| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.96% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 622 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 622 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "flickered" | | 1 | "jaw clenched" | | 2 | "unreadable" | | 3 | "echoed" | | 4 | "pulse" | | 5 | "rhythmic" | | 6 | "weight" | | 7 | "echoing" | | 8 | "stomach" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
| | 1 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "jaw clenched" | | 1 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 62 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 62 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 65 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 4 | | totalWords | 616 | | ratio | 0.006 | | matches | | 0 | "clink" | | 1 | "tap-tap-tap" | | 2 | "tap-tap-tap" | | 3 | "tap-tap-tap" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 49.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 598 | | uniqueNames | 5 | | maxNameDensity | 2.01 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Raven | 1 | | Nest | 2 | | Quinn | 12 | | Tomás | 7 | | Herrera | 2 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Quinn" | | 3 | "Tomás" | | 4 | "Herrera" |
| | places | (empty) | | globalScore | 0.497 | | windowScore | 0.833 | |
| 91.86% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 1 | | matches | | 0 | "as if remembering something" |
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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 | 616 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 65 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 18 | | mean | 34.22 | | std | 23.59 | | cv | 0.689 | | sampleLengths | | 0 | 75 | | 1 | 72 | | 2 | 64 | | 3 | 44 | | 4 | 51 | | 5 | 37 | | 6 | 5 | | 7 | 47 | | 8 | 60 | | 9 | 31 | | 10 | 10 | | 11 | 43 | | 12 | 10 | | 13 | 9 | | 14 | 10 | | 15 | 9 | | 16 | 34 | | 17 | 5 |
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| 93.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 62 | | matches | | 0 | "was gone" | | 1 | "were locked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 106 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 65 | | ratio | 0.077 | | matches | | 0 | "She’d seen enough of this city to know that every shadow could hide a blade—or worse." | | 1 | "She didn’t need to see it to know—someone was moving." | | 2 | "Then she saw it—a set of rusted metal steps descending into darkness." | | 3 | "The air was thick with the scent of damp stone and something else—something sweet and metallic." | | 4 | "She recognized the bearing—military precision, just like hers." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 604 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.023178807947019868 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.004966887417218543 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 65 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 65 | | mean | 9.48 | | std | 5.22 | | cv | 0.551 | | sampleLengths | | 0 | 16 | | 1 | 19 | | 2 | 15 | | 3 | 25 | | 4 | 18 | | 5 | 12 | | 6 | 16 | | 7 | 11 | | 8 | 11 | | 9 | 4 | | 10 | 8 | | 11 | 3 | | 12 | 10 | | 13 | 23 | | 14 | 8 | | 15 | 12 | | 16 | 12 | | 17 | 2 | | 18 | 7 | | 19 | 11 | | 20 | 7 | | 21 | 5 | | 22 | 10 | | 23 | 12 | | 24 | 5 | | 25 | 11 | | 26 | 13 | | 27 | 17 | | 28 | 5 | | 29 | 3 | | 30 | 7 | | 31 | 5 | | 32 | 5 | | 33 | 11 | | 34 | 11 | | 35 | 10 | | 36 | 15 | | 37 | 9 | | 38 | 16 | | 39 | 3 | | 40 | 13 | | 41 | 19 | | 42 | 8 | | 43 | 9 | | 44 | 14 | | 45 | 5 | | 46 | 3 | | 47 | 2 | | 48 | 14 | | 49 | 10 |
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| 40.77% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.24615384615384617 | | totalSentences | 65 | | uniqueOpeners | 16 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 60 | | matches | | 0 | "Then she saw it—a set" | | 1 | "Then the tunnel opened into" |
| | ratio | 0.033 | |
| 93.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 60 | | matches | | 0 | "She had been chasing Tomás" | | 1 | "She’d seen enough of this" | | 2 | "She’d caught him watching her," | | 3 | "She didn’t need to see" | | 4 | "She turned the corner, her" | | 5 | "She could hear it now," | | 6 | "They moved in the shadows," | | 7 | "She had to know why." | | 8 | "She stepped forward, her boots" | | 9 | "She had no idea what" | | 10 | "She took the first step." | | 11 | "She could hear voices, faint" | | 12 | "His eyes were locked on" | | 13 | "She didn’t hesitate." | | 14 | "They staggered, their movements slowing," | | 15 | "She lunged for Tomás, her" | | 16 | "she growled, her voice rough" | | 17 | "She recognized the bearing—military precision," | | 18 | "It was something else." |
| | ratio | 0.317 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 50 | | totalSentences | 60 | | matches | | 0 | "The neon glow of the" | | 1 | "Detective Quinn’s breath fogged in" | | 2 | "The scent of damp stone" | | 3 | "She had been chasing Tomás" | | 4 | "The alley behind the Nest" | | 5 | "Quinn’s fingers tightened around the" | | 6 | "She’d seen enough of this" | | 7 | "Tomás had been working for" | | 8 | "She’d caught him watching her," | | 9 | "A distant *clink* of metal" | | 10 | "Quinn’s pulse spiked." | | 11 | "She didn’t need to see" | | 12 | "She turned the corner, her" | | 13 | "The alley narrowed, the walls" | | 14 | "She could hear it now," | | 15 | "The clique didn’t operate in" | | 16 | "They moved in the shadows," | | 17 | "She had to know why." | | 18 | "She stepped forward, her boots" | | 19 | "The steps creaked under her" |
| | ratio | 0.833 | |
| 83.33% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 60 | | matches | | | ratio | 0.017 | |
| 96.77% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 2 | | matches | | 0 | "She had been chasing Tomás Herrera for hours, ever since he’d vanished from the bar’s back room, his scarred forearm twitching as if remembering something." | | 1 | "They staggered, their movements slowing, their eyes widening in shock." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 1 | | matches | | 0 | "she growled, her voice rough with anger" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 4 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 1 | | effectiveRatio | 0.5 | |