| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 15 | | tagDensity | 0.467 | | leniency | 0.933 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.01% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 556 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 1.08% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 556 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "charged" | | 1 | "amidst" | | 2 | "pounding" | | 3 | "scanned" | | 4 | "glinting" | | 5 | "cacophony" | | 6 | "intricate" | | 7 | "weight" | | 8 | "echoed" | | 9 | "clenching" |
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| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "heart pounded in chest" | | count | 1 |
| | 1 | | label | "eyes widened/narrowed" | | count | 1 |
| | 2 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "heart hammered in her chest" | | 1 | "eyes narrowed" | | 2 | "the air was thick with" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 33 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 33 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 41 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 558 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 16 | | wordCount | 439 | | uniqueNames | 3 | | maxNameDensity | 3.19 | | worstName | "Harlow" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Harlow" | | discoveredNames | | | persons | | | places | | | globalScore | 0 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 30 | | 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 | 558 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 41 | | matches | (empty) | |
| 83.51% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 18 | | mean | 31 | | std | 13.71 | | cv | 0.442 | | sampleLengths | | 0 | 43 | | 1 | 48 | | 2 | 56 | | 3 | 53 | | 4 | 32 | | 5 | 21 | | 6 | 27 | | 7 | 24 | | 8 | 29 | | 9 | 33 | | 10 | 34 | | 11 | 37 | | 12 | 28 | | 13 | 8 | | 14 | 43 | | 15 | 17 | | 16 | 18 | | 17 | 7 |
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| 94.63% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 33 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 83 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 41 | | ratio | 0.073 | | matches | | 0 | "Wooden stalls lined the crowded underground space, each displaying an array of peculiar objects - glinting amulets, bubbling potions, ancient books with cracked spines." | | 1 | "Harlow ignored them all, her focus singular - find the suspect." | | 2 | "\"You've got some nerve following me here,\" the hooded figure - a man, judging by his voice - said as he turned to face her." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 437 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 6 | | adverbRatio | 0.013729977116704805 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.006864988558352402 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 41 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 41 | | mean | 13.61 | | std | 5.63 | | cv | 0.414 | | sampleLengths | | 0 | 17 | | 1 | 12 | | 2 | 14 | | 3 | 17 | | 4 | 15 | | 5 | 12 | | 6 | 4 | | 7 | 20 | | 8 | 14 | | 9 | 16 | | 10 | 6 | | 11 | 17 | | 12 | 12 | | 13 | 24 | | 14 | 19 | | 15 | 13 | | 16 | 21 | | 17 | 27 | | 18 | 15 | | 19 | 9 | | 20 | 11 | | 21 | 18 | | 22 | 12 | | 23 | 8 | | 24 | 13 | | 25 | 25 | | 26 | 9 | | 27 | 20 | | 28 | 17 | | 29 | 12 | | 30 | 16 | | 31 | 3 | | 32 | 5 | | 33 | 8 | | 34 | 17 | | 35 | 18 | | 36 | 7 | | 37 | 10 | | 38 | 9 | | 39 | 9 | | 40 | 7 |
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| 82.11% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.5365853658536586 | | totalSentences | 41 | | uniqueOpeners | 22 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 33 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 5 | | totalSentences | 33 | | matches | | 0 | "She scanned the alley, her" | | 1 | "It emanated from beneath an" | | 2 | "She heard the creak of" | | 3 | "She pressed forward, deeper into" | | 4 | "She found herself in a" |
| | ratio | 0.152 | |
| 66.06% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 26 | | totalSentences | 33 | | matches | | 0 | "Detective Harlow Quinn charged through" | | 1 | "The suspect, a hooded figure," | | 2 | "The streetlights reflected off the" | | 3 | "Harlow yelled, her voice nearly" | | 4 | "The suspect ignored her command," | | 5 | "Harlow followed close behind, her" | | 6 | "The suspect was gone." | | 7 | "She scanned the alley, her" | | 8 | "It emanated from beneath an" | | 9 | "She heard the creak of" | | 10 | "Harlow shouldered her way through" | | 11 | "The cacophony of voices, the" | | 12 | "A woman with a shaved" | | 13 | "Harlow ignored them all, her" | | 14 | "She pressed forward, deeper into" | | 15 | "Harlow surged forward, shoving aside" | | 16 | "She found herself in a" | | 17 | "the hooded figure - a" | | 18 | "Harlow replied, her voice steady" | | 19 | "The man laughed, a grating" |
| | ratio | 0.788 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 33 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 1 | | matches | | 0 | "A woman with a shaved head and intricate tattoos snaking up her arms eyed Harlow warily, her fingers tightening around a large, curved blade at her hip." |
| |
| 53.57% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 1 | | matches | | 0 | "Harlow demanded, her fists clenching" |
| |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 4 | | fancyTags | | 0 | "Harlow yelled (yell)" | | 1 | "he brushed (brush)" | | 2 | "a man judging (a man judging)" | | 3 | "Harlow demanded (demand)" |
| | dialogueSentences | 15 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.8 | | effectiveRatio | 0.533 | |