| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.208 | | leniency | 0.417 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1053 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 71.51% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1053 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "weight" | | 1 | "silk" | | 2 | "flicked" | | 3 | "pulse" | | 4 | "tracing" | | 5 | "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 | 46 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 46 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 83 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1053 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 13 | | wordCount | 557 | | uniqueNames | 8 | | maxNameDensity | 0.54 | | worstName | "Lucien" | | maxWindowNameDensity | 1 | | worstWindowName | "Eva" | | discoveredNames | | Eva | 2 | | Lucien | 3 | | Moreau | 1 | | Cardiff | 1 | | Brick | 1 | | Lane | 1 | | Ptolemy | 3 | | Cold | 1 |
| | persons | | 0 | "Eva" | | 1 | "Lucien" | | 2 | "Moreau" | | 3 | "Ptolemy" |
| | places | | 0 | "Cardiff" | | 1 | "Brick" | | 2 | "Lane" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 39 | | 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 | 1053 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 83 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 20.25 | | std | 18.04 | | cv | 0.891 | | sampleLengths | | 0 | 17 | | 1 | 51 | | 2 | 1 | | 3 | 12 | | 4 | 9 | | 5 | 3 | | 6 | 4 | | 7 | 4 | | 8 | 20 | | 9 | 7 | | 10 | 16 | | 11 | 61 | | 12 | 9 | | 13 | 6 | | 14 | 37 | | 15 | 13 | | 16 | 26 | | 17 | 6 | | 18 | 12 | | 19 | 63 | | 20 | 5 | | 21 | 6 | | 22 | 33 | | 23 | 29 | | 24 | 2 | | 25 | 5 | | 26 | 22 | | 27 | 27 | | 28 | 30 | | 29 | 11 | | 30 | 41 | | 31 | 17 | | 32 | 13 | | 33 | 4 | | 34 | 45 | | 35 | 4 | | 36 | 66 | | 37 | 3 | | 38 | 46 | | 39 | 7 | | 40 | 3 | | 41 | 41 | | 42 | 46 | | 43 | 6 | | 44 | 8 | | 45 | 29 | | 46 | 39 | | 47 | 4 | | 48 | 50 | | 49 | 11 |
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| 97.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 46 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 85 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 83 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 559 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.014311270125223614 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0017889087656529517 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 83 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 83 | | mean | 12.69 | | std | 8.74 | | cv | 0.689 | | sampleLengths | | 0 | 17 | | 1 | 3 | | 2 | 22 | | 3 | 10 | | 4 | 16 | | 5 | 1 | | 6 | 7 | | 7 | 5 | | 8 | 9 | | 9 | 3 | | 10 | 4 | | 11 | 4 | | 12 | 7 | | 13 | 13 | | 14 | 7 | | 15 | 16 | | 16 | 10 | | 17 | 51 | | 18 | 9 | | 19 | 6 | | 20 | 15 | | 21 | 11 | | 22 | 10 | | 23 | 1 | | 24 | 13 | | 25 | 26 | | 26 | 6 | | 27 | 12 | | 28 | 13 | | 29 | 19 | | 30 | 16 | | 31 | 15 | | 32 | 5 | | 33 | 6 | | 34 | 9 | | 35 | 24 | | 36 | 29 | | 37 | 2 | | 38 | 5 | | 39 | 14 | | 40 | 8 | | 41 | 27 | | 42 | 30 | | 43 | 11 | | 44 | 21 | | 45 | 20 | | 46 | 17 | | 47 | 13 | | 48 | 4 | | 49 | 22 |
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| 82.73% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.5180722891566265 | | totalSentences | 83 | | uniqueOpeners | 43 | |
| 79.37% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 42 | | matches | | 0 | "Then the one below it," |
| | ratio | 0.024 | |
| 77.14% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 42 | | matches | | 0 | "I opened the door for" | | 1 | "I put my weight into" | | 2 | "My photograph on top, eight" | | 3 | "I unclipped the chain, because" | | 4 | "He stepped past me, turned" | | 5 | "I flicked the card back" | | 6 | "He stripped off one glove," | | 7 | "He crossed the room, unhurried," | | 8 | "My back found the bookshelf," | | 9 | "His hand came up, knuckles" | | 10 | "My left wrist lit up" | | 11 | "I grabbed it before the" | | 12 | "His hand followed mine, turned" | | 13 | "He drew his hand from" | | 14 | "He stepped between me and" |
| | ratio | 0.357 | |
| 31.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 36 | | totalSentences | 42 | | matches | | 0 | "I opened the door for" | | 1 | "The chain held." | | 2 | "Bergamot threaded through the curry" | | 3 | "Ptolemy flowed out from under" | | 4 | "I put my weight into" | | 5 | "The cane slid into the" | | 6 | "Silk, with something under it" | | 7 | "A fat manila folder slid" | | 8 | "My photograph on top, eight" | | 9 | "I unclipped the chain, because" | | 10 | "He stepped past me, turned" | | 11 | "Eva's flat fought a running" | | 12 | "Folios stacked along the counter," | | 13 | "Chilli smoke seeped up through" | | 14 | "Lucien leaned his cane against" | | 15 | "An envelope landed on the" | | 16 | "I flicked the card back" | | 17 | "The folder sat between us" | | 18 | "Ptolemy watched from the sofa" | | 19 | "He stripped off one glove," |
| | ratio | 0.857 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 42 | | matches | (empty) | | ratio | 0 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 3 | | matches | | 0 | "Bergamot threaded through the curry smell that owned our landing." | | 1 | "He stepped past me, turned all three deadbolts, and hung his coat on the hook like a man who had done it a hundred times before." | | 2 | "His hand followed mine, turned it over with a care that had no business in a man like him, and we both looked down." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 3 | | matches | | 0 | "The folder sat, my younger face grinning up at the ceiling" | | 1 | "His hand came up, knuckles tracing the air beside my jaw without landing" | | 2 | "He drew, and the cane came apart with a click, a blade sliding free, thin and dark and eager" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.042 | | leniency | 0.083 | | rawRatio | 0 | | effectiveRatio | 0 | |