| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 2 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.24% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 952 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "sharply" | | 1 | "softly" | | 2 | "utterly" |
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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) | |
| 47.48% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 952 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "reminder" | | 1 | "race" | | 2 | "predator" | | 3 | "echoed" | | 4 | "weight" | | 5 | "footsteps" | | 6 | "echoing" | | 7 | "pulsed" | | 8 | "stomach" | | 9 | "flicker" |
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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 | 80 | | matches | (empty) | |
| 89.29% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 80 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 82 | | 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 | 947 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 9 | | wordCount | 940 | | uniqueNames | 8 | | maxNameDensity | 0.21 | | worstName | "London" | | maxWindowNameDensity | 0.5 | | worstWindowName | "London" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | London | 2 | | Camden | 1 | | Town | 1 | | Morris | 1 | | Sauer | 1 |
| | persons | | | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "London" | | 3 | "Camden" | | 4 | "Town" |
| | globalScore | 1 | | windowScore | 1 | |
| 69.35% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 2 | | matches | | 0 | "fabrics that seemed to drink the light" | | 1 | "not-quite" |
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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 | 947 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 82 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 20 | | mean | 47.35 | | std | 33.41 | | cv | 0.706 | | sampleLengths | | 0 | 78 | | 1 | 95 | | 2 | 91 | | 3 | 73 | | 4 | 6 | | 5 | 76 | | 6 | 10 | | 7 | 3 | | 8 | 65 | | 9 | 57 | | 10 | 3 | | 11 | 49 | | 12 | 105 | | 13 | 16 | | 14 | 78 | | 15 | 50 | | 16 | 32 | | 17 | 21 | | 18 | 3 | | 19 | 36 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 80 | | matches | (empty) | |
| 52.94% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 136 | | matches | | 0 | "was flagging" | | 1 | "was teeming" | | 2 | "was trying" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 82 | | ratio | 0.012 | | matches | | 0 | "The faces that turned to her were not merely curious; they were ancient, predatory, and utterly alien." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 797 | | adjectiveStacks | 2 | | stackExamples | | 0 | "cold, exhaust-fumed air." | | 1 | "same deep, fundamental wrongness" |
| | adverbCount | 25 | | adverbRatio | 0.03136762860727729 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.010037641154328732 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 82 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 82 | | mean | 11.55 | | std | 6.36 | | cv | 0.55 | | sampleLengths | | 0 | 21 | | 1 | 5 | | 2 | 13 | | 3 | 16 | | 4 | 9 | | 5 | 3 | | 6 | 1 | | 7 | 10 | | 8 | 16 | | 9 | 15 | | 10 | 25 | | 11 | 3 | | 12 | 17 | | 13 | 4 | | 14 | 15 | | 15 | 21 | | 16 | 19 | | 17 | 15 | | 18 | 3 | | 19 | 8 | | 20 | 12 | | 21 | 13 | | 22 | 24 | | 23 | 8 | | 24 | 3 | | 25 | 9 | | 26 | 11 | | 27 | 18 | | 28 | 6 | | 29 | 9 | | 30 | 12 | | 31 | 14 | | 32 | 8 | | 33 | 10 | | 34 | 13 | | 35 | 10 | | 36 | 10 | | 37 | 3 | | 38 | 17 | | 39 | 18 | | 40 | 4 | | 41 | 25 | | 42 | 1 | | 43 | 27 | | 44 | 13 | | 45 | 17 | | 46 | 3 | | 47 | 14 | | 48 | 8 | | 49 | 13 |
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| 54.07% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.3902439024390244 | | totalSentences | 82 | | uniqueOpeners | 32 | |
| 85.47% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 78 | | matches | | 0 | "Just a terrified kid who" | | 1 | "Just a soft, final click" |
| | ratio | 0.026 | |
| 81.54% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 78 | | matches | | 0 | "He was fast, this one." | | 1 | "Her lungs burned." | | 2 | "He vaulted a pile of" | | 3 | "She ploughed straight through them," | | 4 | "He glanced back, just for" | | 5 | "Her worn leather watch was" | | 6 | "He was flagging." | | 7 | "His movements grew sloppier, his" | | 8 | "She pushed harder, her own" | | 9 | "He veered sharply, away from" | | 10 | "She slowed her pace, a" | | 11 | "He fumbled at the rusted" | | 12 | "She closed the distance, her" | | 13 | "He produced something small and" | | 14 | "She saw it clearly in" | | 15 | "He pressed it against the" | | 16 | "He slipped through and the" | | 17 | "Her hand went to the" | | 18 | "It was teeming." | | 19 | "He had melted into the" |
| | ratio | 0.346 | |
| 56.15% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 78 | | matches | | 0 | "The sole of her right" | | 1 | "He was fast, this one." | | 2 | "A wiry silhouette swallowed and" | | 3 | "Rain slicked the tarmac, turning" | | 4 | "Each gasp was a mouthful" | | 5 | "Her lungs burned." | | 6 | "Pain was a reminder she" | | 7 | "He vaulted a pile of" | | 8 | "She ploughed straight through them," | | 9 | "He glanced back, just for" | | 10 | "The chase twisted through a" | | 11 | "Here, the only light came" | | 12 | "Her worn leather watch was" | | 13 | "He was flagging." | | 14 | "His movements grew sloppier, his" | | 15 | "She pushed harder, her own" | | 16 | "A rhythm honed by years" | | 17 | "He veered sharply, away from" | | 18 | "A dead end." | | 19 | "She slowed her pace, a" |
| | ratio | 0.808 | |
| 64.10% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 78 | | matches | | 0 | "Before she could take a" |
| | ratio | 0.013 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 7 | | matches | | 0 | "He vaulted a pile of black bin bags, landing with a sure-footed grace that infuriated her." | | 1 | "Just a soft, final click that echoed, impossibly loud in the drumming rain." | | 2 | "Stalls fashioned from old railway sleepers and scavenged metal displayed wares that made her stomach clench." | | 3 | "Cages holding creatures that jittered and chittered with too many legs." | | 4 | "A man bargaining for a gnarled root had fingers that were too long, ending in black, chitinous nails." | | 5 | "A woman haggling over a silver locket had eyes that were solid pools of black, reflecting the strange lights with an unnerving depth." | | 6 | "The faces that turned to her were not merely curious; they were ancient, predatory, and utterly alien." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |