| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 571 | | 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) | |
| 64.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 571 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "streaming" | | 1 | "flickered" | | 2 | "footsteps" | | 3 | "etched" |
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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 | 69 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 69 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 72 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 570 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 95.85% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 11 | | wordCount | 554 | | uniqueNames | 6 | | maxNameDensity | 1.08 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Victorian | 1 | | Veil | 1 | | Market | 1 | | Morris | 1 | | Quinn | 6 |
| | persons | | 0 | "Victorian" | | 1 | "Morris" | | 2 | "Quinn" |
| | places | | | globalScore | 0.958 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 39 | | 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 | 570 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 72 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 19 | | std | 17.2 | | cv | 0.906 | | sampleLengths | | 0 | 3 | | 1 | 28 | | 2 | 2 | | 3 | 6 | | 4 | 60 | | 5 | 2 | | 6 | 41 | | 7 | 21 | | 8 | 6 | | 9 | 13 | | 10 | 46 | | 11 | 15 | | 12 | 4 | | 13 | 56 | | 14 | 2 | | 15 | 45 | | 16 | 21 | | 17 | 4 | | 18 | 11 | | 19 | 23 | | 20 | 5 | | 21 | 42 | | 22 | 19 | | 23 | 5 | | 24 | 29 | | 25 | 32 | | 26 | 4 | | 27 | 14 | | 28 | 7 | | 29 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 69 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 112 | | matches | (empty) | |
| 63.49% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 72 | | ratio | 0.028 | | matches | | 0 | "Graffiti blurred past—tags she'd seen before, gang signs, something inked in a language that didn't belong to any street crew." | | 1 | "The suspect—lean, dark-haired, wearing a hoodie that said \"London Grind\" — weaved between stalls." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 559 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.025044722719141325 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0017889087656529517 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 72 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 72 | | mean | 7.92 | | std | 5.31 | | cv | 0.671 | | sampleLengths | | 0 | 3 | | 1 | 16 | | 2 | 12 | | 3 | 2 | | 4 | 3 | | 5 | 3 | | 6 | 13 | | 7 | 20 | | 8 | 11 | | 9 | 16 | | 10 | 2 | | 11 | 12 | | 12 | 11 | | 13 | 3 | | 14 | 2 | | 15 | 13 | | 16 | 7 | | 17 | 4 | | 18 | 5 | | 19 | 5 | | 20 | 6 | | 21 | 7 | | 22 | 6 | | 23 | 9 | | 24 | 15 | | 25 | 3 | | 26 | 3 | | 27 | 9 | | 28 | 7 | | 29 | 8 | | 30 | 7 | | 31 | 4 | | 32 | 12 | | 33 | 29 | | 34 | 15 | | 35 | 2 | | 36 | 3 | | 37 | 7 | | 38 | 10 | | 39 | 14 | | 40 | 11 | | 41 | 14 | | 42 | 7 | | 43 | 4 | | 44 | 5 | | 45 | 2 | | 46 | 4 | | 47 | 11 | | 48 | 12 | | 49 | 5 |
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| 57.87% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.3888888888888889 | | totalSentences | 72 | | uniqueOpeners | 28 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 61 | | matches | | 0 | "Just a single drainpipe, slick" | | 1 | "Then he ducked behind a" | | 2 | "Just a symbol etched into" | | 3 | "Then it burned." |
| | ratio | 0.066 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 61 | | matches | | 0 | "He bolted left." | | 1 | "He didn't stop." | | 2 | "They never stopped." | | 3 | "She pushed off the wall," | | 4 | "Her lungs burned from the" | | 5 | "She crouched, rain dripping off" | | 6 | "she muttered, pulling out her" | | 7 | "She clicked the torch on," | | 8 | "She drew her weapon." | | 9 | "She'd heard whispers about the" | | 10 | "She'd written it off as" | | 11 | "He glanced back, saw her," | | 12 | "She pushed through, losing sight" | | 13 | "He slipped through without looking" | | 14 | "She thought of Morris." |
| | ratio | 0.246 | |
| 82.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 46 | | totalSentences | 61 | | matches | | 0 | "He bolted left." | | 1 | "Quinn's boots slapped wet pavement" | | 2 | "The alley swallowed him whole," | | 3 | "He didn't stop." | | 4 | "They never stopped." | | 5 | "She pushed off the wall," | | 6 | "Graffiti blurred past—tags she'd seen" | | 7 | "Her lungs burned from the" | | 8 | "Quinn skidded to a halt" | | 9 | "The brick wall stood seven" | | 10 | "She crouched, rain dripping off" | | 11 | "The grate was loose." | | 12 | "Someone had moved it recently." | | 13 | "she muttered, pulling out her" | | 14 | "The drop was eight feet," | | 15 | "She clicked the torch on," | | 16 | "The air smelled of mildew," | | 17 | "Something warm and floral, like" | | 18 | "A door stood ajar at" | | 19 | "She drew her weapon." |
| | ratio | 0.754 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 85.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 2 | | matches | | 0 | "Stalls lined the walls: glass cases filled with vials of shimmering liquid, cages holding things that clicked and hissed, books bound in leather that looked too…" | | 1 | "A supernatural black market that moved with the full moon." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 5 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 1 | | effectiveRatio | 0.4 | |