| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.294 | | leniency | 0.588 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 86.24% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 727 | | totalAiIsmAdverbs | 2 | | 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) | |
| 65.61% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 727 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "scanning" | | 1 | "eyebrow" | | 2 | "tracing" | | 3 | "familiar" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "flicker of emotion" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "a spark of recognition" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 46 | | matches | | 0 | "a spark of determination" |
| |
| 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 | 58 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 727 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 53 | | wordCount | 588 | | uniqueNames | 15 | | maxNameDensity | 3.23 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 19 | | Tube | 1 | | Camden | 1 | | Constable | 1 | | Reed | 3 | | Veil | 5 | | Market | 3 | | Detective | 2 | | Inspector | 1 | | Llewellyn | 8 | | Welsh | 1 | | Eva | 4 | | Compass | 2 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Reed" | | 3 | "Llewellyn" | | 4 | "Welsh" | | 5 | "Eva" | | 6 | "Morris" |
| | places | | | globalScore | 0 | | windowScore | 0.333 | |
| 76.47% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 34 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed almost deliberate" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 727 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 58 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 23 | | mean | 31.61 | | std | 19.13 | | cv | 0.605 | | sampleLengths | | 0 | 62 | | 1 | 11 | | 2 | 60 | | 3 | 61 | | 4 | 27 | | 5 | 8 | | 6 | 25 | | 7 | 49 | | 8 | 46 | | 9 | 6 | | 10 | 13 | | 11 | 12 | | 12 | 44 | | 13 | 29 | | 14 | 18 | | 15 | 9 | | 16 | 24 | | 17 | 21 | | 18 | 66 | | 19 | 21 | | 20 | 22 | | 21 | 50 | | 22 | 43 |
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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 | 92 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 589 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 9 | | adverbRatio | 0.015280135823429542 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.003395585738539898 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 58 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 58 | | mean | 12.53 | | std | 6.64 | | cv | 0.529 | | sampleLengths | | 0 | 22 | | 1 | 24 | | 2 | 16 | | 3 | 7 | | 4 | 4 | | 5 | 20 | | 6 | 16 | | 7 | 24 | | 8 | 13 | | 9 | 19 | | 10 | 19 | | 11 | 10 | | 12 | 12 | | 13 | 15 | | 14 | 4 | | 15 | 4 | | 16 | 5 | | 17 | 20 | | 18 | 9 | | 19 | 4 | | 20 | 15 | | 21 | 21 | | 22 | 9 | | 23 | 22 | | 24 | 15 | | 25 | 2 | | 26 | 4 | | 27 | 2 | | 28 | 11 | | 29 | 4 | | 30 | 8 | | 31 | 28 | | 32 | 16 | | 33 | 5 | | 34 | 8 | | 35 | 16 | | 36 | 7 | | 37 | 11 | | 38 | 4 | | 39 | 5 | | 40 | 12 | | 41 | 12 | | 42 | 9 | | 43 | 12 | | 44 | 9 | | 45 | 17 | | 46 | 19 | | 47 | 21 | | 48 | 16 | | 49 | 5 |
| |
| 63.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.3793103448275862 | | totalSentences | 58 | | uniqueOpeners | 22 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 44 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 7 | | totalSentences | 44 | | matches | | 0 | "She had been tracking a" | | 1 | "he said, his Welsh accent" | | 2 | "She crouched beside the victim," | | 3 | "She had met Eva a" | | 4 | "She had lost her partner," | | 5 | "She would need to pay" | | 6 | "She would uncover the truth," |
| | ratio | 0.159 | |
| 50.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 36 | | totalSentences | 44 | | matches | | 0 | "Detective Harlow Quinn stepped off" | | 1 | "The air reeked of decay" | | 2 | "A uniformed officer, Constable Reed," | | 3 | "Reed said, her voice low" | | 4 | "Quinn's gaze followed Reed's gesture" | | 5 | "The fluorescent lights overhead cast" | | 6 | "Quinn's trained eyes took in" | | 7 | "The Veil Market, an underground" | | 8 | "She had been tracking a" | | 9 | "Quinn's colleague, Detective Inspector Llewellyn," | | 10 | "he said, his Welsh accent" | | 11 | "Quinn raised an eyebrow." | | 12 | "Llewellyn gestured to the body." | | 13 | "Quinn's eyes narrowed as she" | | 14 | "Something didn't add up." | | 15 | "The body lay too neatly," | | 16 | "She crouched beside the victim," | | 17 | "Quinn murmured, a spark of" | | 18 | "She had met Eva a" | | 19 | "Quinn had been skeptical at" |
| | ratio | 0.818 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 44 | | matches | | 0 | "Now, it seemed, she had" |
| | ratio | 0.023 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 1 | | matches | | 0 | "The body lay too neatly, the limbs arranged with a precision that seemed almost deliberate." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 4 | | matches | | 0 | "Reed said, her voice low" | | 1 | "Quinn murmured, a spark of recognition igniting" | | 2 | "Llewellyn interrupted, his tone gentle" | | 3 | "Quinn repeated, her voice firm" |
| |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 3 | | fancyTags | | 0 | "Quinn murmured (murmur)" | | 1 | "Llewellyn interrupted (interrupt)" | | 2 | "Quinn repeated (repeat)" |
| | dialogueSentences | 17 | | tagDensity | 0.294 | | leniency | 0.588 | | rawRatio | 0.6 | | effectiveRatio | 0.353 | |