| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 86 | | tagDensity | 0.012 | | leniency | 0.023 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1526 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 90.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1526 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "weight" | | 1 | "silence" | | 2 | "flickered" |
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| 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 | 120 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 120 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 205 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1529 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 65 | | wordCount | 863 | | uniqueNames | 8 | | maxNameDensity | 3.36 | | worstName | "Mei" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Mei" | | discoveredNames | | Greek | 1 | | Street | 1 | | Raven | 1 | | Nest | 1 | | Lin | 1 | | Rory | 25 | | Mei | 29 | | Silas | 6 |
| | persons | | 0 | "Nest" | | 1 | "Lin" | | 2 | "Rory" | | 3 | "Mei" | | 4 | "Silas" |
| | places | | 0 | "Greek" | | 1 | "Street" | | 2 | "Raven" |
| | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | 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 | 1529 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 205 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 138 | | mean | 11.08 | | std | 11.24 | | cv | 1.015 | | sampleLengths | | 0 | 34 | | 1 | 29 | | 2 | 7 | | 3 | 32 | | 4 | 3 | | 5 | 1 | | 6 | 8 | | 7 | 1 | | 8 | 1 | | 9 | 33 | | 10 | 4 | | 11 | 31 | | 12 | 48 | | 13 | 3 | | 14 | 7 | | 15 | 11 | | 16 | 31 | | 17 | 12 | | 18 | 2 | | 19 | 6 | | 20 | 2 | | 21 | 65 | | 22 | 15 | | 23 | 8 | | 24 | 14 | | 25 | 10 | | 26 | 13 | | 27 | 6 | | 28 | 21 | | 29 | 8 | | 30 | 44 | | 31 | 13 | | 32 | 6 | | 33 | 21 | | 34 | 2 | | 35 | 2 | | 36 | 24 | | 37 | 13 | | 38 | 21 | | 39 | 9 | | 40 | 3 | | 41 | 6 | | 42 | 3 | | 43 | 6 | | 44 | 8 | | 45 | 1 | | 46 | 8 | | 47 | 3 | | 48 | 2 | | 49 | 9 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 120 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 168 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 205 | | ratio | 0.005 | | matches | | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 900 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.02666666666666667 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0044444444444444444 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 205 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 205 | | mean | 7.46 | | std | 6.7 | | cv | 0.898 | | sampleLengths | | 0 | 18 | | 1 | 16 | | 2 | 4 | | 3 | 4 | | 4 | 9 | | 5 | 12 | | 6 | 3 | | 7 | 4 | | 8 | 16 | | 9 | 16 | | 10 | 3 | | 11 | 1 | | 12 | 3 | | 13 | 5 | | 14 | 1 | | 15 | 1 | | 16 | 12 | | 17 | 21 | | 18 | 4 | | 19 | 8 | | 20 | 20 | | 21 | 3 | | 22 | 5 | | 23 | 11 | | 24 | 13 | | 25 | 6 | | 26 | 3 | | 27 | 10 | | 28 | 3 | | 29 | 7 | | 30 | 11 | | 31 | 8 | | 32 | 11 | | 33 | 12 | | 34 | 12 | | 35 | 2 | | 36 | 6 | | 37 | 2 | | 38 | 4 | | 39 | 6 | | 40 | 3 | | 41 | 12 | | 42 | 15 | | 43 | 11 | | 44 | 14 | | 45 | 15 | | 46 | 8 | | 47 | 3 | | 48 | 11 | | 49 | 10 |
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| 44.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.28780487804878047 | | totalSentences | 205 | | uniqueOpeners | 59 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 109 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 109 | | matches | | 0 | "She looked up without thinking" | | 1 | "She stepped forward and then" | | 2 | "She collided with Mei and" | | 3 | "Her face had lost its" | | 4 | "He moved with the slight" | | 5 | "His auburn hair, streaked grey" | | 6 | "He looked at the two" | | 7 | "Her straight black hair swung" | | 8 | "His hazel eyes narrowed, then" | | 9 | "He uncapped something dark without" | | 10 | "He gave them space, but" | | 11 | "Her stature at five-six always" | | 12 | "Her hands shook." | | 13 | "She blinked hard." | | 14 | "He tapped the bar once" | | 15 | "She grabbed Mei's hand." | | 16 | "She covered it with her" | | 17 | "Her shoulders shook once, twice." | | 18 | "They stood like that while" | | 19 | "She switched it off." |
| | ratio | 0.22 | |
| 15.05% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 97 | | totalSentences | 109 | | matches | | 0 | "The green neon buzzed above" | | 1 | "Rory wiped the counter." | | 2 | "The maps on the wall" | | 3 | "A clock ticked behind the" | | 4 | "The door opened." | | 5 | "She looked up without thinking" | | 6 | "A woman stood in the" | | 7 | "Rory stopped wiping." | | 8 | "The woman blinked." | | 9 | "Rain dripped from her chin." | | 10 | "Mei Lin laughed once, a" | | 11 | "She stepped forward and then" | | 12 | "Rory vaulted the bar before" | | 13 | "She collided with Mei and" | | 14 | "Mei had cut her hair." | | 15 | "Her face had lost its" | | 16 | "A small silver hoop caught" | | 17 | "Rory pulled back enough to" | | 18 | "The bright blue of her" | | 19 | "Mei's eyes were the same," |
| | ratio | 0.89 | |
| 45.87% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 109 | | matches | | 0 | "Now it brushed her jaw," |
| | ratio | 0.009 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 1 | | matches | | 0 | "This Mei held herself like someone who paid for posture lessons." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |