| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 52 | | tagDensity | 0.385 | | leniency | 0.769 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 964 | | 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) | |
| 42.95% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 964 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "solace" | | 1 | "familiar" | | 2 | "flicker" | | 3 | "unreadable" | | 4 | "chill" | | 5 | "whisper" | | 6 | "traced" | | 7 | "silence" | | 8 | "charm" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 65 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 65 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | 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 | 962 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 99.75% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 15 | | wordCount | 597 | | uniqueNames | 9 | | maxNameDensity | 1.01 | | worstName | "Silas" | | maxWindowNameDensity | 2 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Aurora | 2 | | Tuesday | 1 | | Silas | 6 | | Man | 1 | | Hemmings | 1 | | Eva | 1 | | London | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Aurora" | | 3 | "Silas" | | 4 | "Man" | | 5 | "Hemmings" | | 6 | "Eva" |
| | places | | | globalScore | 0.997 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 50 | | glossingSentenceCount | 4 | | matches | | 0 | "something like woodsmoke and regret" | | 1 | "felt like a bruise deep beneath her ski" | | 2 | "Silas, seemingly oblivious, continue" | | 3 | "felt like a betrayal" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 962 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 22.9 | | std | 15.54 | | cv | 0.679 | | sampleLengths | | 0 | 66 | | 1 | 36 | | 2 | 7 | | 3 | 40 | | 4 | 32 | | 5 | 1 | | 6 | 52 | | 7 | 64 | | 8 | 28 | | 9 | 19 | | 10 | 9 | | 11 | 34 | | 12 | 14 | | 13 | 37 | | 14 | 27 | | 15 | 13 | | 16 | 5 | | 17 | 27 | | 18 | 45 | | 19 | 24 | | 20 | 15 | | 21 | 13 | | 22 | 5 | | 23 | 23 | | 24 | 13 | | 25 | 8 | | 26 | 32 | | 27 | 3 | | 28 | 17 | | 29 | 30 | | 30 | 18 | | 31 | 42 | | 32 | 32 | | 33 | 10 | | 34 | 30 | | 35 | 10 | | 36 | 9 | | 37 | 19 | | 38 | 15 | | 39 | 18 | | 40 | 5 | | 41 | 15 |
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| 99.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 65 | | matches | | |
| 61.11% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 96 | | matches | | 0 | "was polishing" | | 1 | "was discussing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 95 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 599 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.03005008347245409 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.011686143572621035 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 10.13 | | std | 5.89 | | cv | 0.582 | | sampleLengths | | 0 | 13 | | 1 | 31 | | 2 | 5 | | 3 | 17 | | 4 | 16 | | 5 | 8 | | 6 | 12 | | 7 | 7 | | 8 | 15 | | 9 | 25 | | 10 | 14 | | 11 | 16 | | 12 | 2 | | 13 | 1 | | 14 | 6 | | 15 | 12 | | 16 | 4 | | 17 | 16 | | 18 | 10 | | 19 | 4 | | 20 | 15 | | 21 | 3 | | 22 | 5 | | 23 | 16 | | 24 | 7 | | 25 | 9 | | 26 | 9 | | 27 | 10 | | 28 | 8 | | 29 | 10 | | 30 | 11 | | 31 | 6 | | 32 | 2 | | 33 | 8 | | 34 | 1 | | 35 | 7 | | 36 | 8 | | 37 | 5 | | 38 | 14 | | 39 | 13 | | 40 | 1 | | 41 | 24 | | 42 | 13 | | 43 | 8 | | 44 | 19 | | 45 | 6 | | 46 | 7 | | 47 | 5 | | 48 | 11 | | 49 | 16 |
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| 91.93% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5578947368421052 | | totalSentences | 95 | | uniqueOpeners | 53 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 63 | | matches | | 0 | "Usually a slow bleed of" | | 1 | "Then she saw him." | | 2 | "Just watched her, his expression" |
| | ratio | 0.048 | |
| 29.52% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 63 | | matches | | 0 | "She shook the water from" | | 1 | "She tossed her keys onto" | | 2 | "He slid a damp cloth" | | 3 | "He poured her a whiskey," | | 4 | "She took a sip, the" | | 5 | "He’d filled out, softened around" | | 6 | "He didn’t bother to turn" | | 7 | "She hadn’t heard it in" | | 8 | "She set her glass down" | | 9 | "He finally turned, a slow," | | 10 | "It didn’t reach his eyes." | | 11 | "She tested the name, the" | | 12 | "he observed, his gaze sweeping" | | 13 | "She managed a tight smile" | | 14 | "He chuckled, a dry, brittle" | | 15 | "He flagged down Silas, requesting" | | 16 | "She mirrored his tone" | | 17 | "He took a sip of" | | 18 | "He shrugged, dismissing her question" | | 19 | "His jaw tightened." |
| | ratio | 0.476 | |
| 55.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 51 | | totalSentences | 63 | | matches | | 0 | "The green neon of The" | | 1 | "Rain plastered strands of Aurora's" | | 2 | "A Tuesday night, nearing ten." | | 3 | "She shook the water from" | | 4 | "Silas was polishing glasses, a" | | 5 | "The bar smelled of stale" | | 6 | "Silas asked, not looking up" | | 7 | "She tossed her keys onto" | | 8 | "Silas finally met her gaze," | | 9 | "He slid a damp cloth" | | 10 | "He poured her a whiskey," | | 11 | "She took a sip, the" | | 12 | "The bar wasn't crowded." | | 13 | "A couple huddled near the" | | 14 | "The suit was tailored, expensive." | | 15 | "Hair, once a riot of" | | 16 | "He’d filled out, softened around" | | 17 | "the man said, his voice" | | 18 | "He didn’t bother to turn" | | 19 | "The name hung in the" |
| | ratio | 0.81 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 19 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 50.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 3 | | matches | | 0 | "Silas asked, not looking up" | | 1 | "the man said, his voice a low rasp" | | 2 | "She leaned, her voice barely a whisper" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "he observed (observe)" | | 1 | "He corrected (correct)" |
| | dialogueSentences | 52 | | tagDensity | 0.096 | | leniency | 0.192 | | rawRatio | 0.4 | | effectiveRatio | 0.077 | |