| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 2 | | adverbTags | | 0 | "But she stepped back [back]" | | 1 | "he said finally [finally]" |
| | dialogueSentences | 50 | | tagDensity | 0.46 | | leniency | 0.92 | | rawRatio | 0.087 | | effectiveRatio | 0.08 | |
| 84.11% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1259 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 88.09% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1259 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "flickered" | | 1 | "weight" | | 2 | "warmth" |
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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 | 1 | | narrationSentences | 84 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 84 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 111 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1263 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 99.60% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 992 | | uniqueNames | 9 | | maxNameDensity | 1.01 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Eva | 4 | | Moreau | 2 | | Lucien | 10 | | Ptolemy | 5 | | Mrs | 1 | | Osei | 1 | | Rory | 8 | | Started | 1 | | Carter | 1 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Lucien" | | 3 | "Ptolemy" | | 4 | "Mrs" | | 5 | "Osei" | | 6 | "Rory" | | 7 | "Carter" |
| | places | (empty) | | globalScore | 0.996 | | windowScore | 1 | |
| 96.81% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | glossingSentenceCount | 1 | | matches | | 0 | "Not quite a smile, but adjacent to one" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.792 | | wordCount | 1263 | | matches | | 0 | "Not quite a smile, but adjacent to one" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 111 | | matches | | 0 | "was that Eva checking that her" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 24.29 | | std | 24.24 | | cv | 0.998 | | sampleLengths | | 0 | 55 | | 1 | 33 | | 2 | 3 | | 3 | 17 | | 4 | 47 | | 5 | 6 | | 6 | 2 | | 7 | 5 | | 8 | 23 | | 9 | 87 | | 10 | 10 | | 11 | 86 | | 12 | 5 | | 13 | 7 | | 14 | 75 | | 15 | 5 | | 16 | 1 | | 17 | 8 | | 18 | 45 | | 19 | 26 | | 20 | 22 | | 21 | 6 | | 22 | 69 | | 23 | 31 | | 24 | 5 | | 25 | 15 | | 26 | 16 | | 27 | 52 | | 28 | 1 | | 29 | 8 | | 30 | 3 | | 31 | 20 | | 32 | 10 | | 33 | 5 | | 34 | 73 | | 35 | 30 | | 36 | 2 | | 37 | 51 | | 38 | 1 | | 39 | 11 | | 40 | 67 | | 41 | 5 | | 42 | 22 | | 43 | 14 | | 44 | 45 | | 45 | 2 | | 46 | 17 | | 47 | 51 | | 48 | 13 | | 49 | 14 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 84 | | matches | (empty) | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 167 | | matches | | 0 | "was wearing was doing" | | 1 | "was standing" | | 2 | "was sitting" | | 3 | "was doing" | | 4 | "was holding" |
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| 39.90% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 111 | | ratio | 0.036 | | matches | | 0 | "His mismatched eyes — amber and black, unsettling in any light, somehow worse in the dim yellow glow of the corridor — tracked over her face with that particular quality of attention she had spent three months actively trying to forget." | | 1 | "Rory pulled the door wide and Lucien stepped through, bringing the cold and the smell of rain and something underneath it — cedar, and smoke, and the faint brimstone edge that clung to him like a rumour she'd never quite been able to confirm." | | 2 | "The light flickered — the flat's electrics were temperamental in the cold — and held." | | 3 | "Lucien's expression was the thing she'd always found most difficult about him — the careful composure that was never quite as total as he meant it to be, the way something moved behind his mismatched eyes that he didn't intend to be visible." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 989 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.03640040444893832 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.011122345803842264 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 111 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 111 | | mean | 11.38 | | std | 11.62 | | cv | 1.021 | | sampleLengths | | 0 | 6 | | 1 | 49 | | 2 | 33 | | 3 | 3 | | 4 | 17 | | 5 | 3 | | 6 | 41 | | 7 | 2 | | 8 | 1 | | 9 | 6 | | 10 | 2 | | 11 | 5 | | 12 | 19 | | 13 | 4 | | 14 | 26 | | 15 | 11 | | 16 | 6 | | 17 | 44 | | 18 | 10 | | 19 | 30 | | 20 | 10 | | 21 | 17 | | 22 | 29 | | 23 | 5 | | 24 | 7 | | 25 | 4 | | 26 | 57 | | 27 | 6 | | 28 | 8 | | 29 | 5 | | 30 | 1 | | 31 | 4 | | 32 | 4 | | 33 | 25 | | 34 | 15 | | 35 | 5 | | 36 | 2 | | 37 | 24 | | 38 | 10 | | 39 | 12 | | 40 | 3 | | 41 | 3 | | 42 | 22 | | 43 | 8 | | 44 | 39 | | 45 | 18 | | 46 | 13 | | 47 | 5 | | 48 | 8 | | 49 | 7 |
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| 50.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.36936936936936937 | | totalSentences | 111 | | uniqueOpeners | 41 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 3.61% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 61 | | matches | | 0 | "His mismatched eyes — amber" | | 1 | "He reached down and scratched" | | 2 | "She was already imagining the" | | 3 | "She shut all three deadbolts" | | 4 | "He surveyed the room the" | | 5 | "She crossed her arms." | | 6 | "She was very aware, suddenly," | | 7 | "She was not dressed for" | | 8 | "She was not, in any" | | 9 | "He tilted his head." | | 10 | "She moved to the kitchen," | | 11 | "She heard the soft knock" | | 12 | "She turned around." | | 13 | "He was closer than she'd" | | 14 | "His platinum hair was damp" | | 15 | "He hadn't slicked it back" | | 16 | "Her voice came out steadier" | | 17 | "She turned back to the" | | 18 | "She set two mugs down" | | 19 | "She kept her hands around" |
| | ratio | 0.541 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 61 | | matches | | 0 | "The second deadbolt had stuck" | | 1 | "Rory was still wrestling with" | | 2 | "Lucien Moreau stood in the" | | 3 | "Rory didn't move." | | 4 | "Ptolemy, the traitor, wound immediately" | | 5 | "His mismatched eyes — amber" | | 6 | "He reached down and scratched" | | 7 | "Osei from across the hall" | | 8 | "She was already imagining the" | | 9 | "Rory pulled the door wide" | | 10 | "She shut all three deadbolts" | | 11 | "He surveyed the room the" | | 12 | "Books stacked on the floor" | | 13 | "Eva's research notes in a" | | 14 | "A mug of tea gone" | | 15 | "She crossed her arms." | | 16 | "She was very aware, suddenly," | | 17 | "She was not dressed for" | | 18 | "She was not, in any" | | 19 | "He tilted his head." |
| | ratio | 0.934 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 19.70% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 5 | | matches | | 0 | "Rory pulled the door wide and Lucien stepped through, bringing the cold and the smell of rain and something underneath it — cedar, and smoke, and the faint brim…" | | 1 | "He hadn't slicked it back tonight with his usual precision and a few strands had come loose at his temple, which was the most undone she had ever seen him look,…" | | 2 | "Ptolemy had followed Lucien into the kitchen and was sitting squarely in the middle of the floor with his tail curled around his feet, watching them both with t…" | | 3 | "Lucien's expression was the thing she'd always found most difficult about him — the careful composure that was never quite as total as he meant it to be, the wa…" | | 4 | "The particular specific quiet of a conversation that had not actually ended." |
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| 81.52% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 2 | | matches | | 0 | "He reached, not breaking her gaze" | | 1 | "her had, fractionally" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 50 | | tagDensity | 0.28 | | leniency | 0.56 | | rawRatio | 0.071 | | effectiveRatio | 0.04 | |