| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.98% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1247 | | totalAiIsmAdverbs | 2 | | 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) | |
| 63.91% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1247 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "echo" | | 1 | "hulking" | | 2 | "scanning" | | 3 | "etched" | | 4 | "pulsed" | | 5 | "scanned" | | 6 | "silence" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 209 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 209 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 218 | | 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 | 2 | | markdownWords | 6 | | totalWords | 1230 | | ratio | 0.005 | | matches | | 0 | "Dreams Brewed Fresh. Regrets Free." | | 1 | "smell" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 1120 | | uniqueNames | 11 | | maxNameDensity | 0.98 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 11 | | Morris | 5 | | Met | 1 | | Leicester | 1 | | Square | 1 | | Soho | 1 | | Victorian | 1 | | Veil | 1 | | Market | 1 | | Brewed | 1 | | Fresh | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Met" | | 3 | "Victorian" |
| | places | | | globalScore | 1 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 75 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like scarred flesh" |
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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 | 1230 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 218 | | matches | | 0 | "carrying that briefcase" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 88 | | mean | 13.98 | | std | 17.47 | | cv | 1.25 | | sampleLengths | | 0 | 10 | | 1 | 76 | | 2 | 33 | | 3 | 2 | | 4 | 57 | | 5 | 4 | | 6 | 33 | | 7 | 2 | | 8 | 25 | | 9 | 4 | | 10 | 55 | | 11 | 6 | | 12 | 6 | | 13 | 7 | | 14 | 3 | | 15 | 41 | | 16 | 6 | | 17 | 30 | | 18 | 20 | | 19 | 5 | | 20 | 1 | | 21 | 46 | | 22 | 4 | | 23 | 23 | | 24 | 6 | | 25 | 47 | | 26 | 3 | | 27 | 6 | | 28 | 76 | | 29 | 2 | | 30 | 2 | | 31 | 3 | | 32 | 21 | | 33 | 71 | | 34 | 14 | | 35 | 5 | | 36 | 32 | | 37 | 21 | | 38 | 2 | | 39 | 25 | | 40 | 2 | | 41 | 4 | | 42 | 2 | | 43 | 7 | | 44 | 2 | | 45 | 9 | | 46 | 5 | | 47 | 3 | | 48 | 24 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 209 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 202 | | matches | | 0 | "was humming" | | 1 | "was handing" |
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| 11.80% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 17 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 218 | | ratio | 0.046 | | matches | | 0 | "And the frame—she squatted, brushed aside the grime with a gloved hand—etched with a spiral motif." | | 1 | "Smelled of beeswax, burnt herbs, and something metallic—copper, or blood." | | 2 | "The watch on her left wrist—Morris’s old service watch, its leather strap cracked and faded—ticked once." | | 3 | "The scent deepened—incense, yes, and rot, but beneath it, ozone." | | 4 | "Another, teeth—human and otherwise—strung on wire." | | 5 | "He was handing something to the stall keeper—a small, bone-white token." | | 6 | "The keeper—a man with too many fingers—nodded." | | 7 | "The eyes—black, no whites—widened." | | 8 | "The stall keeper screamed—a sound like grinding glass—and dove into a pile of furs." | | 9 | "Then it shoved the briefcase forward—right into her line of fire—and ducked." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 530 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.02830188679245283 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0018867924528301887 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 218 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 218 | | mean | 5.64 | | std | 4.58 | | cv | 0.812 | | sampleLengths | | 0 | 10 | | 1 | 4 | | 2 | 20 | | 3 | 18 | | 4 | 14 | | 5 | 20 | | 6 | 3 | | 7 | 10 | | 8 | 6 | | 9 | 8 | | 10 | 6 | | 11 | 2 | | 12 | 7 | | 13 | 4 | | 14 | 21 | | 15 | 7 | | 16 | 7 | | 17 | 11 | | 18 | 4 | | 19 | 1 | | 20 | 4 | | 21 | 15 | | 22 | 9 | | 23 | 4 | | 24 | 2 | | 25 | 4 | | 26 | 9 | | 27 | 9 | | 28 | 2 | | 29 | 1 | | 30 | 4 | | 31 | 13 | | 32 | 3 | | 33 | 2 | | 34 | 2 | | 35 | 16 | | 36 | 2 | | 37 | 2 | | 38 | 4 | | 39 | 7 | | 40 | 4 | | 41 | 6 | | 42 | 2 | | 43 | 2 | | 44 | 2 | | 45 | 3 | | 46 | 4 | | 47 | 3 | | 48 | 7 | | 49 | 9 |
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| 52.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 22 | | diversityRatio | 0.3761467889908257 | | totalSentences | 218 | | uniqueOpeners | 82 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 153 | | matches | | 0 | "Just shoved a stack of" | | 1 | "Just a dead end." | | 2 | "Then she saw it." | | 3 | "Then the tunnel opened into" | | 4 | "Just a keyhole the shape" | | 5 | "Then it shoved the briefcase" | | 6 | "Just the distant hum." |
| | ratio | 0.046 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 153 | | matches | | 0 | "She vaulted the overflowing bin" | | 1 | "She hit the pavement on" | | 2 | "He was good." | | 3 | "Her voice cracked over the" | | 4 | "He didn’t look back." | | 5 | "Her breath came in tight," | | 6 | "She rounded the corner." | | 7 | "She stepped forward, scanning." | | 8 | "She’d seen it before." | | 9 | "Her fingers tightened on her" | | 10 | "It was thick." | | 11 | "She’d left her team chasing" | | 12 | "She reached for her radio." | | 13 | "They wouldn’t believe her." | | 14 | "They’d file it with the" | | 15 | "She holstered the radio." | | 16 | "She took the first step" | | 17 | "Her torch beam danced on" | | 18 | "She drew her pistol." | | 19 | "She scanned the stalls." |
| | ratio | 0.229 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 102 | | totalSentences | 153 | | matches | | 0 | "The alley wall exploded in" | | 1 | "Harlow Quinn didn’t flinch." | | 2 | "She vaulted the overflowing bin" | | 3 | "The echo of the gunshot" | | 4 | "Rain needled her face, cold" | | 5 | "She hit the pavement on" | | 6 | "He was good." | | 7 | "The one with the silver" | | 8 | "The same model from the" | | 9 | "The one never logged into" | | 10 | "Her voice cracked over the" | | 11 | "He didn’t look back." | | 12 | "Quinn followed, boots splashing through" | | 13 | "Her breath came in tight," | | 14 | "She rounded the corner." | | 15 | "A fire escape ladder, crusted" | | 16 | "A single flickering bulb buzzed" | | 17 | "The man was gone." | | 18 | "She stepped forward, scanning." | | 19 | "The skip overflowed with food" |
| | ratio | 0.667 | |
| 65.36% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 153 | | matches | | 0 | "As if she were a" | | 1 | "As if multiple people spoke" |
| | ratio | 0.013 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |