| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1642 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "carefully" | | 1 | "very" | | 2 | "gently" |
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| 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) | |
| 72.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1642 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "chaotic" | | 1 | "tapestry" | | 2 | "weight" | | 3 | "vibrated" | | 4 | "could feel" |
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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 | 166 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 166 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 180 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1665 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 1469 | | uniqueNames | 9 | | maxNameDensity | 0.82 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | High | 1 | | Street | 1 | | Raven | 1 | | Nest | 1 | | Tube | 1 | | Morris | 3 | | Shoreditch | 1 | | Quinn | 12 |
| | persons | | 0 | "Raven" | | 1 | "Morris" | | 2 | "Quinn" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Shoreditch" |
| | globalScore | 1 | | windowScore | 1 | |
| 99.49% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 99 | | glossingSentenceCount | 2 | | matches | | 0 | "smelled like old grease and rust" | | 1 | "seemed heavier than their contents warranted" |
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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 | 1665 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 180 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 49 | | mean | 33.98 | | std | 23.43 | | cv | 0.69 | | sampleLengths | | 0 | 54 | | 1 | 68 | | 2 | 37 | | 3 | 11 | | 4 | 46 | | 5 | 41 | | 6 | 2 | | 7 | 56 | | 8 | 37 | | 9 | 23 | | 10 | 66 | | 11 | 7 | | 12 | 73 | | 13 | 50 | | 14 | 94 | | 15 | 36 | | 16 | 11 | | 17 | 70 | | 18 | 40 | | 19 | 46 | | 20 | 44 | | 21 | 20 | | 22 | 63 | | 23 | 7 | | 24 | 40 | | 25 | 6 | | 26 | 22 | | 27 | 2 | | 28 | 31 | | 29 | 3 | | 30 | 15 | | 31 | 25 | | 32 | 43 | | 33 | 4 | | 34 | 16 | | 35 | 44 | | 36 | 63 | | 37 | 84 | | 38 | 52 | | 39 | 17 | | 40 | 19 | | 41 | 9 | | 42 | 40 | | 43 | 16 | | 44 | 1 | | 45 | 29 | | 46 | 40 | | 47 | 37 | | 48 | 5 |
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| 98.92% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 166 | | matches | | 0 | "was filed" | | 1 | "was forgotten" | | 2 | "was bolted" | | 3 | "was corroded" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 265 | | matches | | 0 | "wasn't looking" | | 1 | "was fumbling" | | 2 | "was already moving" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 22 | | semicolonCount | 0 | | flaggedSentences | 17 | | totalSentences | 180 | | ratio | 0.094 | | matches | | 0 | "Quinn's shoes slapped wet concrete as she rounded the corner onto Camden High Street, her breath ragged, the suspect — stocky build, dark hoodie, twenty yards ahead — cutting left toward the old market stalls." | | 1 | "The motion sent a sharp pain through her left knee — the one she'd never had fixed after Morris went down." | | 2 | "At the far end, he shouldered through a door she hadn't seen — or hadn't existed — five seconds ago." | | 3 | "Faint sound — music, low and droning." | | 4 | "She crossed the gap — three feet of rain-dark air over a six-storey drop — and landed in a crouch." | | 5 | "Not a shop, not a stall — a sprawling, chaotic bazaar hidden beneath the city." | | 6 | "And people — dozens of them, moving between the stalls, haggling, laughing, carrying bags that seemed heavier than their contents warranted." | | 7 | "The opening was wide enough to drop through, but there was nothing to land on — just open air and a hard floor ten feet below." | | 8 | "The air hit her — warm, humid, thick with the smell of incense and something metallic she couldn't place." | | 9 | "A heavyset man stood behind a counter covered in feathers — real feathers, arranged in patterns that shifted when she wasn't looking directly at them." | | 10 | "She could feel it — a weight in her pocket that had no authority." | | 11 | "The suspect's footprints — wet from the rain — tracked across the stone floor and disappeared around a bend." | | 12 | "No — not a dead end." | | 13 | "She holstered her weapon — no room to draw it in there — and wedged herself into the gap." | | 14 | "The crack narrowed, tightened, then released her into another space — larger, emptier, lit by a single overhead bulb that swung gently in a draft." | | 15 | "He laughed — a short, broken sound." | | 16 | "Somewhere below, she heard water flowing — not a pipe, something natural, something old." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1452 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.026859504132231406 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.003443526170798898 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 180 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 180 | | mean | 9.25 | | std | 6.99 | | cv | 0.756 | | sampleLengths | | 0 | 7 | | 1 | 35 | | 2 | 4 | | 3 | 8 | | 4 | 10 | | 5 | 17 | | 6 | 3 | | 7 | 7 | | 8 | 16 | | 9 | 10 | | 10 | 4 | | 11 | 1 | | 12 | 5 | | 13 | 5 | | 14 | 21 | | 15 | 6 | | 16 | 11 | | 17 | 4 | | 18 | 21 | | 19 | 4 | | 20 | 8 | | 21 | 9 | | 22 | 20 | | 23 | 11 | | 24 | 4 | | 25 | 3 | | 26 | 3 | | 27 | 2 | | 28 | 7 | | 29 | 7 | | 30 | 5 | | 31 | 6 | | 32 | 8 | | 33 | 5 | | 34 | 18 | | 35 | 4 | | 36 | 6 | | 37 | 2 | | 38 | 6 | | 39 | 13 | | 40 | 6 | | 41 | 12 | | 42 | 11 | | 43 | 4 | | 44 | 11 | | 45 | 10 | | 46 | 20 | | 47 | 13 | | 48 | 2 | | 49 | 6 |
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| 51.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.36666666666666664 | | totalSentences | 180 | | uniqueOpeners | 66 | |
| 68.03% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 147 | | matches | | 0 | "Just smooth grain and a" | | 1 | "Then he straightened and jerked" | | 2 | "Somewhere below, she heard water" |
| | ratio | 0.02 | |
| 62.18% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 58 | | totalSentences | 147 | | matches | | 0 | "She'd spotted him leaving The" | | 1 | "She'd been ready." | | 2 | "He vaulted a newspaper stand." | | 3 | "She swallowed it and kept" | | 4 | "He didn't look back." | | 5 | "He rounded the corner into" | | 6 | "Her torch cut a pale" | | 7 | "She reached the door." | | 8 | "It didn't budge." | | 9 | "She pressed her ear to" | | 10 | "She stepped back and looked" | | 11 | "She reached for the lowest" | | 12 | "Her leather watch caught on" | | 13 | "She unclasped it, stuffed it" | | 14 | "She slid twice before reaching" | | 15 | "She crossed the gap —" | | 16 | "She watched him weave through" | | 17 | "She pressed her palms flat" | | 18 | "She'd arrived to find him" | | 19 | "She'd spent two years building" |
| | ratio | 0.395 | |
| 45.03% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 122 | | totalSentences | 147 | | matches | | 0 | "The rain hammered the pavement" | | 1 | "Quinn's shoes slapped wet concrete" | | 2 | "The street was empty." | | 3 | "Everyone with sense had gone" | | 4 | "She'd spotted him leaving The" | | 5 | "She'd been ready." | | 6 | "He vaulted a newspaper stand." | | 7 | "Quinn vaulted it after him." | | 8 | "The motion sent a sharp" | | 9 | "She swallowed it and kept" | | 10 | "He didn't look back." | | 11 | "He rounded the corner into" | | 12 | "Quinn drew her weapon." | | 13 | "The alley smelled like old" | | 14 | "Her torch cut a pale" | | 15 | "A sliver of amber light" | | 16 | "She reached the door." | | 17 | "It didn't budge." | | 18 | "She pressed her ear to" | | 19 | "Voices layered over each other." |
| | ratio | 0.83 | |
| 34.01% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 147 | | matches | | | ratio | 0.007 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 5 | | matches | | 0 | "Vendors stood behind counters stacked with things that defied her ability to name them." | | 1 | "And people — dozens of them, moving between the stalls, haggling, laughing, carrying bags that seemed heavier than their contents warranted." | | 2 | "She could feel it — a weight in her pocket that had no authority." | | 3 | "The crack narrowed, tightened, then released her into another space — larger, emptier, lit by a single overhead bulb that swung gently in a draft." | | 4 | "The suspect was already moving, his flashlight bobbing ahead of her." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 22 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0.25 | | effectiveRatio | 0.091 | |