| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva said quietly [quietly]" |
| | dialogueSentences | 46 | | tagDensity | 0.239 | | leniency | 0.478 | | rawRatio | 0.091 | | effectiveRatio | 0.043 | |
| 90.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1615 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "carefully" | | 1 | "really" | | 2 | "slightly" |
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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) | |
| 81.42% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1615 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "perfect" | | 1 | "etched" | | 2 | "could feel" | | 3 | "resonance" | | 4 | "beacon" | | 5 | "fractured" |
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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 | 84 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 84 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 119 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1621 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1106 | | uniqueNames | 12 | | maxNameDensity | 1.54 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Eva" | | discoveredNames | | Tube | 1 | | Harlow | 17 | | Quinn | 1 | | Buck | 1 | | Street | 1 | | Blitz | 1 | | Eva | 15 | | Kowalski | 2 | | Scene | 1 | | Crime | 1 | | Camden | 1 | | Morris | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Eva" | | 3 | "Kowalski" | | 4 | "Scene" | | 5 | "Morris" |
| | places | | | globalScore | 0.731 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like salt or ash ground fine as fl" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.617 | | wordCount | 1621 | | matches | | 0 | "not dilated or contracted, but fractured, as if something had burst outward from inside the" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 119 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 54 | | mean | 30.02 | | std | 26.34 | | cv | 0.878 | | sampleLengths | | 0 | 84 | | 1 | 25 | | 2 | 9 | | 3 | 50 | | 4 | 19 | | 5 | 7 | | 6 | 4 | | 7 | 68 | | 8 | 28 | | 9 | 38 | | 10 | 2 | | 11 | 12 | | 12 | 7 | | 13 | 57 | | 14 | 71 | | 15 | 10 | | 16 | 59 | | 17 | 44 | | 18 | 6 | | 19 | 5 | | 20 | 74 | | 21 | 21 | | 22 | 39 | | 23 | 6 | | 24 | 12 | | 25 | 10 | | 26 | 1 | | 27 | 18 | | 28 | 24 | | 29 | 36 | | 30 | 42 | | 31 | 5 | | 32 | 52 | | 33 | 4 | | 34 | 37 | | 35 | 70 | | 36 | 7 | | 37 | 5 | | 38 | 3 | | 39 | 83 | | 40 | 30 | | 41 | 9 | | 42 | 3 | | 43 | 16 | | 44 | 29 | | 45 | 2 | | 46 | 31 | | 47 | 97 | | 48 | 10 | | 49 | 23 |
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| 88.55% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 84 | | matches | | 0 | "been laid" | | 1 | "being manipulated" | | 2 | "was supposed" | | 3 | "was unlocked" | | 4 | "been sealed" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 7 | | totalVerbs | 185 | | matches | | 0 | "was escaping" | | 1 | "was worrying" | | 2 | "wasn’t pointing" | | 3 | "was pointing" | | 4 | "was lying" | | 5 | "was still trembling" | | 6 | "was pointing" |
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| 22.81% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 119 | | ratio | 0.042 | | matches | | 0 | "She turned toward Eva, who looked up at the same moment and tucked a strand of hair behind her left ear — a quick, nervous gesture that Harlow filed away." | | 1 | "The skin had a grayish cast that suggested he’d been dead for at least twelve hours, but the position was wrong — bodies dumped in a hurry didn’t arrange themselves like effigies on a tomb." | | 2 | "The salt circle — if that’s what it was — had been laid with geometric precision, the kind of precision that required time and steady hands." | | 3 | "This was a ritual killing staged to look like nothing at all — at least, nothing that fit a police report." | | 4 | "In the portable light, his pupils looked wrong — not dilated or contracted, but fractured, as if something had burst outward from inside them." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1106 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.03345388788426763 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.009041591320072333 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 119 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 119 | | mean | 13.62 | | std | 10.55 | | cv | 0.775 | | sampleLengths | | 0 | 26 | | 1 | 31 | | 2 | 27 | | 3 | 10 | | 4 | 15 | | 5 | 9 | | 6 | 28 | | 7 | 22 | | 8 | 9 | | 9 | 10 | | 10 | 2 | | 11 | 5 | | 12 | 4 | | 13 | 17 | | 14 | 21 | | 15 | 30 | | 16 | 28 | | 17 | 7 | | 18 | 31 | | 19 | 2 | | 20 | 12 | | 21 | 3 | | 22 | 4 | | 23 | 16 | | 24 | 16 | | 25 | 12 | | 26 | 13 | | 27 | 14 | | 28 | 17 | | 29 | 3 | | 30 | 2 | | 31 | 35 | | 32 | 10 | | 33 | 50 | | 34 | 9 | | 35 | 2 | | 36 | 25 | | 37 | 17 | | 38 | 6 | | 39 | 5 | | 40 | 16 | | 41 | 7 | | 42 | 16 | | 43 | 26 | | 44 | 5 | | 45 | 4 | | 46 | 14 | | 47 | 7 | | 48 | 4 | | 49 | 35 |
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| 53.50% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.36134453781512604 | | totalSentences | 119 | | uniqueOpeners | 43 | |
| 87.72% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 76 | | matches | | 0 | "Then Eva reached into her" | | 1 | "Then she stood, brushed the" |
| | ratio | 0.026 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 76 | | matches | | 0 | "He nodded toward the far" | | 1 | "Her curly red hair was" | | 2 | "She turned toward Eva, who" | | 3 | "She walked toward the body," | | 4 | "she asked the lead SOCO" | | 5 | "She held up an evidence" | | 6 | "It surrounded the corpse in" | | 7 | "She returned to where Eva" | | 8 | "She held it out on" | | 9 | "It was a compass, old" | | 10 | "It was pointing directly at" | | 11 | "She’d seen a lot of" | | 12 | "she repeated, her voice flat" | | 13 | "Her partner, DS Morris, had" | | 14 | "She’d buried that along with" | | 15 | "She turned back." | | 16 | "She looked at the dead" | | 17 | "She paused, studying Eva’s face" | | 18 | "She’d seen that before." | | 19 | "She reached out, careful not" |
| | ratio | 0.263 | |
| 38.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 76 | | matches | | 0 | "The air in the abandoned" | | 1 | "Detective Harlow Quinn ducked under" | | 2 | "The patrol constable who’d called" | | 3 | "He nodded toward the far" | | 4 | "Harlow asked, not slowing her" | | 5 | "Eva Kowalski sat on an" | | 6 | "Her curly red hair was" | | 7 | "the constable said" | | 8 | "The platform stretched away into" | | 9 | "Harlow could make out the" | | 10 | "She turned toward Eva, who" | | 11 | "Eva’s green eyes held hers" | | 12 | "Harlow didn’t blink." | | 13 | "She walked toward the body," | | 14 | "An academic researcher descends into" | | 15 | "The timing was too neat," | | 16 | "The body lay on its" | | 17 | "The skin had a grayish" | | 18 | "she asked the lead SOCO" | | 19 | "She held up an evidence" |
| | ratio | 0.842 | |
| 65.79% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 76 | | matches | | 0 | "Now here was this woman" |
| | ratio | 0.013 | |
| 3.48% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 8 | | matches | | 0 | "The air in the abandoned Tube station tasted of wet limestone and something older, something that clung to the back of the throat like candle smoke." | | 1 | "Detective Harlow Quinn ducked under the police tape stretched across the service door on Buck Street, her leather soles scraping against concrete that hadn’t se…" | | 2 | "The patrol constable who’d called it in stood by the emergency lighting rig they’d hauled down three flights of stairs, his face the color of old milk." | | 3 | "She turned toward Eva, who looked up at the same moment and tucked a strand of hair behind her left ear — a quick, nervous gesture that Harlow filed away." | | 4 | "Male, mid-forties, wearing a suit that had been expensive before it acquired the patina of tunnel grime." | | 5 | "It was pointing directly at the body, trembling slightly as if drawn by a current only it could feel." | | 6 | "Now here was this woman with her museum credentials and her nervous tic and her compass pointing at a dead man wearing a five-thousand-pound suit in a sealed un…" | | 7 | "In the portable light, his pupils looked wrong — not dilated or contracted, but fractured, as if something had burst outward from inside them." |
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| 34.09% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 2 | | matches | | 0 | "Harlow asked, not slowing her stride" | | 1 | "she repeated, her voice flat" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 46 | | tagDensity | 0.152 | | leniency | 0.304 | | rawRatio | 0.143 | | effectiveRatio | 0.043 | |