| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 7 | | tagDensity | 0.571 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 885 | | 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) | |
| 15.25% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 885 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "fractured" | | 1 | "jaw clenched" | | 2 | "gloom" | | 3 | "weight" | | 4 | "pulse" | | 5 | "rhythmic" | | 6 | "unspoken" | | 7 | "flickered" | | 8 | "sentinels" | | 9 | "clandestine" | | 10 | "familiar" | | 11 | "stomach" | | 12 | "tension" | | 13 | "echo" | | 14 | "footsteps" |
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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 | "flicker of emotion" | | count | 1 |
|
| | highlights | | 0 | "jaw clenched" | | 1 | "a flash of recognition" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 60 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 60 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 63 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 886 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 816 | | uniqueNames | 11 | | maxNameDensity | 0.98 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 8 | | Morris | 1 | | Raven | 1 | | Nest | 1 | | Tube | 1 | | Camden | 1 | | Veil | 1 | | Market | 1 | | London | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Raven" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | 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 | 886 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 63 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 23 | | mean | 38.52 | | std | 24.05 | | cv | 0.624 | | sampleLengths | | 0 | 67 | | 1 | 83 | | 2 | 45 | | 3 | 80 | | 4 | 58 | | 5 | 101 | | 6 | 42 | | 7 | 48 | | 8 | 29 | | 9 | 38 | | 10 | 34 | | 11 | 7 | | 12 | 25 | | 13 | 26 | | 14 | 8 | | 15 | 31 | | 16 | 11 | | 17 | 25 | | 18 | 36 | | 19 | 22 | | 20 | 23 | | 21 | 20 | | 22 | 27 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 60 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 145 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 63 | | ratio | 0.143 | | matches | | 0 | "The Raven’s Nest — she registered it just then, the distinctive green neon sign pulsating through the mist above the stair entrance." | | 1 | "A sudden crack — the suspect stumbled as a loose step gave way." | | 2 | "Farther down, she could hear the murmur of voices — low, harsh whispers slicing through the air filmed with an electrical charge." | | 3 | "At the bottom of the stairs was a vaulted cavern carved into the old Tube station beneath Camden — the Veil Market." | | 4 | "Quinn’s brain ticked through the risks — danger, unknown terrain, enemies who’d vanish her with one clean strike." | | 5 | "She could call for backup — wait, plan, secure a better angle." | | 6 | "Without warning, he doubled down a narrow corridor lined with booths stacked high with twisted trinkets—shards of bone, frozen fire, dried herbs pressed neat beneath glass." | | 7 | "Somewhere in this maze lay answers—and danger waiting just beyond reach." | | 8 | "The choice was hers: step beyond that veil — into the unknown choked with history and hazard—or let the suspect vanish into this dark market’s endless labyrinth." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 265 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 10 | | adverbRatio | 0.03773584905660377 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.007547169811320755 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 63 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 63 | | mean | 14.06 | | std | 8.56 | | cv | 0.608 | | sampleLengths | | 0 | 18 | | 1 | 22 | | 2 | 16 | | 3 | 11 | | 4 | 26 | | 5 | 21 | | 6 | 22 | | 7 | 3 | | 8 | 11 | | 9 | 31 | | 10 | 14 | | 11 | 22 | | 12 | 6 | | 13 | 6 | | 14 | 16 | | 15 | 30 | | 16 | 10 | | 17 | 16 | | 18 | 4 | | 19 | 14 | | 20 | 14 | | 21 | 13 | | 22 | 3 | | 23 | 22 | | 24 | 17 | | 25 | 46 | | 26 | 5 | | 27 | 22 | | 28 | 15 | | 29 | 22 | | 30 | 7 | | 31 | 10 | | 32 | 9 | | 33 | 25 | | 34 | 4 | | 35 | 18 | | 36 | 5 | | 37 | 15 | | 38 | 8 | | 39 | 12 | | 40 | 14 | | 41 | 7 | | 42 | 25 | | 43 | 8 | | 44 | 10 | | 45 | 8 | | 46 | 8 | | 47 | 26 | | 48 | 5 | | 49 | 5 |
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| 70.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.4603174603174603 | | totalSentences | 63 | | uniqueOpeners | 29 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 57 | | matches | | 0 | "More than once she had" | | 1 | "Somewhere in this maze lay" |
| | ratio | 0.035 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 57 | | matches | | 0 | "Her leather coat, soaked through," | | 1 | "Her salt-and-pepper hair plastered to" | | 2 | "Her breath hitched as she" | | 3 | "She followed, boots thudding against" | | 4 | "She crept deeper, senses straining." | | 5 | "Her eyes caught a flash" | | 6 | "His silhouette slipped through an" | | 7 | "She wiped rain from her" | | 8 | "She could call for backup" | | 9 | "She stepped forward and crossed" | | 10 | "She didn’t pause for the" | | 11 | "He stumbled but didn’t break." | | 12 | "she hissed, voice tight with" | | 13 | "Her boot caught in a" |
| | ratio | 0.246 | |
| 74.04% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 57 | | matches | | 0 | "The rain hammered down, turning" | | 1 | "Detective Harlow Quinn’s boots slapped" | | 2 | "Her leather coat, soaked through," | | 3 | "Her salt-and-pepper hair plastered to" | | 4 | "The figure glanced back, a" | | 5 | "Quinn tightened her grip on" | | 6 | "The distant rumble of thunder" | | 7 | "Tonight felt different." | | 8 | "The weight of the past" | | 9 | "A faint glow spilled downward," | | 10 | "The Raven’s Nest — she" | | 11 | "Her breath hitched as she" | | 12 | "This place wasn’t just a" | | 13 | "The suspect disappeared out of" | | 14 | "Quinn’s pulse thudded louder, the" | | 15 | "The memory of" | | 16 | "A sudden crack — the" | | 17 | "Quinn didn’t pause." | | 18 | "She followed, boots thudding against" | | 19 | "The scent here was heavier," |
| | ratio | 0.772 | |
| 87.72% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 57 | | matches | | 0 | "To descend into this subterranean" |
| | ratio | 0.018 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 3 | | matches | | 0 | "Ahead, the suspect’s pace faltered momentarily at a cold brick wall that bisected the alley, then slipped down a narrow stairwell barely visible beneath peeling…" | | 1 | "The lighting was faint as a witch’s candle, shadows lurking behind pillars and racks packed with oddities that would have been laughable if not so undeniably re…" | | 2 | "Quinn’s brain ticked through the risks — danger, unknown terrain, enemies who’d vanish her with one clean strike." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 1 | | matches | | 0 | "she hissed, voice tight with years of loss" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "he spat (spit)" | | 1 | "she hissed (hiss)" |
| | dialogueSentences | 7 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 1 | | effectiveRatio | 0.571 | |