| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 18 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 80.21% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 758 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "carefully" | | 1 | "lazily" | | 2 | "suddenly" |
| |
| 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) | |
| 53.83% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 758 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "flicker" | | 1 | "etched" | | 2 | "raced" | | 3 | "navigating" | | 4 | "scanning" | | 5 | "pulse" | | 6 | "trembled" |
| |
| 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 | 62 | | matches | (empty) | |
| 96.77% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 62 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 76 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 750 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 605 | | uniqueNames | 7 | | maxNameDensity | 2.15 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Eva" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 13 | | Veil | 1 | | Market | 1 | | Kowalski | 1 | | Eva | 13 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" |
| | places | (empty) | | globalScore | 0.426 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 39 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 66.67% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.333 | | wordCount | 750 | | matches | | 0 | "Not toward the exits, but deeper into the station, toward the old tracks" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 76 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 24.19 | | std | 20.1 | | cv | 0.831 | | sampleLengths | | 0 | 89 | | 1 | 79 | | 2 | 1 | | 3 | 34 | | 4 | 8 | | 5 | 28 | | 6 | 30 | | 7 | 45 | | 8 | 14 | | 9 | 5 | | 10 | 20 | | 11 | 35 | | 12 | 9 | | 13 | 20 | | 14 | 27 | | 15 | 40 | | 16 | 41 | | 17 | 9 | | 18 | 40 | | 19 | 15 | | 20 | 17 | | 21 | 19 | | 22 | 12 | | 23 | 38 | | 24 | 21 | | 25 | 20 | | 26 | 8 | | 27 | 9 | | 28 | 6 | | 29 | 3 | | 30 | 8 |
| |
| 93.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 62 | | matches | | 0 | "was supposed" | | 1 | "been dragged" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 100 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 76 | | ratio | 0.053 | | matches | | 0 | "The air in the abandoned Tube station was thick with the scent of damp stone and something metallic underneath—blood, maybe, or rust from the old tracks." | | 1 | "She pulled it free—a small brass compass, its face etched with sigils, the needle spinning lazily despite the stillness of the air." | | 2 | "But there, just beyond the edge of the platform—a shimmer in the air, like heat off pavement." | | 3 | "But this—this was something else." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 611 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.03273322422258593 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.009819967266775777 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 76 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 76 | | mean | 9.87 | | std | 6.48 | | cv | 0.657 | | sampleLengths | | 0 | 26 | | 1 | 18 | | 2 | 30 | | 3 | 15 | | 4 | 9 | | 5 | 23 | | 6 | 18 | | 7 | 15 | | 8 | 3 | | 9 | 2 | | 10 | 1 | | 11 | 8 | | 12 | 1 | | 13 | 2 | | 14 | 18 | | 15 | 14 | | 16 | 8 | | 17 | 13 | | 18 | 15 | | 19 | 5 | | 20 | 18 | | 21 | 3 | | 22 | 4 | | 23 | 16 | | 24 | 11 | | 25 | 18 | | 26 | 9 | | 27 | 5 | | 28 | 5 | | 29 | 5 | | 30 | 15 | | 31 | 13 | | 32 | 22 | | 33 | 5 | | 34 | 4 | | 35 | 7 | | 36 | 10 | | 37 | 3 | | 38 | 14 | | 39 | 13 | | 40 | 3 | | 41 | 5 | | 42 | 10 | | 43 | 3 | | 44 | 5 | | 45 | 14 | | 46 | 6 | | 47 | 13 | | 48 | 9 | | 49 | 13 |
| |
| 48.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.32894736842105265 | | totalSentences | 76 | | uniqueOpeners | 25 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 58 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 58 | | matches | | 0 | "She clutched her worn leather" | | 1 | "It was useful." | | 2 | "It was also infuriating." | | 3 | "She crouched beside the body," | | 4 | "she muttered, more to herself" | | 5 | "She pulled it free—a small" | | 6 | "She stood abruptly, scanning the" | | 7 | "She pointed to the dust" | | 8 | "She followed the trail, her" | | 9 | "She reached for her sidearm" | | 10 | "She had spent eighteen years" |
| | ratio | 0.19 | |
| 46.21% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 48 | | totalSentences | 58 | | matches | | 0 | "The air in the abandoned" | | 1 | "Detective Harlow Quinn stepped carefully" | | 2 | "The Veil Market was supposed" | | 3 | "Quinn’s sharp jaw tightened as" | | 4 | "The market’s usual eerie glow" | | 5 | "The body lay sprawled near" | | 6 | "A man, late thirties, dressed" | | 7 | "Eva Kowalski stood a few" | | 8 | "She clutched her worn leather" | | 9 | "Quinn said, voice low" | | 10 | "Eva tucked a curl of" | | 11 | "Quinn exhaled through her nose." | | 12 | "Eva had a way of" | | 13 | "It was useful." | | 14 | "It was also infuriating." | | 15 | "She crouched beside the body," | | 16 | "she muttered, more to herself" | | 17 | "Eva knelt beside her, careful" | | 18 | "Quinn shot her a look." | | 19 | "Eva met her gaze, unflinching." |
| | ratio | 0.828 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 58 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn said, voice low" | | 1 | "she muttered, more to herself than Eva" |
| |
| 94.44% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 18 | | tagDensity | 0.111 | | leniency | 0.222 | | rawRatio | 0.5 | | effectiveRatio | 0.111 | |