| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.65% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1150 | | 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) | |
| 47.83% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1150 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "chill" | | 1 | "scanning" | | 2 | "standard" | | 3 | "flickered" | | 4 | "weight" | | 5 | "pulse" | | 6 | "depths" | | 7 | "familiar" | | 8 | "whisper" | | 9 | "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 | 62 | | matches | (empty) | |
| 27.65% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 3 | | narrationSentences | 62 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 62 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1141 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 1133 | | uniqueNames | 17 | | maxNameDensity | 0.71 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Herrera" | | discoveredNames | | London | 6 | | Harlow | 2 | | Quinn | 8 | | Victorian | 2 | | October | 1 | | Herrera | 7 | | North | 1 | | Camden | 3 | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Saint | 1 | | Christopher | 1 | | Georgian | 1 | | Underground | 1 | | Morris | 4 | | Tube | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Camden" | | 4 | "Nest" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Morris" |
| | places | | 0 | "London" | | 1 | "Victorian" | | 2 | "North" | | 3 | "Raven" | | 4 | "Soho" |
| | globalScore | 1 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 4 | | matches | | 0 | "quite articulate" | | 1 | "seemed focused on something beyond the physical world, searching the rain-soaked night for threats she couldn't perceive" | | 2 | "seemed older here, their Georgian facades weathered by more than just London's industrial grime" | | 3 | "darkness that seemed to absorb her torch beam" |
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| 24.72% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.753 | | wordCount | 1141 | | matches | | 0 | "not through the front entrance she'd been monitoring, but simply absent, as if the darkness itself had swallowed him" | | 1 | "not pain, but wonder, as if he'd witnessed something beautiful" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 62 | | matches | | |
| 49.50% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 16 | | mean | 71.31 | | std | 23.05 | | cv | 0.323 | | sampleLengths | | 0 | 62 | | 1 | 80 | | 2 | 69 | | 3 | 90 | | 4 | 58 | | 5 | 76 | | 6 | 63 | | 7 | 74 | | 8 | 86 | | 9 | 138 | | 10 | 65 | | 11 | 60 | | 12 | 66 | | 13 | 74 | | 14 | 61 | | 15 | 19 |
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| 93.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 62 | | matches | | 0 | "was gone" | | 1 | "were lined" | | 2 | "been carved" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 182 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 62 | | ratio | 0.129 | | matches | | 0 | "The thefts themselves weren't unusual—desperate addicts often targeted hospitals for painkillers." | | 1 | "The next, he was gone—not through the front entrance she'd been monitoring, but simply absent, as if the darkness itself had swallowed him." | | 2 | "She remembered the file photo from his NHS personnel record—younger then, before whatever had cost him his medical license." | | 3 | "The rain took on a different quality too—still cold, still relentless, but somehow thicker, as if the water itself carried weight beyond moisture." | | 4 | "The official cause of death was heart failure, but she'd seen the look on his face—not pain, but wonder, as if he'd witnessed something beautiful and terrible in his final moments." | | 5 | "But instead of running, he nodded—a gesture that might have been acknowledgment or invitation—before disappearing into the depths." | | 6 | "The air grew warmer as she descended, carrying scents that belonged in no London street—sandalwood, ozone, and something metallic that reminded her of old blood." | | 7 | "The walls were lined with Victorian brick, but symbols had been carved into the mortar between courses—geometric patterns that shifted and writhed in her peripheral vision." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1153 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.026886383347788378 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.006938421509106678 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 62 | | echoCount | 0 | | echoWords | (empty) | |
| 95.49% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 62 | | mean | 18.4 | | std | 7.15 | | cv | 0.389 | | sampleLengths | | 0 | 18 | | 1 | 23 | | 2 | 21 | | 3 | 16 | | 4 | 2 | | 5 | 26 | | 6 | 11 | | 7 | 25 | | 8 | 10 | | 9 | 3 | | 10 | 23 | | 11 | 33 | | 12 | 10 | | 13 | 16 | | 14 | 16 | | 15 | 25 | | 16 | 23 | | 17 | 7 | | 18 | 14 | | 19 | 16 | | 20 | 21 | | 21 | 17 | | 22 | 23 | | 23 | 14 | | 24 | 22 | | 25 | 19 | | 26 | 44 | | 27 | 16 | | 28 | 16 | | 29 | 19 | | 30 | 23 | | 31 | 27 | | 32 | 19 | | 33 | 22 | | 34 | 18 | | 35 | 8 | | 36 | 19 | | 37 | 23 | | 38 | 22 | | 39 | 16 | | 40 | 19 | | 41 | 31 | | 42 | 20 | | 43 | 13 | | 44 | 14 | | 45 | 18 | | 46 | 11 | | 47 | 15 | | 48 | 20 | | 49 | 14 |
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| 74.73% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.46774193548387094 | | totalSentences | 62 | | uniqueOpeners | 29 | |
| 55.56% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 60 | | matches | | 0 | "Instead, the darkness below seemed" |
| | ratio | 0.017 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 60 | | matches | | 0 | "She'd been tracking the former" | | 1 | "She'd lost her backup twenty" | | 2 | "She'd been watching through the" | | 3 | "She'd circled the building, found" | | 4 | "He glanced over his shoulder," | | 5 | "She remembered the file photo" | | 6 | "Her quarry descended a set" | | 7 | "They'd been pursuing a suspect" | | 8 | "She'd been two blocks away," | | 9 | "They'd found his body the" | | 10 | "He looked back once more," | | 11 | "She pulled out her radio," |
| | ratio | 0.2 | |
| 93.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 60 | | matches | | 0 | "The rain hammered London's streets" | | 1 | "Detective Harlow Quinn pressed her" | | 2 | "Water dripped from her closely" | | 3 | "She'd been tracking the former" | | 4 | "The thefts themselves weren't unusual—desperate" | | 5 | "Quinn adjusted her worn leather" | | 6 | "The streets of Camden were" | | 7 | "She'd lost her backup twenty" | | 8 | "The memory of that impossible" | | 9 | "She'd been watching through the" | | 10 | "Maps and black-and-white photographs covered" | | 11 | "The next, he was gone—not" | | 12 | "Military precision had carried her" | | 13 | "She'd circled the building, found" | | 14 | "Herrera paused at the mouth" | | 15 | "The scar along his left" | | 16 | "He glanced over his shoulder," | | 17 | "She remembered the file photo" | | 18 | "The official report cited When" | | 19 | "Herrera moved again, turning down" |
| | ratio | 0.733 | |
| 83.33% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 60 | | matches | | 0 | "Now, as she shadowed him" |
| | ratio | 0.017 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 13 | | matches | | 0 | "She'd been tracking the former paramedic for three weeks, following a trail of medical supplies that had gone missing from various NHS facilities across North L…" | | 1 | "She'd lost her backup twenty minutes ago when Herrera had suddenly bolted from The Raven's Nest, abandoning his pint mid-conversation and slipping out through w…" | | 2 | "Maps and black-and-white photographs covered the walls, creating a labyrinth of shadows that made surveillance challenging." | | 3 | "The next, he was gone—not through the front entrance she'd been monitoring, but simply absent, as if the darkness itself had swallowed him." | | 4 | "The rain took on a different quality too—still cold, still relentless, but somehow thicker, as if the water itself carried weight beyond moisture." | | 5 | "They'd found his body the next morning in an abandoned Tube station that hadn't appeared on any transport map." | | 6 | "The official cause of death was heart failure, but she'd seen the look on his face—not pain, but wonder, as if he'd witnessed something beautiful and terrible i…" | | 7 | "But instead of running, he nodded—a gesture that might have been acknowledgment or invitation—before disappearing into the depths." | | 8 | "But the static that greeted her attempt at transmission was the same electronic whisper she'd heard that night Morris died." | | 9 | "But Morris was dead, Herrera was involved with something that defied explanation, and somewhere in the darkness below might be the answers she'd been seeking fo…" | | 10 | "Each step was worn smooth by countless feet, polished to a mirror sheen that reflected her light in fractured patterns." | | 11 | "The air grew warmer as she descended, carrying scents that belonged in no London street—sandalwood, ozone, and something metallic that reminded her of old blood…" | | 12 | "The walls were lined with Victorian brick, but symbols had been carved into the mortar between courses—geometric patterns that shifted and writhed in her periph…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "The official report cited (cite)" |
| | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 1 | | effectiveRatio | 1 | |