| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 36 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1063 | | 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) | |
| 90.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1063 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 101 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 101 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 121 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1063 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 32.35% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 850 | | uniqueNames | 11 | | maxNameDensity | 2.35 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Kowalski | 1 | | Quinn | 20 | | Eva | 15 | | Veil | 2 | | Market | 1 | | Camden | 1 | | Calloway | 1 | | Compass | 1 | | Tube | 1 | | Metropolitan | 1 | | Police | 1 |
| | persons | | 0 | "Kowalski" | | 1 | "Quinn" | | 2 | "Eva" | | 3 | "Market" | | 4 | "Calloway" | | 5 | "Compass" |
| | places | | | globalScore | 0.324 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | 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 | 1063 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 121 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 20.06 | | std | 18.34 | | cv | 0.915 | | sampleLengths | | 0 | 16 | | 1 | 49 | | 2 | 21 | | 3 | 42 | | 4 | 3 | | 5 | 11 | | 6 | 3 | | 7 | 3 | | 8 | 79 | | 9 | 26 | | 10 | 40 | | 11 | 12 | | 12 | 4 | | 13 | 5 | | 14 | 54 | | 15 | 17 | | 16 | 11 | | 17 | 12 | | 18 | 22 | | 19 | 41 | | 20 | 26 | | 21 | 4 | | 22 | 7 | | 23 | 53 | | 24 | 4 | | 25 | 21 | | 26 | 8 | | 27 | 12 | | 28 | 45 | | 29 | 15 | | 30 | 48 | | 31 | 25 | | 32 | 14 | | 33 | 6 | | 34 | 59 | | 35 | 33 | | 36 | 3 | | 37 | 8 | | 38 | 1 | | 39 | 2 | | 40 | 1 | | 41 | 10 | | 42 | 30 | | 43 | 13 | | 44 | 7 | | 45 | 7 | | 46 | 55 | | 47 | 12 | | 48 | 25 | | 49 | 7 |
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| 80.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 101 | | matches | | 0 | "been sealed" | | 1 | "was carved" | | 2 | "was etched" | | 3 | "been scratched" | | 4 | "was nailed" | | 5 | "was lined" | | 6 | "been marked" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 143 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 121 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 850 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.01764705882352941 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.001176470588235294 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 121 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 121 | | mean | 8.79 | | std | 5.3 | | cv | 0.603 | | sampleLengths | | 0 | 16 | | 1 | 24 | | 2 | 25 | | 3 | 13 | | 4 | 4 | | 5 | 4 | | 6 | 20 | | 7 | 9 | | 8 | 13 | | 9 | 3 | | 10 | 11 | | 11 | 3 | | 12 | 3 | | 13 | 4 | | 14 | 7 | | 15 | 24 | | 16 | 18 | | 17 | 11 | | 18 | 15 | | 19 | 6 | | 20 | 9 | | 21 | 11 | | 22 | 8 | | 23 | 16 | | 24 | 6 | | 25 | 4 | | 26 | 6 | | 27 | 12 | | 28 | 4 | | 29 | 5 | | 30 | 21 | | 31 | 4 | | 32 | 4 | | 33 | 9 | | 34 | 16 | | 35 | 4 | | 36 | 13 | | 37 | 7 | | 38 | 4 | | 39 | 7 | | 40 | 5 | | 41 | 16 | | 42 | 6 | | 43 | 7 | | 44 | 4 | | 45 | 10 | | 46 | 20 | | 47 | 12 | | 48 | 14 | | 49 | 4 |
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| 45.73% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.33884297520661155 | | totalSentences | 121 | | uniqueOpeners | 41 | |
| 38.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 87 | | matches | | 0 | "Pale, thin, wearing a worn" |
| | ratio | 0.011 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 87 | | matches | | 0 | "Its needle trembled under the" | | 1 | "She crouched, kept her gloves" | | 2 | "She tucked it behind her" | | 3 | "She swept the platform with" | | 4 | "She produced a sheet with" | | 5 | "She pried Calloway's fingers open." | | 6 | "It was carved with a" | | 7 | "It pointed not at the" | | 8 | "It pointed at a circular" | | 9 | "Her boots rang on the" | | 10 | "She stopped before the plate." |
| | ratio | 0.126 | |
| 0.23% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 80 | | totalSentences | 87 | | matches | | 0 | "Quinn's boot pressed the first" | | 1 | "The dead man lay on" | | 2 | "Its needle trembled under the" | | 3 | "She crouched, kept her gloves" | | 4 | "The casing was cold." | | 5 | "The glass was warm." | | 6 | "Eva Kowalski stood where the" | | 7 | "A red curl escaped the" | | 8 | "She tucked it behind her" | | 9 | "Quinn did not answer." | | 10 | "She swept the platform with" | | 11 | "The Veil Market had set" | | 12 | "Stalls leaned over one another," | | 13 | "Jars of smoke, dried bone," | | 14 | "A bell hung above the" | | 15 | "The market moved every full" | | 16 | "This platform had been sealed" | | 17 | "The two facts sat side" | | 18 | "Quinn turned the body over" | | 19 | "The man's face was smooth," |
| | ratio | 0.92 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 87 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 1 | | matches | | 0 | "Its needle trembled under the glass, refusing the body, the platform door, and the black cable that ran along the wall like a frozen snake." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 36 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |