| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.536 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1271 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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 | 1271 | | totalAiIsms | 28 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "footsteps" | | 1 | "echoed" | | 2 | "charm" | | 3 | "pulse" | | 4 | "chill" | | 5 | "scanning" | | 6 | "echoing" | | 7 | "glinting" | | 8 | "pulsed" | | 9 | "flicked" | | 10 | "could feel" | | 11 | "weight" | | 12 | "flickered" | | 13 | "echo" | | 14 | "reminder" | | 15 | "magnetic" | | 16 | "raced" | | 17 | "glistening" | | 18 | "beacon" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 89 | | matches | | |
| 62.60% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 4 | | narrationSentences | 89 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 102 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1271 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 1063 | | uniqueNames | 8 | | maxNameDensity | 0.75 | | worstName | "Harlow" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Harlow" | | discoveredNames | | Quinn | 1 | | Raven | 3 | | Nest | 3 | | Saint | 1 | | Christopher | 1 | | Harlow | 8 | | Tomás | 5 | | Morris | 2 |
| | persons | | 0 | "Quinn" | | 1 | "Nest" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Harlow" | | 5 | "Tomás" | | 6 | "Morris" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 77 | | glossingSentenceCount | 5 | | matches | | 0 | "pulse that seemed to sync with the thunder" | | 1 | "as if reacting to the market's energy" | | 2 | "chant that seemed to rise from the walls themselves" | | 3 | "as if urging her forward" | | 4 | "as if trying to wash away the decision" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.787 | | wordCount | 1271 | | matches | | 0 | "not her own face, but a younger version of herself, standing beside DS Morris, his" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 102 | | matches | | |
| 54.11% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 27.63 | | std | 9.38 | | cv | 0.339 | | sampleLengths | | 0 | 49 | | 1 | 29 | | 2 | 8 | | 3 | 28 | | 4 | 8 | | 5 | 36 | | 6 | 30 | | 7 | 24 | | 8 | 25 | | 9 | 41 | | 10 | 38 | | 11 | 9 | | 12 | 33 | | 13 | 14 | | 14 | 18 | | 15 | 25 | | 16 | 21 | | 17 | 20 | | 18 | 41 | | 19 | 43 | | 20 | 35 | | 21 | 27 | | 22 | 29 | | 23 | 22 | | 24 | 33 | | 25 | 33 | | 26 | 13 | | 27 | 30 | | 28 | 30 | | 29 | 29 | | 30 | 10 | | 31 | 34 | | 32 | 32 | | 33 | 31 | | 34 | 39 | | 35 | 26 | | 36 | 20 | | 37 | 40 | | 38 | 25 | | 39 | 27 | | 40 | 26 | | 41 | 22 | | 42 | 21 | | 43 | 32 | | 44 | 34 | | 45 | 31 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 89 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 176 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 102 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1066 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small bone-shaped charm" |
| | adverbCount | 15 | | adverbRatio | 0.014071294559099437 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0009380863039399625 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 102 | | echoCount | 0 | | echoWords | (empty) | |
| 97.56% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 102 | | mean | 12.46 | | std | 4.91 | | cv | 0.394 | | sampleLengths | | 0 | 13 | | 1 | 20 | | 2 | 16 | | 3 | 8 | | 4 | 17 | | 5 | 4 | | 6 | 8 | | 7 | 10 | | 8 | 7 | | 9 | 11 | | 10 | 8 | | 11 | 11 | | 12 | 17 | | 13 | 8 | | 14 | 7 | | 15 | 13 | | 16 | 10 | | 17 | 24 | | 18 | 14 | | 19 | 11 | | 20 | 12 | | 21 | 14 | | 22 | 15 | | 23 | 11 | | 24 | 11 | | 25 | 16 | | 26 | 9 | | 27 | 24 | | 28 | 9 | | 29 | 10 | | 30 | 4 | | 31 | 7 | | 32 | 11 | | 33 | 19 | | 34 | 6 | | 35 | 5 | | 36 | 16 | | 37 | 11 | | 38 | 9 | | 39 | 22 | | 40 | 19 | | 41 | 10 | | 42 | 14 | | 43 | 19 | | 44 | 14 | | 45 | 11 | | 46 | 10 | | 47 | 16 | | 48 | 11 | | 49 | 8 |
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| 44.12% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.23529411764705882 | | totalSentences | 102 | | uniqueOpeners | 24 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 1.40% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 47 | | totalSentences | 86 | | matches | | 0 | "She chased a silhouette that" | | 1 | "she barked, voice cracking through" | | 2 | "He smirked, eyes narrowing." | | 3 | "She lunged, boots splashing, grabbed" | | 4 | "He twisted, slipping his hand" | | 5 | "she demanded, pulling him closer" | | 6 | "He laughed, a short bark" | | 7 | "He tossed a small bone-shaped" | | 8 | "It clinked against the cobblestones" | | 9 | "She snatched it, feeling the" | | 10 | "she asked, voice low, eyes" | | 11 | "He glanced back at the" | | 12 | "He slipped through, the stone" | | 13 | "She stepped into the darkness," | | 14 | "Her flashlight cut a thin" | | 15 | "she called, voice echoing off" | | 16 | "He wore a battered leather" | | 17 | "she said, the name slipping" | | 18 | "He tilted his head, a" | | 19 | "She stared at the bone" |
| | ratio | 0.547 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 85 | | totalSentences | 86 | | matches | | 0 | "Harlow Quinn's leather coat clung" | | 1 | "She chased a silhouette that" | | 2 | "she barked, voice cracking through" | | 3 | "The suspect turned, a flash" | | 4 | "He smirked, eyes narrowing." | | 5 | "She lunged, boots splashing, grabbed" | | 6 | "The fabric tore, revealing a" | | 7 | "He twisted, slipping his hand" | | 8 | "she demanded, pulling him closer" | | 9 | "He laughed, a short bark" | | 10 | "He tossed a small bone-shaped" | | 11 | "It clinked against the cobblestones" | | 12 | "Harlow's heart hammered faster than" | | 13 | "The token glowed faintly, a" | | 14 | "She snatched it, feeling the" | | 15 | "she asked, voice low, eyes" | | 16 | "He glanced back at the" | | 17 | "The entrance to the abandoned" | | 18 | "He slipped through, the stone" | | 19 | "Harlow hesitated, the token heavy" |
| | ratio | 0.988 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 81.28% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 5 | | matches | | 0 | "Rain hammered the cobblestones, turning the alley into a mirror that swallowed footsteps." | | 1 | "She glanced at the bone token again, its glow intensifying as if reacting to the market's energy." | | 2 | "He tossed the mirror into a nearby stall, shattering it into a thousand shards that reflected the market's lanterns." | | 3 | "The token in her palm warmed, as if urging her forward." | | 4 | "She lifted her chin, eyes narrowing, and stepped toward the vortex, the market's chant rising to a crescendo." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 7 | | matches | | 0 | "she barked, voice cracking through the storm" | | 1 | "she called, voice echoing off the walls" | | 2 | "she said, the name slipping out like a breath" | | 3 | "he asked, voice muffled by the mask" | | 4 | "she said, eyes glinting" | | 5 | "Tomás warned, his voice low" | | 6 | "she demanded, voice shaking stone" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 7 | | fancyTags | | 0 | "she barked (bark)" | | 1 | "he hissed (hiss)" | | 2 | "she demanded (demand)" | | 3 | "he whispered (whisper)" | | 4 | "Tomás warned (warn)" | | 5 | "he whispered (whisper)" | | 6 | "she demanded (demand)" |
| | dialogueSentences | 28 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |