| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn stepped around [around]" |
| | dialogueSentences | 36 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0.167 | | effectiveRatio | 0.056 | |
| 69.77% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 827 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "lazily" | | 1 | "carefully" | | 2 | "slowly" | | 3 | "sharply" |
| |
| 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) | |
| 45.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 827 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "gloom" | | 1 | "quickened" | | 2 | "intricate" | | 3 | "scanned" | | 4 | "eyebrow" | | 5 | "flicked" | | 6 | "silence" | | 7 | "jaw clenched" | | 8 | "racing" |
| |
| 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 | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "jaw clenched" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 57 | | matches | | |
| 92.73% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 57 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 86 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 829 | | ratio | 0 | | matches | (empty) | |
| 75.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 1 | | matches | | 0 | "Strung together, they told a story at odds with the evidence in front of them." |
| |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 531 | | uniqueNames | 6 | | maxNameDensity | 3.39 | | worstName | "Quinn" | | maxWindowNameDensity | 5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 18 | | Tube | 1 | | Eva | 13 | | Kowalski | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Eva" | | 3 | "Kowalski" | | 4 | "Market" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 39 | | 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 | 829 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 86 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 36 | | mean | 23.03 | | std | 17.23 | | cv | 0.748 | | sampleLengths | | 0 | 64 | | 1 | 31 | | 2 | 35 | | 3 | 6 | | 4 | 25 | | 5 | 60 | | 6 | 7 | | 7 | 44 | | 8 | 7 | | 9 | 23 | | 10 | 10 | | 11 | 13 | | 12 | 12 | | 13 | 56 | | 14 | 50 | | 15 | 7 | | 16 | 54 | | 17 | 38 | | 18 | 20 | | 19 | 32 | | 20 | 10 | | 21 | 6 | | 22 | 20 | | 23 | 8 | | 24 | 12 | | 25 | 2 | | 26 | 13 | | 27 | 8 | | 28 | 24 | | 29 | 11 | | 30 | 8 | | 31 | 25 | | 32 | 31 | | 33 | 11 | | 34 | 35 | | 35 | 11 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 57 | | matches | (empty) | |
| 63.95% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 98 | | matches | | 0 | "were running" | | 1 | "was ticking" |
| |
| 43.19% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 86 | | ratio | 0.035 | | matches | | 0 | "Her gaze swept the scene, taking in the details – an intricate bone token clutched in one hand, a scatter of broken glass, dark splashes of blood." | | 1 | "Three years ago, she'd faced a similar situation – strange evidence, conflicting stories, an investigation that spiraled into something far darker and more dangerous than they'd anticipated." | | 2 | "Slowly, the pieces started to come together – a cluster of footprints here, a scrap of cloth there." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 528 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.032196969696969696 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.017045454545454544 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 86 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 86 | | mean | 9.64 | | std | 6.37 | | cv | 0.661 | | sampleLengths | | 0 | 17 | | 1 | 18 | | 2 | 16 | | 3 | 13 | | 4 | 20 | | 5 | 7 | | 6 | 4 | | 7 | 15 | | 8 | 11 | | 9 | 9 | | 10 | 3 | | 11 | 3 | | 12 | 12 | | 13 | 13 | | 14 | 12 | | 15 | 11 | | 16 | 8 | | 17 | 27 | | 18 | 2 | | 19 | 7 | | 20 | 10 | | 21 | 16 | | 22 | 12 | | 23 | 6 | | 24 | 4 | | 25 | 3 | | 26 | 4 | | 27 | 19 | | 28 | 10 | | 29 | 8 | | 30 | 5 | | 31 | 7 | | 32 | 5 | | 33 | 5 | | 34 | 27 | | 35 | 17 | | 36 | 7 | | 37 | 13 | | 38 | 12 | | 39 | 16 | | 40 | 9 | | 41 | 2 | | 42 | 5 | | 43 | 11 | | 44 | 10 | | 45 | 18 | | 46 | 15 | | 47 | 7 | | 48 | 31 | | 49 | 7 |
| |
| 80.62% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5116279069767442 | | totalSentences | 86 | | uniqueOpeners | 44 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 55 | | matches | | 0 | "Slowly, the pieces started to" | | 1 | "Somewhere out there, a clock" |
| | ratio | 0.036 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 55 | | matches | | 0 | "Her shoes crunched on the" | | 1 | "It was Eva Kowalski, the" | | 2 | "It was a young man," | | 3 | "His eyes stared sightlessly at" | | 4 | "Her gaze swept the scene," | | 5 | "She scanned the survivors huddled" | | 6 | "She still didn't have all" | | 7 | "she explained as Quinn frowned" | | 8 | "They moved carefully through the" | | 9 | "They worked in silence, each" | | 10 | "She took a deep breath." | | 11 | "She pushed the thought away." |
| | ratio | 0.218 | |
| 41.82% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 46 | | totalSentences | 55 | | matches | | 0 | "Detective Harlow Quinn ducked under" | | 1 | "Her shoes crunched on the" | | 2 | "The place had been out" | | 3 | "The beam of her torch" | | 4 | "Quinn quickened her pace." | | 5 | "a clipped voice greeted her" | | 6 | "It was Eva Kowalski, the" | | 7 | "Quinn nodded curtly." | | 8 | "Eva pushed her round glasses" | | 9 | "Quinn stepped around a rusted" | | 10 | "It was a young man," | | 11 | "His eyes stared sightlessly at" | | 12 | "Her gaze swept the scene," | | 13 | "Quinn straightened up, her leather" | | 14 | "She scanned the survivors huddled" | | 15 | "Something niggled at her, an" | | 16 | "Eva pursed her lips." | | 17 | "Quinn raised an eyebrow." | | 18 | "Quinn felt a tingle run" | | 19 | "Eva shrugged noncommittally, her red" |
| | ratio | 0.836 | |
| 90.91% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 55 | | matches | | 0 | "Now it was their turn." |
| | ratio | 0.018 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 1 | | matches | | 0 | "Three years ago, she'd faced a similar situation – strange evidence, conflicting stories, an investigation that spiraled into something far darker and more dang…" |
| |
| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 1 | | matches | | 0 | "Eva finished, her voice tight" |
| |
| 94.44% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "she explained (explain)" |
| | dialogueSentences | 36 | | tagDensity | 0.056 | | leniency | 0.111 | | rawRatio | 1 | | effectiveRatio | 0.111 | |