| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 34 | | tagDensity | 0.206 | | leniency | 0.412 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1445 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 27.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1445 | | totalAiIsms | 21 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "shattered" | | 1 | "echoing" | | 2 | "unreadable" | | 3 | "traced" | | 4 | "flicked" | | 5 | "gloom" | | 6 | "velvet" | | 7 | "echo" | | 8 | "scanned" | | 9 | "etched" | | 10 | "gleaming" | | 11 | "footsteps" | | 12 | "tracing" | | 13 | "glint" | | 14 | "stark" | | 15 | "chilled" | | 16 | "aligned" | | 17 | "silence" | | 18 | "pulsed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 188 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 188 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 215 | | 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 | 1406 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 46.95% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 77 | | wordCount | 1116 | | uniqueNames | 19 | | maxNameDensity | 2.06 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 23 | | Tube | 1 | | Camden | 1 | | Kowalski | 1 | | Veil | 1 | | Market | 1 | | Aurora | 2 | | Fabric | 1 | | Cool | 1 | | Patel | 9 | | Eva | 14 | | Morris | 2 | | Fingernails | 1 | | Fog | 3 | | Needle | 6 | | Frost | 3 | | Compass | 3 | | Rift | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Aurora" | | 4 | "Fabric" | | 5 | "Patel" | | 6 | "Eva" | | 7 | "Morris" | | 8 | "Fog" | | 9 | "Needle" | | 10 | "Frost" | | 11 | "Compass" | | 12 | "Rift" |
| | places | (empty) | | globalScore | 0.47 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | 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 | 1406 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 215 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 61 | | mean | 23.05 | | std | 16.66 | | cv | 0.723 | | sampleLengths | | 0 | 64 | | 1 | 55 | | 2 | 46 | | 3 | 9 | | 4 | 29 | | 5 | 75 | | 6 | 22 | | 7 | 28 | | 8 | 56 | | 9 | 21 | | 10 | 30 | | 11 | 53 | | 12 | 29 | | 13 | 17 | | 14 | 12 | | 15 | 22 | | 16 | 19 | | 17 | 49 | | 18 | 16 | | 19 | 16 | | 20 | 14 | | 21 | 48 | | 22 | 24 | | 23 | 19 | | 24 | 20 | | 25 | 39 | | 26 | 4 | | 27 | 13 | | 28 | 30 | | 29 | 42 | | 30 | 22 | | 31 | 11 | | 32 | 6 | | 33 | 30 | | 34 | 52 | | 35 | 7 | | 36 | 14 | | 37 | 41 | | 38 | 12 | | 39 | 10 | | 40 | 10 | | 41 | 24 | | 42 | 19 | | 43 | 3 | | 44 | 5 | | 45 | 9 | | 46 | 39 | | 47 | 13 | | 48 | 18 | | 49 | 14 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 188 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 262 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 16 | | semicolonCount | 0 | | flaggedSentences | 14 | | totalSentences | 215 | | ratio | 0.065 | | matches | | 0 | "The air reeked of damp stone and something sharper—ozone, like a storm trapped underground." | | 1 | "Whispers of it had crossed her desk for months, tied to that clique she tracked—Aurora and her lot." | | 2 | "Rails vanished into black tunnels, but faint scratches marred the concrete lip—claw-like, spaced wide." | | 3 | "Three years since DS Morris vanished on a case like this—routine raid turned nightmare." | | 4 | "Needle in her pocket spun wild now, tugging left—toward the tunnel." | | 5 | "Tiny punctures dotted the rail—sucked clean, like mouthparts." | | 6 | "No blood loss explained frost—drained, not spilled." | | 7 | "Defensive posture wrong—arms up, but palms out, pushing nothing." | | 8 | "Victim's tattoos pulsed faint under light—sigils matching the compass face." | | 9 | "Rift cracks open—not full portal, tear." | | 10 | "Token snapped in panic—sealed the tear half-perfected." | | 11 | "Needle spun once more—pointing dead at her feet." | | 12 | "Blood welled—real blood, pattering red." | | 13 | "A hand—pale, clawed—brushed the edge." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1116 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.017025089605734768 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.002688172043010753 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 215 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 215 | | mean | 6.54 | | std | 4.26 | | cv | 0.652 | | sampleLengths | | 0 | 13 | | 1 | 9 | | 2 | 14 | | 3 | 14 | | 4 | 14 | | 5 | 5 | | 6 | 16 | | 7 | 12 | | 8 | 5 | | 9 | 3 | | 10 | 4 | | 11 | 10 | | 12 | 11 | | 13 | 13 | | 14 | 13 | | 15 | 9 | | 16 | 4 | | 17 | 5 | | 18 | 8 | | 19 | 21 | | 20 | 10 | | 21 | 16 | | 22 | 12 | | 23 | 18 | | 24 | 13 | | 25 | 6 | | 26 | 11 | | 27 | 11 | | 28 | 7 | | 29 | 21 | | 30 | 8 | | 31 | 7 | | 32 | 1 | | 33 | 1 | | 34 | 4 | | 35 | 12 | | 36 | 17 | | 37 | 6 | | 38 | 8 | | 39 | 5 | | 40 | 8 | | 41 | 5 | | 42 | 25 | | 43 | 6 | | 44 | 9 | | 45 | 5 | | 46 | 11 | | 47 | 6 | | 48 | 2 | | 49 | 5 |
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| 87.13% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5255813953488372 | | totalSentences | 215 | | uniqueOpeners | 113 | |
| 20.20% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 165 | | matches | | | ratio | 0.006 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 165 | | matches | | 0 | "Her boots crunched over shattered" | | 1 | "She spotted the body first." | | 2 | "His chest gaped with three" | | 3 | "She circled the corpse, salt-and-pepper" | | 4 | "Her worn leather satchel slumped" | | 5 | "She traced a chalk outline" | | 6 | "Her worn leather watch caught" | | 7 | "She scanned the platform." | | 8 | "She checked her watch: 2:17" | | 9 | "She knelt again, peering under" | | 10 | "She knew better." | | 11 | "She paced the body, boots" | | 12 | "She followed its pull, flashlight" | | 13 | "He checked his handheld." | | 14 | "She scraped a sample into" | | 15 | "Her mind clicked pieces." | | 16 | "Her voice cut steel" | | 17 | "He hustled off." | | 18 | "She dropped to knees, prying" | | 19 | "She smeared blood on the" |
| | ratio | 0.139 | |
| 63.03% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 131 | | totalSentences | 165 | | matches | | 0 | "Detective Harlow Quinn flashed her" | | 1 | "Rust flaked from the metal" | | 2 | "Her boots crunched over shattered" | | 3 | "Floodlights hummed overhead, casting jagged" | | 4 | "The air reeked of damp" | | 5 | "She spotted the body first." | | 6 | "His chest gaped with three" | | 7 | "None at all." | | 8 | "Quinn's brown eyes narrowed." | | 9 | "She circled the corpse, salt-and-pepper" | | 10 | "Eva Kowalski knelt nearby, round" | | 11 | "Her worn leather satchel slumped" | | 12 | "She traced a chalk outline" | | 13 | "Quinn crouched beside her." | | 14 | "Eva glanced up, green eyes" | | 15 | "Quinn's gaze flicked to the" | | 16 | "Velvet drapes hung limp over" | | 17 | "A sign in looping script" | | 18 | "Whispers of it had crossed" | | 19 | "Quinn prodded the man's cloak" |
| | ratio | 0.794 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 165 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 1 | | matches | | 0 | "Velvet drapes hung limp over booths peddling jars of glowing sludge and amulets that hummed faintly." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |