| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 19 | | tagDensity | 0.263 | | leniency | 0.526 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.55% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 918 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 34.64% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 918 | | totalAiIsms | 12 | | found | | 0 | | word | "skipped a beat" | | count | 1 |
| | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | word | "down her spine" | | count | 1 |
| | 6 | | | 7 | | | 8 | | | 9 | | | 10 | |
| | highlights | | 0 | "skipped a beat" | | 1 | "flicker" | | 2 | "etched" | | 3 | "unreadable" | | 4 | "chill" | | 5 | "down her spine" | | 6 | "could feel" | | 7 | "weight" | | 8 | "pounding" | | 9 | "streaming" | | 10 | "silence" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 93.35% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 3 | | narrationSentences | 79 | | matches | | 0 | "felt a chill" | | 1 | "filled with sorrow" | | 2 | "d with sorrow" |
| |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 79 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 93 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 916 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 41.30% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 690 | | uniqueNames | 5 | | maxNameDensity | 2.17 | | worstName | "Silas" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Aurora | 12 | | Silas | 15 | | Rory | 1 |
| | persons | | 0 | "Nest" | | 1 | "Aurora" | | 2 | "Silas" | | 3 | "Rory" |
| | places | | | globalScore | 0.413 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 916 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 93 | | matches | | |
| 72.93% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 32.71 | | std | 13.26 | | cv | 0.405 | | sampleLengths | | 0 | 35 | | 1 | 3 | | 2 | 59 | | 3 | 54 | | 4 | 42 | | 5 | 24 | | 6 | 36 | | 7 | 45 | | 8 | 15 | | 9 | 35 | | 10 | 33 | | 11 | 24 | | 12 | 21 | | 13 | 19 | | 14 | 35 | | 15 | 36 | | 16 | 36 | | 17 | 38 | | 18 | 44 | | 19 | 42 | | 20 | 30 | | 21 | 42 | | 22 | 41 | | 23 | 20 | | 24 | 24 | | 25 | 48 | | 26 | 33 | | 27 | 2 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 79 | | matches | (empty) | |
| 57.14% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 140 | | matches | | 0 | "was staring" | | 1 | "was watching" | | 2 | "was shaking" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 93 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 692 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.02745664739884393 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.004335260115606936 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 93 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 93 | | mean | 9.85 | | std | 5.64 | | cv | 0.573 | | sampleLengths | | 0 | 16 | | 1 | 10 | | 2 | 5 | | 3 | 4 | | 4 | 3 | | 5 | 16 | | 6 | 7 | | 7 | 15 | | 8 | 21 | | 9 | 3 | | 10 | 5 | | 11 | 3 | | 12 | 3 | | 13 | 5 | | 14 | 4 | | 15 | 5 | | 16 | 8 | | 17 | 5 | | 18 | 13 | | 19 | 6 | | 20 | 5 | | 21 | 8 | | 22 | 16 | | 23 | 7 | | 24 | 7 | | 25 | 10 | | 26 | 3 | | 27 | 4 | | 28 | 5 | | 29 | 7 | | 30 | 10 | | 31 | 7 | | 32 | 7 | | 33 | 5 | | 34 | 21 | | 35 | 19 | | 36 | 11 | | 37 | 4 | | 38 | 8 | | 39 | 20 | | 40 | 7 | | 41 | 8 | | 42 | 10 | | 43 | 8 | | 44 | 7 | | 45 | 8 | | 46 | 16 | | 47 | 6 | | 48 | 15 | | 49 | 6 |
| |
| 46.95% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.3333333333333333 | | totalSentences | 93 | | uniqueOpeners | 31 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 76 | | matches | (empty) | | ratio | 0 | |
| 56.84% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 76 | | matches | | 0 | "Her heart skipped a beat." | | 1 | "His eyes were wild, his" | | 2 | "He looked her way, and" | | 3 | "She blinked back into focus." | | 4 | "She knew everyone was watching" | | 5 | "He leaned on the bar," | | 6 | "Her throat felt tight, her" | | 7 | "She reached for her glass," | | 8 | "She took a deep breath," | | 9 | "He finished his drink and" | | 10 | "He sighed, running a hand" | | 11 | "She thought she had escaped," | | 12 | "It was only a matter" | | 13 | "She shook her head, her" | | 14 | "She wanted to believe him," | | 15 | "She had trusted him once," | | 16 | "She couldn't go through that" | | 17 | "He slid the envelope across" | | 18 | "She could feel the weight" | | 19 | "She glanced up at Silas," |
| | ratio | 0.408 | |
| 52.11% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 62 | | totalSentences | 76 | | matches | | 0 | "The door to the Raven's" | | 1 | "Her heart skipped a beat." | | 2 | "Silas stood in the doorway," | | 3 | "His eyes were wild, his" | | 4 | "The drink in his hand" | | 5 | "He looked her way, and" | | 6 | "Aurora couldn't breathe." | | 7 | "Memories flooded back, drowning her." | | 8 | "A beach house." | | 9 | "A stolen kiss." | | 10 | "Waves crashing against the shore." | | 11 | "The coppery taste of blood" | | 12 | "Betrayal etched on his face." | | 13 | "The words rang in Aurora's" | | 14 | "She blinked back into focus." | | 15 | "Silas was staring at her," | | 16 | "The bar was silent, the" | | 17 | "She knew everyone was watching" | | 18 | "Silas limped forward, his leg" | | 19 | "He leaned on the bar," |
| | ratio | 0.816 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 76 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 2 | | matches | | 0 | "She shook, her voice trembling" | | 1 | "He slid, his eyes pleading" |
| |
| 44.74% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "he breathed (breathe)" | | 1 | "He sighed (sigh)" |
| | dialogueSentences | 19 | | tagDensity | 0.105 | | leniency | 0.211 | | rawRatio | 1 | | effectiveRatio | 0.211 | |