| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 2 | | adverbTags | | 0 | "She circled back [back]" | | 1 | "She crouched again [again]" |
| | dialogueSentences | 62 | | tagDensity | 0.323 | | leniency | 0.645 | | rawRatio | 0.1 | | effectiveRatio | 0.065 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1333 | | 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) | |
| 39.98% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1333 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoed" | | 2 | "traced" | | 3 | "flicked" | | 4 | "dancing" | | 5 | "scanned" | | 6 | "flickered" | | 7 | "echoes" | | 8 | "gloom" | | 9 | "etched" | | 10 | "whisper" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 110 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 110 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 152 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1329 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 12.57% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 764 | | uniqueNames | 6 | | maxNameDensity | 2.75 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 3 | | Quinn | 21 | | Alan | 1 | | Price | 15 | | Plumes | 1 | | Compass | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Alan" | | 3 | "Price" |
| | places | (empty) | | globalScore | 0.126 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | 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 | 1329 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 152 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 68 | | mean | 19.54 | | std | 11.81 | | cv | 0.604 | | sampleLengths | | 0 | 33 | | 1 | 8 | | 2 | 24 | | 3 | 34 | | 4 | 25 | | 5 | 19 | | 6 | 21 | | 7 | 18 | | 8 | 44 | | 9 | 16 | | 10 | 37 | | 11 | 25 | | 12 | 15 | | 13 | 35 | | 14 | 37 | | 15 | 41 | | 16 | 13 | | 17 | 51 | | 18 | 15 | | 19 | 39 | | 20 | 23 | | 21 | 28 | | 22 | 24 | | 23 | 20 | | 24 | 10 | | 25 | 45 | | 26 | 9 | | 27 | 38 | | 28 | 14 | | 29 | 24 | | 30 | 10 | | 31 | 24 | | 32 | 26 | | 33 | 35 | | 34 | 29 | | 35 | 18 | | 36 | 15 | | 37 | 25 | | 38 | 6 | | 39 | 33 | | 40 | 11 | | 41 | 7 | | 42 | 25 | | 43 | 14 | | 44 | 11 | | 45 | 23 | | 46 | 8 | | 47 | 19 | | 48 | 31 | | 49 | 9 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 154 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 152 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 768 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.028645833333333332 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005208333333333333 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 152 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 152 | | mean | 8.74 | | std | 5.49 | | cv | 0.628 | | sampleLengths | | 0 | 6 | | 1 | 12 | | 2 | 15 | | 3 | 8 | | 4 | 15 | | 5 | 9 | | 6 | 5 | | 7 | 11 | | 8 | 11 | | 9 | 3 | | 10 | 4 | | 11 | 18 | | 12 | 5 | | 13 | 2 | | 14 | 8 | | 15 | 11 | | 16 | 9 | | 17 | 9 | | 18 | 3 | | 19 | 10 | | 20 | 8 | | 21 | 5 | | 22 | 10 | | 23 | 3 | | 24 | 2 | | 25 | 24 | | 26 | 3 | | 27 | 13 | | 28 | 12 | | 29 | 9 | | 30 | 16 | | 31 | 4 | | 32 | 5 | | 33 | 12 | | 34 | 4 | | 35 | 7 | | 36 | 8 | | 37 | 11 | | 38 | 6 | | 39 | 18 | | 40 | 16 | | 41 | 5 | | 42 | 16 | | 43 | 9 | | 44 | 9 | | 45 | 8 | | 46 | 15 | | 47 | 4 | | 48 | 9 | | 49 | 8 |
| |
| 61.81% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.39072847682119205 | | totalSentences | 151 | | uniqueOpeners | 59 | |
| 33.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 101 | | matches | | 0 | "Instead she stared into an" |
| | ratio | 0.01 | |
| 73.47% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 101 | | matches | | 0 | "She paused beneath a flickering" | | 1 | "She traced one line with" | | 2 | "she said, voice low, controlled," | | 3 | "He frowned, leaned back against" | | 4 | "She held her torch steady." | | 5 | "Her leather watch caught the" | | 6 | "He crouched again, momentarily distracted" | | 7 | "He flicked at the phone" | | 8 | "She shook her head, rose" | | 9 | "She swept her torch over" | | 10 | "He frowned, stepping aside." | | 11 | "She straightened, wiped her glove" | | 12 | "She traced a path of" | | 13 | "He perched on an overturned" | | 14 | "He looked at her, surprised." | | 15 | "She circled back to the" | | 16 | "She crouched again, skirting the" | | 17 | "She tapped her watch, silencing" | | 18 | "He rose, shouldered his kit." | | 19 | "She offered him a flat" |
| | ratio | 0.366 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 95 | | totalSentences | 101 | | matches | | 0 | "Footsteps echoed through the hollow" | | 1 | "Detective Harlow Quinn’s leather-soled boots" | | 2 | "She paused beneath a flickering" | | 3 | "A hand, pale as bone," | | 4 | "DS Alan Price knelt beside" | | 5 | "Quinn crouched, angled her head." | | 6 | "The red ran in six" | | 7 | "She traced one line with" | | 8 | "she said, voice low, controlled," | | 9 | "The chalk refused to cake." | | 10 | "He frowned, leaned back against" | | 11 | "Quinn brushed gravel away from" | | 12 | "A shard of glass glinted" | | 13 | "Price rose, stooped, scuffed the" | | 14 | "She held her torch steady." | | 15 | "The fragment bore a straight" | | 16 | "Price’s eyes narrowed." | | 17 | "Quinn said, She shone light" | | 18 | "The cut was too clean" | | 19 | "A distant drip echoed." |
| | ratio | 0.941 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 101 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 17 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, voice low, controlled," |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 3 | | fancyTags | | 0 | "he muttered (mutter)" | | 1 | "she breathed (breathe)" | | 2 | "He snapped (snap)" |
| | dialogueSentences | 62 | | tagDensity | 0.097 | | leniency | 0.194 | | rawRatio | 0.5 | | effectiveRatio | 0.097 | |