| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.313 | | leniency | 0.625 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 85.77% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1054 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "sharply" | | 1 | "completely" | | 2 | "slowly" |
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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) | |
| 76.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1054 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "flickered" | | 1 | "footsteps" | | 2 | "echoed" | | 3 | "gloom" | | 4 | "marble" |
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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 | 124 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 124 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 134 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 10 | | totalWords | 1054 | | ratio | 0.009 | | matches | | 0 | "Wrong" | | 1 | "This is wrong." | | 2 | "Turn back," | | 3 | "You don't belong here." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 9 | | wordCount | 994 | | uniqueNames | 8 | | maxNameDensity | 0.2 | | worstName | "Soho" | | maxWindowNameDensity | 0.5 | | worstWindowName | "Soho" | | discoveredNames | | Old | 1 | | Compton | 1 | | Street | 1 | | Raven | 1 | | Nest | 1 | | Soho | 2 | | Bank | 1 | | Victorian | 1 |
| | persons | | | places | | 0 | "Old" | | 1 | "Compton" | | 2 | "Street" | | 3 | "Raven" | | 4 | "Soho" |
| | globalScore | 1 | | windowScore | 1 | |
| 79.58% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like jars of preserved" | | 1 | "quite hold onto" |
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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 | 1054 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 134 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 23.42 | | std | 20.06 | | cv | 0.857 | | sampleLengths | | 0 | 21 | | 1 | 2 | | 2 | 36 | | 3 | 52 | | 4 | 12 | | 5 | 35 | | 6 | 57 | | 7 | 26 | | 8 | 25 | | 9 | 2 | | 10 | 31 | | 11 | 59 | | 12 | 9 | | 13 | 9 | | 14 | 30 | | 15 | 2 | | 16 | 53 | | 17 | 30 | | 18 | 5 | | 19 | 6 | | 20 | 6 | | 21 | 32 | | 22 | 13 | | 23 | 48 | | 24 | 5 | | 25 | 44 | | 26 | 3 | | 27 | 2 | | 28 | 4 | | 29 | 35 | | 30 | 57 | | 31 | 15 | | 32 | 9 | | 33 | 80 | | 34 | 30 | | 35 | 5 | | 36 | 42 | | 37 | 4 | | 38 | 10 | | 39 | 4 | | 40 | 38 | | 41 | 10 | | 42 | 7 | | 43 | 45 | | 44 | 4 |
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| 99.60% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 124 | | matches | | 0 | "been gutted" | | 1 | "was gone" |
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| 75.78% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 161 | | matches | | 0 | "were weaving" | | 1 | "was choosing" | | 2 | "was heading" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 134 | | ratio | 0.007 | | matches | | 0 | "The rain vanished behind me; in its place, my own footsteps echoed too loud." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 814 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.038083538083538086 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.009828009828009828 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 134 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 134 | | mean | 7.87 | | std | 5.82 | | cv | 0.74 | | sampleLengths | | 0 | 21 | | 1 | 2 | | 2 | 6 | | 3 | 19 | | 4 | 4 | | 5 | 7 | | 6 | 26 | | 7 | 7 | | 8 | 13 | | 9 | 6 | | 10 | 3 | | 11 | 9 | | 12 | 12 | | 13 | 9 | | 14 | 14 | | 15 | 4 | | 16 | 1 | | 17 | 2 | | 18 | 7 | | 19 | 21 | | 20 | 2 | | 21 | 2 | | 22 | 18 | | 23 | 20 | | 24 | 6 | | 25 | 2 | | 26 | 3 | | 27 | 9 | | 28 | 11 | | 29 | 2 | | 30 | 6 | | 31 | 11 | | 32 | 7 | | 33 | 7 | | 34 | 10 | | 35 | 19 | | 36 | 13 | | 37 | 3 | | 38 | 14 | | 39 | 3 | | 40 | 6 | | 41 | 9 | | 42 | 19 | | 43 | 11 | | 44 | 2 | | 45 | 2 | | 46 | 10 | | 47 | 1 | | 48 | 16 | | 49 | 11 |
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| 63.68% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.44029850746268656 | | totalSentences | 134 | | uniqueOpeners | 59 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 99 | | matches | | 0 | "Then he pushed the door" | | 1 | "Instead, I followed him through" | | 2 | "Even the rain was gone." | | 3 | "Just the sound of a" |
| | ratio | 0.04 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 99 | | matches | | 0 | "My voice cracked against the" | | 1 | "My breath came hard." | | 2 | "My lungs burned with cold," | | 3 | "His face was ordinary." | | 4 | "He could have been any" | | 5 | "I kept my voice level," | | 6 | "I should have called it" | | 7 | "It smelled of damp stone" | | 8 | "I descended a metal staircase" | | 9 | "It could not exist under" | | 10 | "His smile had gone." | | 11 | "He looked at me with" | | 12 | "He turned and walked into" | | 13 | "I watched his back disappear" | | 14 | "I couldn't make out the" | | 15 | "My radio crackled at my" | | 16 | "I reached up and turned" | | 17 | "I stepped over the line." | | 18 | "He stood under a sign" | | 19 | "I moved toward him, forcing" |
| | ratio | 0.333 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 99 | | matches | | 0 | "The sole of my boot" | | 1 | "My voice cracked against the" | | 2 | "The figure ahead didn't falter," | | 3 | "My breath came hard." | | 4 | "My lungs burned with cold," | | 5 | "The moment our eyes met," | | 6 | "*This is wrong.* But my" | | 7 | "The alley opened onto a" | | 8 | "The suspect stood beside a" | | 9 | "His face was ordinary." | | 10 | "A small gold stud in" | | 11 | "He could have been any" | | 12 | "A man who had just" | | 13 | "I kept my voice level," | | 14 | "A proper, friendly smile that" | | 15 | "I should have called it" | | 16 | "The substation had been gutted" | | 17 | "It smelled of damp stone" | | 18 | "The rain vanished behind me;" | | 19 | "Nothing but the hum of" |
| | ratio | 0.687 | |
| 50.51% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 99 | | matches | | 0 | "Now we were weaving through" |
| | ratio | 0.01 | |
| 73.17% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 4 | | matches | | 0 | "Three streets back, I'd spotted him loitering outside The Raven's Nest, standing in the green glow of the neon sign like he wanted to be seen." | | 1 | "There was a narrow corridor of exposed brick and flaking paint, lit by a single emergency bulb that flickered." | | 2 | "I pushed deeper into the market, feeling the cold seep through my boots, feeling the suspicion prickle across my neck." | | 3 | "The detective in me catalogued everything: the bone tokens exchanging hands, the bottles of black liquid, the maps of places that didn't exist on any city chart…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0 | | effectiveRatio | 0 | |