| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said carefully [carefully]" | | 1 | "she said slowly [slowly]" |
| | dialogueSentences | 50 | | tagDensity | 0.32 | | leniency | 0.64 | | rawRatio | 0.125 | | effectiveRatio | 0.08 | |
| 85.96% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2137 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "slowly" | | 1 | "carefully" | | 2 | "slightly" | | 3 | "sharply" | | 4 | "very" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 67.24% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2137 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "fluttered" | | 1 | "weight" | | 2 | "scanning" | | 3 | "glinting" | | 4 | "could feel" | | 5 | "charged" | | 6 | "etched" | | 7 | "chill" | | 8 | "aftermath" | | 9 | "electric" | | 10 | "scanned" | | 11 | "mechanical" | | 12 | "flickered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
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| | highlights | | 0 | "eyes narrowed" | | 1 | "eyes widened" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 214 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 214 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 247 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 17 | | totalWords | 2149 | | ratio | 0.008 | | matches | | 0 | "Rifts and Veil Crossings: A Practical Guide" | | 1 | "Eva was right. The Market moves tonight. Need bone token." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 79 | | wordCount | 1791 | | uniqueNames | 18 | | maxNameDensity | 1.28 | | worstName | "Harlow" | | maxWindowNameDensity | 4 | | worstWindowName | "Eva" | | discoveredNames | | Tube | 1 | | Camden | 1 | | Market | 5 | | Harlow | 23 | | Quinn | 1 | | Patel | 19 | | Veil | 4 | | Crossings | 1 | | Practical | 1 | | Morris | 2 | | Victorian | 1 | | London | 1 | | Underground | 1 | | Eva | 12 | | Kowalski | 3 | | British | 1 | | Museum | 1 | | Ahead | 1 |
| | persons | | 0 | "Market" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Patel" | | 4 | "Morris" | | 5 | "Eva" | | 6 | "Kowalski" |
| | places | | 0 | "Veil" | | 1 | "London" | | 2 | "British" |
| | globalScore | 0.858 | | windowScore | 0.333 | |
| 41.30% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 138 | | glossingSentenceCount | 6 | | matches | | 0 | "shadows that seemed to move when she wasn't looking directly at them" | | 1 | "looked like salt mixed with something dar" | | 2 | "seemed deeper than they should be" | | 3 | "looked like frozen screams in glass jars" | | 4 | "as if sensing their presence" | | 5 | "felt like she was finally asking the ri" |
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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 | 2149 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 247 | | matches | | 0 | "glinted that brass" | | 1 | "check that warehouse" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 78 | | mean | 27.55 | | std | 20.45 | | cv | 0.742 | | sampleLengths | | 0 | 82 | | 1 | 47 | | 2 | 72 | | 3 | 30 | | 4 | 76 | | 5 | 9 | | 6 | 48 | | 7 | 41 | | 8 | 5 | | 9 | 6 | | 10 | 44 | | 11 | 13 | | 12 | 45 | | 13 | 16 | | 14 | 28 | | 15 | 14 | | 16 | 11 | | 17 | 1 | | 18 | 8 | | 19 | 71 | | 20 | 3 | | 21 | 15 | | 22 | 77 | | 23 | 41 | | 24 | 38 | | 25 | 21 | | 26 | 2 | | 27 | 14 | | 28 | 19 | | 29 | 62 | | 30 | 37 | | 31 | 9 | | 32 | 47 | | 33 | 27 | | 34 | 53 | | 35 | 19 | | 36 | 37 | | 37 | 11 | | 38 | 5 | | 39 | 44 | | 40 | 28 | | 41 | 4 | | 42 | 32 | | 43 | 19 | | 44 | 15 | | 45 | 76 | | 46 | 6 | | 47 | 23 | | 48 | 34 | | 49 | 13 |
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| 92.15% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 8 | | totalSentences | 214 | | matches | | 0 | "been sealed" | | 1 | "been crouched" | | 2 | "were cauterised" | | 3 | "been closed" | | 4 | "been told" | | 5 | "been torn" | | 6 | "were covered" | | 7 | "been blocked" |
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| 34.88% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 323 | | matches | | 0 | "wasn't looking" | | 1 | "were hunting" | | 2 | "was watching" | | 3 | "was already thinking" | | 4 | "was willing" | | 5 | "was arguing" | | 6 | "was screaming" | | 7 | "was finally asking" |
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| 38.75% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 247 | | ratio | 0.036 | | matches | | 0 | "— anonymous tip about a body in the old tunnels." | | 1 | "Its face bore strange etchings — sigils that made her teeth ache when she looked too long." | | 2 | "The marks looked burned into the concrete — swirling patterns that hurt to focus on." | | 3 | "Inside were books — old ones with cracked leather bindings." | | 4 | "She'd heard whispers during her years on the force — an underground black market for the sort of people who believed in magic." | | 5 | "There — faint scratches in the concrete." | | 6 | "Footprints — small ones — led through the gap." | | 7 | "Creatures — no, people — of various descriptions haggled over items that shouldn't exist." | | 8 | "There — by a stall selling what looked like frozen screams in glass jars." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1784 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 57 | | adverbRatio | 0.03195067264573991 | | lyAdverbCount | 23 | | lyAdverbRatio | 0.01289237668161435 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 247 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 247 | | mean | 8.7 | | std | 5.47 | | cv | 0.629 | | sampleLengths | | 0 | 20 | | 1 | 20 | | 2 | 21 | | 3 | 21 | | 4 | 6 | | 5 | 8 | | 6 | 10 | | 7 | 7 | | 8 | 12 | | 9 | 4 | | 10 | 6 | | 11 | 12 | | 12 | 12 | | 13 | 19 | | 14 | 9 | | 15 | 2 | | 16 | 2 | | 17 | 10 | | 18 | 14 | | 19 | 8 | | 20 | 8 | | 21 | 11 | | 22 | 14 | | 23 | 12 | | 24 | 3 | | 25 | 12 | | 26 | 7 | | 27 | 17 | | 28 | 9 | | 29 | 36 | | 30 | 12 | | 31 | 9 | | 32 | 6 | | 33 | 10 | | 34 | 16 | | 35 | 5 | | 36 | 4 | | 37 | 2 | | 38 | 6 | | 39 | 16 | | 40 | 22 | | 41 | 13 | | 42 | 10 | | 43 | 4 | | 44 | 15 | | 45 | 7 | | 46 | 6 | | 47 | 3 | | 48 | 6 | | 49 | 10 |
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| 54.79% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.3603238866396761 | | totalSentences | 247 | | uniqueOpeners | 89 | |
| 35.09% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 190 | | matches | | 0 | "Just a small brass object" | | 1 | "Instead she pulled the evidence" |
| | ratio | 0.011 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 56 | | totalSentences | 190 | | matches | | 0 | "Her boots splashed through shallow" | | 1 | "His face, what remained of" | | 2 | "His face looked pale under" | | 3 | "She leaned closer." | | 4 | "Its face bore strange etchings" | | 5 | "she asked Patel, not looking" | | 6 | "She slipped it into an" | | 7 | "She stood, scanning the platform" | | 8 | "They weren't spray paint." | | 9 | "She reached out, then pulled" | | 10 | "Her fingers tingled." | | 11 | "She shot him a look." | | 12 | "He had the grace to" | | 13 | "She'd lost consciousness before the" | | 14 | "She'd been told to let" | | 15 | "Her torch beam caught something" | | 16 | "She approached slowly." | | 17 | "She knelt, noting the clasp" | | 18 | "Its title, stamped in faded" | | 19 | "She flipped it open." |
| | ratio | 0.295 | |
| 41.58% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 159 | | totalSentences | 190 | | matches | | 0 | "The abandoned Tube station beneath" | | 1 | "Detective Harlow Quinn descended the" | | 2 | "This wasn't a normal crime" | | 3 | "The call had come in" | | 4 | "The station had been sealed" | | 5 | "Her boots splashed through shallow" | | 6 | "The air grew thicker the" | | 7 | "A man lay sprawled near" | | 8 | "His face, what remained of" | | 9 | "DS Patel straightened from where" | | 10 | "His face looked pale under" | | 11 | "Harlow crouched beside the body," | | 12 | "The wounds didn't match any" | | 13 | "The edges were cauterised in" | | 14 | "She leaned closer." | | 15 | "The man's eyes were open," | | 16 | "Its face bore strange etchings" | | 17 | "she asked Patel, not looking" | | 18 | "Patel shrugged, but his voice" | | 19 | "Harlow turned the compass over" |
| | ratio | 0.837 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 190 | | matches | (empty) | | ratio | 0 | |
| 95.86% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 76 | | technicalSentenceCount | 5 | | matches | | 0 | "At five-foot-nine, she had to duck beneath a sagging beam, her sharp jaw set in a line that brooked no nonsense." | | 1 | "Its face bore strange etchings — sigils that made her teeth ache when she looked too long." | | 2 | "Knowledge in her green eyes that went beyond what she was willing to share." | | 3 | "Stalls lined both sides of a vast underground chamber, lit by floating orbs that weren't electric." | | 4 | "Creatures — no, people — of various descriptions haggled over items that shouldn't exist." |
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| 31.25% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 3 | | matches | | 0 | "she asked, not looking up" | | 1 | "Patel shrugged, but his voice carried uncertainty" | | 2 | "she replied, not breaking stride" |
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| 70.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 4 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "she warned (warn)" | | 2 | "she whispered (whisper)" | | 3 | "he gasped (gasp)" |
| | dialogueSentences | 50 | | tagDensity | 0.22 | | leniency | 0.44 | | rawRatio | 0.364 | | effectiveRatio | 0.16 | |