| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "Her voice echoed too [too]" |
| | dialogueSentences | 30 | | tagDensity | 0.567 | | leniency | 1 | | rawRatio | 0.059 | | effectiveRatio | 0.059 | |
| 96.98% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1654 | | 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) | |
| 66.75% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1654 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "treacherous" | | 1 | "standard" | | 2 | "vibrated" | | 3 | "mechanical" | | 4 | "silence" | | 5 | "echoing" | | 6 | "echoed" | | 7 | "scanning" | | 8 | "constructed" | | 9 | "velvet" | | 10 | "scanned" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 98.12% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 4 | | narrationSentences | 124 | | matches | | 0 | "looked angry" | | 1 | "filled with panic" | | 2 | "d with panic" | | 3 | "felt a prickle" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 124 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 137 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1648 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 1458 | | uniqueNames | 15 | | maxNameDensity | 1.58 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Herrera" | | discoveredNames | | West | 1 | | End | 1 | | Harlow | 23 | | Quinn | 1 | | Camden | 2 | | High | 2 | | Street | 1 | | Herrera | 17 | | Morris | 5 | | Saint | 1 | | Christopher | 1 | | London | 4 | | Underground | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Morris" | | 4 | "Saint" | | 5 | "Christopher" |
| | places | | 0 | "West" | | 1 | "End" | | 2 | "Camden" | | 3 | "High" | | 4 | "Street" | | 5 | "London" |
| | globalScore | 0.711 | | windowScore | 0.5 | |
| 17.02% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 94 | | glossingSentenceCount | 5 | | matches | | 0 | "seemed disproportionate to a simple police chase" | | 1 | "thrum that seemed to vibrate in Harlow’s molars" | | 2 | "as if waking from a century-long sleep" | | 3 | "looked like a grotesque parody of riot ar" | | 4 | "felt like she was drowning" |
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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 | 1648 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 137 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 31.69 | | std | 18.79 | | cv | 0.593 | | sampleLengths | | 0 | 36 | | 1 | 27 | | 2 | 77 | | 3 | 29 | | 4 | 62 | | 5 | 12 | | 6 | 32 | | 7 | 36 | | 8 | 16 | | 9 | 51 | | 10 | 13 | | 11 | 39 | | 12 | 17 | | 13 | 29 | | 14 | 32 | | 15 | 43 | | 16 | 3 | | 17 | 1 | | 18 | 78 | | 19 | 32 | | 20 | 13 | | 21 | 57 | | 22 | 19 | | 23 | 51 | | 24 | 11 | | 25 | 9 | | 26 | 10 | | 27 | 47 | | 28 | 5 | | 29 | 53 | | 30 | 38 | | 31 | 34 | | 32 | 46 | | 33 | 31 | | 34 | 23 | | 35 | 9 | | 36 | 24 | | 37 | 14 | | 38 | 52 | | 39 | 30 | | 40 | 63 | | 41 | 25 | | 42 | 17 | | 43 | 35 | | 44 | 59 | | 45 | 7 | | 46 | 47 | | 47 | 36 | | 48 | 48 | | 49 | 13 |
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| 91.11% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 124 | | matches | | 0 | "was plastered" | | 1 | "was gone" | | 2 | "were lined" | | 3 | "being struck" | | 4 | "was buried" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 9 | | totalVerbs | 262 | | matches | | 0 | "wasn't running" | | 1 | "was running" | | 2 | "was fumbling" | | 3 | "was talking" | | 4 | "was standing" | | 5 | "was arguing" | | 6 | "was gripping" | | 7 | "was saying" | | 8 | "was drowning" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 4 | | flaggedSentences | 9 | | totalSentences | 137 | | ratio | 0.066 | | matches | | 0 | "London rain didn’t just fall; it dismantled." | | 1 | "Harlow pushed harder, her hand reflexively checking the worn leather watch on her left wrist—a nervous tic she’d developed after Morris died." | | 2 | "It wasn’t a standard service entrance; the metal was wrought in twisting, thorny patterns that hurt the eyes if stared at too long." | | 3 | "The rusted gate didn't swing on hinges; it retracted, the metal groaning as if waking from a century-long sleep." | | 4 | "The other part—the part that had held Morris’s cold hand while he bled out from a wound that defied physics—took over." | | 5 | "They advertised products she didn’t recognize—tonics for \"Aetheric Sickness\" and balms for \"Shadow-Bight.\"" | | 6 | "A figure in a plague doctor’s mask hissed as she brushed past; she ignored it." | | 7 | "Harlow felt a prickle of electricity run up her spine—the sensation of being watched." | | 8 | "She looked at the exit—a long, dark tunnel leading back to the surface, back to the rain, back to a world that made sense." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1467 | | adjectiveStacks | 1 | | stackExamples | | 0 | "short, curly dark hair" |
| | adverbCount | 33 | | adverbRatio | 0.022494887525562373 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.007498295841854124 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 137 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 137 | | mean | 12.03 | | std | 7.33 | | cv | 0.609 | | sampleLengths | | 0 | 7 | | 1 | 29 | | 2 | 7 | | 3 | 15 | | 4 | 5 | | 5 | 18 | | 6 | 31 | | 7 | 2 | | 8 | 1 | | 9 | 2 | | 10 | 23 | | 11 | 5 | | 12 | 21 | | 13 | 3 | | 14 | 3 | | 15 | 17 | | 16 | 19 | | 17 | 23 | | 18 | 6 | | 19 | 6 | | 20 | 22 | | 21 | 5 | | 22 | 5 | | 23 | 17 | | 24 | 19 | | 25 | 14 | | 26 | 2 | | 27 | 16 | | 28 | 23 | | 29 | 12 | | 30 | 6 | | 31 | 7 | | 32 | 3 | | 33 | 21 | | 34 | 9 | | 35 | 4 | | 36 | 2 | | 37 | 17 | | 38 | 7 | | 39 | 11 | | 40 | 11 | | 41 | 5 | | 42 | 18 | | 43 | 9 | | 44 | 3 | | 45 | 21 | | 46 | 19 | | 47 | 3 | | 48 | 1 | | 49 | 13 |
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| 44.77% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.32116788321167883 | | totalSentences | 137 | | uniqueOpeners | 44 | |
| 29.50% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 113 | | matches | | 0 | "Then she looked at Herrera," |
| | ratio | 0.009 | |
| 60.71% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 113 | | matches | | 0 | "It stripped the city of" | | 1 | "It cleared the streets of" | | 2 | "Her boots slammed against the" | | 3 | "They never did." | | 4 | "He moved with a wiry," | | 5 | "His short, curly dark hair" | | 6 | "He glanced back, his olive" | | 7 | "He wasn't running from the" | | 8 | "He was running toward something" | | 9 | "It was a service access" | | 10 | "It wasn’t a standard service" | | 11 | "He was fumbling with something" | | 12 | "He didn't turn." | | 13 | "He yanked at the chain" | | 14 | "It looked like ivory." | | 15 | "he whispered, though whether he" | | 16 | "He slotted the bone token" | | 17 | "It wasn't a mechanical rumble," | | 18 | "She had a split second" | | 19 | "She threw her shoulder against" |
| | ratio | 0.398 | |
| 17.52% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 100 | | totalSentences | 113 | | matches | | 0 | "London rain didn’t just fall;" | | 1 | "It stripped the city of" | | 2 | "Detective Harlow Quinn didn’t mind" | | 3 | "It cleared the streets of" | | 4 | "Tonight she was the latter." | | 5 | "Her boots slammed against the" | | 6 | "A link to the clique" | | 7 | "The command was muscle memory," | | 8 | "They never did." | | 9 | "Herrera was fast." | | 10 | "He moved with a wiry," | | 11 | "His short, curly dark hair" | | 12 | "He glanced back, his olive" | | 13 | "He wasn't running from the" | | 14 | "He was running toward something" | | 15 | "Harlow pushed harder, her hand" | | 16 | "The time was 11:47 PM." | | 17 | "Herrera banked hard to the" | | 18 | "It was a service access" | | 19 | "Harlow skidded around the corner," |
| | ratio | 0.885 | |
| 44.25% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 113 | | matches | | | ratio | 0.009 | |
| 2.16% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 66 | | technicalSentenceCount | 13 | | matches | | 0 | "It stripped the city of its pretense, slicking the cobblestones into treacherous mirrors and turning the neon glow of the West End into bleeding watercolor stre…" | | 1 | "The command was muscle memory, sharp with the military precision that defined her life, but she didn’t expect him to obey." | | 2 | "He glanced back, his olive skin pale under the streetlights, eyes wide with a terror that seemed disproportionate to a simple police chase." | | 3 | "It wasn’t a standard service entrance; the metal was wrought in twisting, thorny patterns that hurt the eyes if stared at too long." | | 4 | "He was fumbling with something at his neck, his fingers shaking violently." | | 5 | "It wasn't a mechanical rumble, like a passing train, but a deep, resonant thrum that seemed to vibrate in Harlow’s molars." | | 6 | "The rusted gate didn't swing on hinges; it retracted, the metal groaning as if waking from a century-long sleep." | | 7 | "The rational part of her mind, the part that filed paperwork and followed evidentiary procedure, screamed at her to call for backup." | | 8 | "The concourse, which should have been empty and rat-infested, was alive." | | 9 | "Braziers burned with flames that licked blue and violet, casting long, distorted shadows against the curved ceiling." | | 10 | "He was arguing with a vendor who looked less like a shopkeep and more like a cadaver, possessing skin the color of parchment." | | 11 | "He looked at the retreating crowd, who had begun to form a wide, silent circle around them." | | 12 | "They were taller than the average man, clad in security gear that looked like a grotesque parody of riot armor, their faces hidden behind dark visors." |
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| 7.35% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 4 | | matches | | 0 | "Herrera was saying, his voice cracking" | | 1 | "Harlow said, her voice low and dangerous close to his ear" | | 2 | "Herrera said, his voice dropping to a terrified hush" | | 3 | "Harlow ordered, her voice steady despite the adrenaline flooding her system" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 9 | | fancyTags | | 0 | "Harlow shouted (shout)" | | 1 | "Harlow barked (bark)" | | 2 | "he whispered (whisper)" | | 3 | "Harlow warned (warn)" | | 4 | "he gasped (gasp)" | | 5 | "Herrera was saying (be say)" | | 6 | "Herrera whispered (whisper)" | | 7 | "Herrera breathed (breathe)" | | 8 | "Harlow ordered (order)" |
| | dialogueSentences | 30 | | tagDensity | 0.467 | | leniency | 0.933 | | rawRatio | 0.643 | | effectiveRatio | 0.6 | |