| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn crouched again [again]" |
| | dialogueSentences | 26 | | tagDensity | 0.346 | | leniency | 0.692 | | rawRatio | 0.111 | | effectiveRatio | 0.077 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 875 | | 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) | |
| 65.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 875 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "pulse" | | 1 | "standard" | | 2 | "stark" | | 3 | "etched" | | 4 | "glistening" |
| |
| 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 | "clenched jaw/fists" | | count | 1 |
|
| | highlights | | 0 | "eyes widened" | | 1 | "clenched fist" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 58 | | matches | (empty) | |
| 93.60% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 58 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 75 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 63 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 875 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 47.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 534 | | uniqueNames | 11 | | maxNameDensity | 2.06 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Eva" | | discoveredNames | | Quinn | 11 | | Eva | 10 | | Kowalski | 1 | | Ticket | 1 | | Hall | 1 | | Camden | 1 | | Veil | 1 | | Market | 1 | | Metropolitan | 1 | | Museum | 1 | | Oxford | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Eva" | | 2 | "Kowalski" | | 3 | "Metropolitan" |
| | places | | 0 | "Ticket" | | 1 | "Hall" | | 2 | "Oxford" |
| | globalScore | 0.47 | | windowScore | 0.5 | |
| 89.02% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 41 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 875 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 75 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 26 | | mean | 33.65 | | std | 22.88 | | cv | 0.68 | | sampleLengths | | 0 | 50 | | 1 | 22 | | 2 | 55 | | 3 | 76 | | 4 | 19 | | 5 | 52 | | 6 | 54 | | 7 | 63 | | 8 | 37 | | 9 | 32 | | 10 | 15 | | 11 | 31 | | 12 | 30 | | 13 | 2 | | 14 | 3 | | 15 | 88 | | 16 | 18 | | 17 | 38 | | 18 | 6 | | 19 | 64 | | 20 | 33 | | 21 | 27 | | 22 | 33 | | 23 | 6 | | 24 | 7 | | 25 | 14 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 58 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 95 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 75 | | ratio | 0.013 | | matches | | 0 | "Stalls of black cloth and bone charms hung empty; the Veil Market vendors never lingered once Metropolitan boots appeared." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 538 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.024163568773234202 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0018587360594795538 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 75 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 75 | | mean | 11.67 | | std | 8.94 | | cv | 0.767 | | sampleLengths | | 0 | 16 | | 1 | 16 | | 2 | 8 | | 3 | 1 | | 4 | 9 | | 5 | 16 | | 6 | 6 | | 7 | 17 | | 8 | 17 | | 9 | 21 | | 10 | 3 | | 11 | 10 | | 12 | 19 | | 13 | 19 | | 14 | 12 | | 15 | 13 | | 16 | 6 | | 17 | 13 | | 18 | 15 | | 19 | 26 | | 20 | 11 | | 21 | 10 | | 22 | 19 | | 23 | 15 | | 24 | 4 | | 25 | 6 | | 26 | 4 | | 27 | 6 | | 28 | 35 | | 29 | 18 | | 30 | 5 | | 31 | 14 | | 32 | 18 | | 33 | 10 | | 34 | 4 | | 35 | 18 | | 36 | 3 | | 37 | 12 | | 38 | 9 | | 39 | 22 | | 40 | 11 | | 41 | 10 | | 42 | 9 | | 43 | 2 | | 44 | 3 | | 45 | 25 | | 46 | 63 | | 47 | 7 | | 48 | 11 | | 49 | 7 |
| |
| 87.56% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5333333333333333 | | totalSentences | 75 | | uniqueOpeners | 40 | |
| 62.89% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 53 | | matches | | | ratio | 0.019 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 53 | | matches | | 0 | "She pressed two fingers to" | | 1 | "she told the figure fidgeting" | | 2 | "She kept a respectful distance" | | 3 | "She rose, leather watch several" | | 4 | "She knelt without waiting, gloved" | | 5 | "She pried open stiff fingers" | | 6 | "She did not reach for" | | 7 | "Her speech sped, Oxford vowels" | | 8 | "She stood, satchel swinging." | | 9 | "It lit a boot print" | | 10 | "She arrived at Quinn's shoulder," |
| | ratio | 0.208 | |
| 16.60% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 53 | | matches | | 0 | "The chalk circle smeared under" | | 1 | "Blood still seeped between the" | | 2 | "She pressed two fingers to" | | 3 | "she told the figure fidgeting" | | 4 | "Eva Kowalski tucked a curl" | | 5 | "She kept a respectful distance" | | 6 | "Quinn's jaw tightened." | | 7 | "She rose, leather watch several" | | 8 | "The abandoned Ticket Hall of" | | 9 | "Stalls of black cloth and" | | 10 | "A pair of constables argued" | | 11 | "Quinn pointed at the half-erased" | | 12 | "Eva stepped closer, freckles stark" | | 13 | "She knelt without waiting, gloved" | | 14 | "Quinn crouched again, glove brushing" | | 15 | "She pried open stiff fingers" | | 16 | "A small brass compass rolled" | | 17 | "Verdigris rinded the casing." | | 18 | "Eva's green eyes widened." | | 19 | "She did not reach for" |
| | ratio | 0.887 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 53 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 1 | | matches | | 0 | "Something darker, thicker, the consistency of used engine oil that reeked of sulphur." |
| |
| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn crouched again, glove brushing the victim's clenched fist" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "Eva whispered (whisper)" |
| | dialogueSentences | 26 | | tagDensity | 0.115 | | leniency | 0.231 | | rawRatio | 0.333 | | effectiveRatio | 0.077 | |