| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 2 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 82.08% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 279 | | totalAiIsmAdverbs | 1 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 279 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "cascading" | | 1 | "glint" | | 2 | "scanned" | | 3 | "pulse" | | 4 | "crystal" | | 5 | "standard" |
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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 | 34 | | matches | (empty) | |
| 58.82% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 34 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 34 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 275 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 75.93% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 13 | | wordCount | 270 | | uniqueNames | 9 | | maxNameDensity | 1.48 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Detective | 1 | | Harlow | 1 | | Quinn | 4 | | Silas | 1 | | Morris | 2 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Harlow" | | 3 | "Quinn" | | 4 | "Silas" | | 5 | "Morris" |
| | places | (empty) | | globalScore | 0.759 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 22 | | glossingSentenceCount | 4 | | matches | | 0 | "felt like unfinished business" | | 1 | "Artifacts that seemed to pulse with their own strange light" | | 2 | "looked like preserved animal hearts in cr" | | 3 | "felt like the same supernatural 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 | 275 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 34 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 13 | | mean | 21.15 | | std | 13.48 | | cv | 0.637 | | sampleLengths | | 0 | 49 | | 1 | 5 | | 2 | 14 | | 3 | 40 | | 4 | 11 | | 5 | 6 | | 6 | 26 | | 7 | 31 | | 8 | 24 | | 9 | 30 | | 10 | 14 | | 11 | 22 | | 12 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 34 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 40 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 274 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 9 | | adverbRatio | 0.032846715328467155 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0072992700729927005 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 34 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 34 | | mean | 8.09 | | std | 4.91 | | cv | 0.607 | | sampleLengths | | 0 | 23 | | 1 | 11 | | 2 | 15 | | 3 | 5 | | 4 | 7 | | 5 | 7 | | 6 | 8 | | 7 | 17 | | 8 | 8 | | 9 | 7 | | 10 | 11 | | 11 | 4 | | 12 | 2 | | 13 | 5 | | 14 | 6 | | 15 | 15 | | 16 | 8 | | 17 | 6 | | 18 | 4 | | 19 | 10 | | 20 | 3 | | 21 | 6 | | 22 | 12 | | 23 | 6 | | 24 | 15 | | 25 | 15 | | 26 | 4 | | 27 | 3 | | 28 | 7 | | 29 | 4 | | 30 | 3 | | 31 | 3 | | 32 | 12 | | 33 | 3 |
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| 97.06% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.6470588235294118 | | totalSentences | 34 | | uniqueOpeners | 22 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 31 | | matches | | 0 | "Just a slight shake of" |
| | ratio | 0.032 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 5 | | totalSentences | 31 | | matches | | 0 | "Her worn leather watch caught" | | 1 | "She moved past the black-and-white" | | 2 | "Her target weaved through the" | | 3 | "She was deep now." | | 4 | "Her breath came faster." |
| | ratio | 0.161 | |
| 72.90% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 24 | | totalSentences | 31 | | matches | | 0 | "The neon green sign of" | | 1 | "Rain pelted her salt-and-pepper hair," | | 2 | "Her worn leather watch caught" | | 3 | "Silas, the bartender, didn't even" | | 4 | "Quinn's boot heels clicked against" | | 5 | "She moved past the black-and-white" | | 6 | "The bookshelf at the back" | | 7 | "A glimpse of a dark" | | 8 | "The stairs descended into darkness." | | 9 | "Quinn's hand instinctively brushed her" | | 10 | "The stairwell opened into a" | | 11 | "Shadowy figures moved between makeshift" | | 12 | "Bottles with unnatural colors." | | 13 | "Artifacts that seemed to pulse" | | 14 | "The Veil Market." | | 15 | "Her target weaved through the" | | 16 | "Marketplace vendors with inhuman features" | | 17 | "Nobody wanted trouble with a" | | 18 | "Quinn pushed past a stall" | | 19 | "The suspect ducked behind a" |
| | ratio | 0.774 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 31 | | matches | (empty) | | ratio | 0 | |
| 12.99% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 11 | | technicalSentenceCount | 2 | | matches | | 0 | "The suspect ducked behind a curtain of hanging chains that clinked with strange metallic sounds." | | 1 | "Something that felt like the same supernatural current that had claimed Morris." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "she shouted (shout)" |
| | dialogueSentences | 2 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 1 | | effectiveRatio | 1 | |