4 | | 14 | 9 | | 15 | 7 | | 16 | 16 | | 17 | 1 | | 18 | 3 | | 19 | 11 | | 20 | 8 | | 21 | 4 | | 22 | 6 | | 23 | 11 | | 24 | 22 | | 25 | 1 | | 26 | 22 | | 27 | 4 | | 28 | 26 | | 29 | 3 | | 30 | 3 | | 31 | 15 | | 32 | 8 | | 33 | 6 | | 34 | 16 | | 35 | 9 | | 36 | 24 | | 37 | 13 | | 38 | 4 | | 39 | 6 | | 40 | 5 | | 41 | 15 | | 42 | 4 | | 43 | 15 | | 44 | 7 | | 45 | 23 | | 46 | 18 | | 47 | 7 | | 48 | 4 | | 49 | 26 |
| |
| 55.56% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3710691823899371 | | totalSentences | 159 | | uniqueOpeners | 59 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 91 | | matches | (empty) | | ratio | 0 | |
| 61.76% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 91 | | matches | | 0 | "She set the bag by" | | 1 | "She took a stool and" | | 2 | "He looked at the scar," | | 3 | "His mouth moved." | | 4 | "He took down a bottle" | | 5 | "She left it where it" | | 6 | "He came down the bar." | | 7 | "He halted opposite her." | | 8 | "He took his place behind" | | 9 | "She turned her glass a" | | 10 | "His glance took the delivery" | | 11 | "He set his right hand" | | 12 | "She put no city to" | | 13 | "He offered none." | | 14 | "He set the pint down," | | 15 | "He drew a second glass" | | 16 | "He drank standing, weight on" | | 17 | "Her fingers stayed loose around" | | 18 | "He studied the rings her" | | 19 | "His eyes came up level" |
| | ratio | 0.396 | |
| 20.44% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 80 | | totalSentences | 91 | | matches | | 0 | "Rory shouldered in, insulated bag" | | 1 | "The bar held its dark" | | 2 | "She set the bag by" | | 3 | "Ginger and hot oil clung" | | 4 | "A man stood at the" | | 5 | "Auburn hair had gone grey" | | 6 | "The beard followed the jaw," | | 7 | "Hazel eyes found her." | | 8 | "The cloth stopped in the" | | 9 | "Rory left her hand on" | | 10 | "She took a stool and" | | 11 | "The crescent scar showed pale" | | 12 | "Silas Blackwood set the glass" | | 13 | "The silver signet on his" | | 14 | "He looked at the scar," | | 15 | "The voice carried the low" | | 16 | "His mouth moved." | | 17 | "He took down a bottle" | | 18 | "The glass travelled to her" | | 19 | "She left it where it" |
| | ratio | 0.879 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 91 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | |