| 82.35% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 3 | | adverbTags | | 0 | "she asked eventually [eventually]" | | 1 | "He gestured vaguely [vaguely]" | | 2 | "He turned back [back]" |
| | dialogueSentences | 51 | | tagDensity | 0.451 | | leniency | 0.902 | | rawRatio | 0.13 | | effectiveRatio | 0.118 | |
| 95.55% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1123 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 82.19% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1123 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "weight" | | 1 | "comfortable" | | 2 | "flickered" | | 3 | "silence" |
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| 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 | 48 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 48 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 77 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 73 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 16 | | totalWords | 1121 | | ratio | 0.014 | | matches | | 0 | "I saw that, and I'm sorry, and there's nothing either of us can do about it." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 17 | | wordCount | 804 | | uniqueNames | 8 | | maxNameDensity | 0.5 | | worstName | "Silas" | | maxWindowNameDensity | 1 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 2 | | Golden | 1 | | Empress | 1 | | Cardiff | 2 | | Silas | 4 | | Tommy | 3 | | Rory | 3 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Tommy" | | 4 | "Rory" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 33.72% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 2 | | matches | | 0 | "not quite a smile" | | 1 | "tant now as he apparently felt from himself" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1121 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 77 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 24.37 | | std | 20.95 | | cv | 0.86 | | sampleLengths | | 0 | 77 | | 1 | 11 | | 2 | 1 | | 3 | 32 | | 4 | 3 | | 5 | 69 | | 6 | 16 | | 7 | 17 | | 8 | 4 | | 9 | 50 | | 10 | 19 | | 11 | 5 | | 12 | 4 | | 13 | 13 | | 14 | 20 | | 15 | 4 | | 16 | 17 | | 17 | 39 | | 18 | 8 | | 19 | 30 | | 20 | 3 | | 21 | 9 | | 22 | 29 | | 23 | 26 | | 24 | 63 | | 25 | 5 | | 26 | 37 | | 27 | 40 | | 28 | 10 | | 29 | 26 | | 30 | 5 | | 31 | 22 | | 32 | 53 | | 33 | 1 | | 34 | 87 | | 35 | 5 | | 36 | 38 | | 37 | 7 | | 38 | 26 | | 39 | 40 | | 40 | 21 | | 41 | 39 | | 42 | 6 | | 43 | 33 | | 44 | 40 | | 45 | 11 |
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| 90.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 48 | | matches | | 0 | "being asked" | | 1 | "been filled" |
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| 22.22% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 150 | | matches | | 0 | "was sorting" | | 1 | "was always pushing" | | 2 | "was reading" | | 3 | "wasn't looking" |
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| 68.65% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 77 | | ratio | 0.026 | | matches | | 0 | "The Raven's Nest smelled the same as it always had—whisky and old paper and the faint char of the fireplace nobody bothered to clean properly." | | 1 | "\"Good.\" He said it too quickly, too sharp, and something in his face flickered—an old anger surfacing before he could stop it." |
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| 85.45% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 671 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 38 | | adverbRatio | 0.05663189269746647 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.013412816691505217 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 77 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 77 | | mean | 14.56 | | std | 12.58 | | cv | 0.864 | | sampleLengths | | 0 | 25 | | 1 | 27 | | 2 | 25 | | 3 | 11 | | 4 | 1 | | 5 | 26 | | 6 | 6 | | 7 | 3 | | 8 | 9 | | 9 | 11 | | 10 | 26 | | 11 | 23 | | 12 | 10 | | 13 | 6 | | 14 | 16 | | 15 | 1 | | 16 | 4 | | 17 | 29 | | 18 | 4 | | 19 | 17 | | 20 | 19 | | 21 | 5 | | 22 | 4 | | 23 | 13 | | 24 | 8 | | 25 | 12 | | 26 | 4 | | 27 | 13 | | 28 | 4 | | 29 | 7 | | 30 | 32 | | 31 | 3 | | 32 | 5 | | 33 | 22 | | 34 | 8 | | 35 | 3 | | 36 | 5 | | 37 | 4 | | 38 | 15 | | 39 | 14 | | 40 | 16 | | 41 | 10 | | 42 | 8 | | 43 | 38 | | 44 | 17 | | 45 | 5 | | 46 | 26 | | 47 | 11 | | 48 | 40 | | 49 | 7 |
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| 83.55% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5324675324675324 | | totalSentences | 77 | | uniqueOpeners | 41 | |
| 72.46% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 46 | | matches | | 0 | "Then something loosened in his" |
| | ratio | 0.022 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 46 | | matches | | 0 | "She almost didn't recognise the" | | 1 | "He turned, and for a" | | 2 | "He'd put on weight, but" | | 3 | "It sat wrong on him," | | 4 | "His hair, once a mess" | | 5 | "She sat on the stool" | | 6 | "He lifted his glass, some" | | 7 | "He gave her nothing, just" | | 8 | "She stopped herself" | | 9 | "she said, because it was" | | 10 | "He laughed, short and without" | | 11 | "He turned the glass in" | | 12 | "She hadn't heard anyone say" | | 13 | "He said it too quickly," | | 14 | "She wrapped both hands around" | | 15 | "she asked, because she needed" | | 16 | "He said it like the" | | 17 | "He looked at her properly" | | 18 | "She didn't know what to" | | 19 | "she asked eventually" |
| | ratio | 0.696 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 46 | | matches | | 0 | "The Raven's Nest smelled the" | | 1 | "Rory came down from her" | | 2 | "Silas was behind the bar" | | 3 | "She almost didn't recognise the" | | 4 | "He turned, and for a" | | 5 | "He'd put on weight, but" | | 6 | "It sat wrong on him," | | 7 | "His hair, once a mess" | | 8 | "The last time she'd seen" | | 9 | "She sat on the stool" | | 10 | "He lifted his glass, some" | | 11 | "Silas set a coffee in" | | 12 | "Rory caught his eye." | | 13 | "He gave her nothing, just" | | 14 | "Tommy said, and it came" | | 15 | "She stopped herself" | | 16 | "she said, because it was" | | 17 | "He laughed, short and without" | | 18 | "He turned the glass in" | | 19 | "The name landed like a" |
| | ratio | 0.957 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 46 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 19 | | technicalSentenceCount | 1 | | matches | | 0 | "Silas was behind the bar polishing a glass that didn't need polishing, the way he did when he wanted an excuse to watch the door." |
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| 38.04% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 4 | | matches | | 0 | "Tommy's mouth twitched, not quite a smile" | | 1 | "He shrugged, and the gesture seemed to cost him something" | | 2 | "He held up, not unkindly" | | 3 | "she said, though her coffee was still half full and she had twenty minutes to spare" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 51 | | tagDensity | 0.176 | | leniency | 0.353 | | rawRatio | 0 | | effectiveRatio | 0 | |