| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.276 | | leniency | 0.552 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 951 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 68.45% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 951 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "pulsed" | | 1 | "stomach" | | 2 | "traced" | | 3 | "stark" | | 4 | "racing" | | 5 | "flicked" |
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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 | 82 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 82 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 103 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 7 | | markdownWords | 7 | | totalWords | 948 | | ratio | 0.007 | | matches | | 0 | "placed" | | 1 | "crack" | | 2 | "clean" | | 3 | "supernatural" | | 4 | "am" | | 5 | "sheen" | | 6 | "ritual" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 88.94% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 737 | | uniqueNames | 7 | | maxNameDensity | 1.22 | | worstName | "Davies" | | maxWindowNameDensity | 2 | | worstWindowName | "Davies" | | discoveredNames | | Tube | 2 | | Oxfords | 1 | | Davies | 9 | | Camden | 1 | | Veil | 3 | | Market | 2 | | Compass | 1 |
| | persons | | | places | (empty) | | globalScore | 0.889 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 50 | | glossingSentenceCount | 1 | | matches | | 0 | "as if reacting to my presence" |
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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 | 948 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 103 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 24.95 | | std | 19.15 | | cv | 0.768 | | sampleLengths | | 0 | 83 | | 1 | 10 | | 2 | 65 | | 3 | 6 | | 4 | 24 | | 5 | 47 | | 6 | 24 | | 7 | 28 | | 8 | 52 | | 9 | 11 | | 10 | 8 | | 11 | 57 | | 12 | 2 | | 13 | 25 | | 14 | 40 | | 15 | 44 | | 16 | 7 | | 17 | 17 | | 18 | 3 | | 19 | 44 | | 20 | 10 | | 21 | 15 | | 22 | 24 | | 23 | 26 | | 24 | 34 | | 25 | 8 | | 26 | 40 | | 27 | 44 | | 28 | 20 | | 29 | 28 | | 30 | 4 | | 31 | 29 | | 32 | 3 | | 33 | 12 | | 34 | 12 | | 35 | 29 | | 36 | 8 | | 37 | 5 |
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| 83.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 82 | | matches | | 0 | "been dropped" | | 1 | "was frozen" | | 2 | "was lit" | | 3 | "were covered" | | 4 | "was smudged" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 128 | | matches | | |
| 31.90% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 1 | | flaggedSentences | 4 | | totalSentences | 103 | | ratio | 0.039 | | matches | | 0 | "The victim’s clothes were too clean for a place like this—no grime, no rips, not even a speck of dust." | | 1 | "The victim’s skin was pale, almost waxy, but there was something else—an odd shimmer to it, like oil on water." | | 2 | "These were symbols—arcane, deliberate." | | 3 | "The Veil Market wasn’t just a black market; it was a *supernatural* black market." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 602 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.03322259136212625 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.008305647840531562 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 103 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 103 | | mean | 9.2 | | std | 6.59 | | cv | 0.716 | | sampleLengths | | 0 | 20 | | 1 | 20 | | 2 | 18 | | 3 | 15 | | 4 | 10 | | 5 | 8 | | 6 | 2 | | 7 | 9 | | 8 | 25 | | 9 | 20 | | 10 | 11 | | 11 | 6 | | 12 | 18 | | 13 | 6 | | 14 | 3 | | 15 | 7 | | 16 | 8 | | 17 | 21 | | 18 | 8 | | 19 | 21 | | 20 | 3 | | 21 | 16 | | 22 | 12 | | 23 | 11 | | 24 | 20 | | 25 | 7 | | 26 | 1 | | 27 | 13 | | 28 | 11 | | 29 | 2 | | 30 | 6 | | 31 | 5 | | 32 | 20 | | 33 | 11 | | 34 | 4 | | 35 | 17 | | 36 | 2 | | 37 | 22 | | 38 | 3 | | 39 | 2 | | 40 | 5 | | 41 | 14 | | 42 | 17 | | 43 | 2 | | 44 | 10 | | 45 | 13 | | 46 | 3 | | 47 | 18 | | 48 | 2 | | 49 | 5 |
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| 56.96% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.3883495145631068 | | totalSentences | 103 | | uniqueOpeners | 40 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 68 | | matches | | 0 | "Just a man lying dead" | | 1 | "Too cold for a body" | | 2 | "Instead, I pulled out my" | | 3 | "Instead, I pulled out my" |
| | ratio | 0.059 | |
| 55.29% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 68 | | matches | | 0 | "I crouched beside the body," | | 1 | "His face was frozen in" | | 2 | "I ignored him, my gaze" | | 3 | "His shoes, polished Oxfords, didn’t" | | 4 | "I already didn’t." | | 5 | "I reached into my coat" | | 6 | "I leaned in closer, my" | | 7 | "I brushed my fingers against" | | 8 | "I asked, tapping the victim’s" | | 9 | "I stood, my joints protesting." | | 10 | "I turned my attention to" | | 11 | "They pulsed faintly under the" | | 12 | "My stomach twisted." | | 13 | "I pointed to the largest" | | 14 | "I traced the air above" | | 15 | "I didn’t answer." | | 16 | "I pocketed my phone" | | 17 | "I turned to him, my" | | 18 | "He knew as well as" | | 19 | "I knelt again, this time" |
| | ratio | 0.412 | |
| 62.94% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 68 | | matches | | 0 | "The air smelled of damp" | | 1 | "I crouched beside the body," | | 2 | "The victim lay sprawled on" | | 3 | "His face was frozen in" | | 4 | "Davies didn’t look up from" | | 5 | "I ignored him, my gaze" | | 6 | "The platform was lit by" | | 7 | "The victim’s clothes were too" | | 8 | "His shoes, polished Oxfords, didn’t" | | 9 | "Davies finally glanced at me," | | 10 | "I already didn’t." | | 11 | "The body was too neat," | | 12 | "The kind used to enter" | | 13 | "I reached into my coat" | | 14 | "Davies gestured to the victim’s" | | 15 | "I leaned in closer, my" | | 16 | "The victim’s skin was pale," | | 17 | "I brushed my fingers against" | | 18 | "I asked, tapping the victim’s" | | 19 | "I stood, my joints protesting." |
| | ratio | 0.794 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 2 | | matches | | 0 | "The air smelled of damp stone and something older, something that clung to the back of my throat like copper." | | 1 | "The platform was lit by a handful of flickering bulbs strung haphazardly along the walls, casting long shadows that danced like drunks at last call." |
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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 | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.069 | | leniency | 0.138 | | rawRatio | 0 | | effectiveRatio | 0 | |