| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 26 | | tagDensity | 0.385 | | leniency | 0.769 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 79.44% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1216 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "carefully" | | 2 | "quickly" | | 3 | "slowly" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 30.10% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1216 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "wavered" | | 1 | "traced" | | 2 | "silence" | | 3 | "glint" | | 4 | "rhythmic" | | 5 | "echoing" | | 6 | "weight" | | 7 | "flickered" | | 8 | "resolved" | | 9 | "standard" | | 10 | "trembled" | | 11 | "pulse" | | 12 | "familiar" |
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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 | 94 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 94 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 108 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1216 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 84.61% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 994 | | uniqueNames | 4 | | maxNameDensity | 1.31 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 13 | | Patel | 10 | | Amateur | 1 | | Morris | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Patel" | | 2 | "Morris" |
| | places | (empty) | | globalScore | 0.846 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | glossingSentenceCount | 1 | | matches | | 0 | "as though answering a faster current" |
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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 | 1216 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 108 | | matches | | 0 | "kept that observation" | | 1 | "stored that detail" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 36 | | mean | 33.78 | | std | 19.5 | | cv | 0.577 | | sampleLengths | | 0 | 36 | | 1 | 35 | | 2 | 41 | | 3 | 8 | | 4 | 51 | | 5 | 54 | | 6 | 47 | | 7 | 16 | | 8 | 39 | | 9 | 11 | | 10 | 52 | | 11 | 90 | | 12 | 33 | | 13 | 51 | | 14 | 34 | | 15 | 60 | | 16 | 48 | | 17 | 19 | | 18 | 9 | | 19 | 53 | | 20 | 7 | | 21 | 13 | | 22 | 35 | | 23 | 53 | | 24 | 5 | | 25 | 6 | | 26 | 46 | | 27 | 48 | | 28 | 47 | | 29 | 20 | | 30 | 14 | | 31 | 29 | | 32 | 36 | | 33 | 42 | | 34 | 25 | | 35 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 94 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 162 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 108 | | ratio | 0 | | matches | (empty) | |
| 97.30% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 998 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 43 | | adverbRatio | 0.04308617234468938 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.014028056112224449 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 108 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 108 | | mean | 11.26 | | std | 6.61 | | cv | 0.587 | | sampleLengths | | 0 | 16 | | 1 | 20 | | 2 | 14 | | 3 | 11 | | 4 | 10 | | 5 | 5 | | 6 | 18 | | 7 | 11 | | 8 | 6 | | 9 | 1 | | 10 | 8 | | 11 | 12 | | 12 | 21 | | 13 | 18 | | 14 | 12 | | 15 | 10 | | 16 | 26 | | 17 | 2 | | 18 | 4 | | 19 | 21 | | 20 | 10 | | 21 | 16 | | 22 | 6 | | 23 | 10 | | 24 | 11 | | 25 | 8 | | 26 | 3 | | 27 | 17 | | 28 | 5 | | 29 | 6 | | 30 | 14 | | 31 | 10 | | 32 | 28 | | 33 | 11 | | 34 | 13 | | 35 | 12 | | 36 | 20 | | 37 | 22 | | 38 | 12 | | 39 | 25 | | 40 | 8 | | 41 | 4 | | 42 | 10 | | 43 | 29 | | 44 | 2 | | 45 | 2 | | 46 | 4 | | 47 | 9 | | 48 | 25 | | 49 | 14 |
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| 57.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.3888888888888889 | | totalSentences | 108 | | uniqueOpeners | 42 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 83 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 83 | | matches | | 0 | "His torch beam wavered over" | | 1 | "She crouched by a smear" | | 2 | "He pointed at the far" | | 3 | "She traced the edge of" | | 4 | "She flipped it." | | 5 | "She thumbed the side of" | | 6 | "She walked the perimeter where" | | 7 | "She knelt and brushed dust" | | 8 | "She lifted it carefully and" | | 9 | "She slipped the bag into" | | 10 | "She stored that detail." | | 11 | "She raised her voice only" | | 12 | "They shifted their footing, boots" | | 13 | "she ordered without turning" | | 14 | "Her watch strap cut into" | | 15 | "His shoe tread left a" | | 16 | "She kept her torch steady." | | 17 | "His hand opened to show" |
| | ratio | 0.217 | |
| 32.29% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 83 | | matches | | 0 | "Detective Quinn stepped over the" | | 1 | "A faint copper sting clung" | | 2 | "His torch beam wavered over" | | 3 | "Quinn didn't answer at once." | | 4 | "The station had been closed" | | 5 | "She crouched by a smear" | | 6 | "Copper stung her nostrils once" | | 7 | "He pointed at the far" | | 8 | "She traced the edge of" | | 9 | "The paint fumes were faint," | | 10 | "Patel's light swung to a" | | 11 | "Quinn picked one up, careful" | | 12 | "A crimson fingerprint marked the" | | 13 | "The leaflet edge cut sharper" | | 14 | "She flipped it." | | 15 | "Patel laughed under his breath." | | 16 | "She thumbed the side of" | | 17 | "The metal casing felt colder" | | 18 | "She walked the perimeter where" | | 19 | "A glint caught her eye" |
| | ratio | 0.855 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 83 | | matches | (empty) | | ratio | 0 | |
| 98.21% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 3 | | matches | | 0 | "The glass front bore faint concentric scratches that formed interlocking circles, reminiscent of protective marks, yet she kept that observation to herself." | | 1 | "The needle inside it circled once more, quicker than before, as though answering a faster current." | | 2 | "One lowered his torch, revealing the edge of a bone-coloured token hanging from his lapel, carved with the same reversed symbols Quinn had examined on the wall." |
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| 75.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 1 | | matches | | 0 | "Patel said, his voice echoing back from the tunnel mouth" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 26 | | tagDensity | 0.346 | | leniency | 0.692 | | rawRatio | 0.111 | | effectiveRatio | 0.077 | |