| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 3 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.19% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1040 | | 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) | |
| 37.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1040 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "flickered" | | 1 | "flicker" | | 2 | "wavering" | | 3 | "echoed" | | 4 | "pulsed" | | 5 | "pulse" | | 6 | "potential" | | 7 | "silk" | | 8 | "intricate" | | 9 | "glint" | | 10 | "raced" | | 11 | "could feel" | | 12 | "weight" |
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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 | 89 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 89 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 91 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 7 | | markdownWords | 18 | | totalWords | 1031 | | ratio | 0.017 | | matches | | 0 | "The Raven’s Nest" | | 1 | "Tomás Herrera" | | 2 | "Camden Tube Station – Closed for Maintenance" | | 3 | "seeing" | | 4 | "dared" | | 5 | "bone token" | | 6 | "Another cop?" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 1008 | | uniqueNames | 16 | | maxNameDensity | 1.19 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Herrera" | | discoveredNames | | Raven | 1 | | Detective | 1 | | Harlow | 1 | | Quinn | 12 | | Static | 1 | | Soho | 1 | | Saint | 1 | | Christopher | 1 | | Tube | 1 | | Station | 1 | | Closed | 1 | | God | 1 | | Veil | 1 | | Market | 1 | | Met | 1 | | Herrera | 12 |
| | persons | | 0 | "Raven" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Static" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Station" | | 7 | "Herrera" |
| | places | | | globalScore | 0.905 | | windowScore | 0.667 | |
| 16.07% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like scavenged tarpaulin and old a" | | 1 | "looked like animal bones carved into intr" | | 2 | "looked like human teeth" |
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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 | 1031 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 91 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 25.78 | | std | 25.05 | | cv | 0.972 | | sampleLengths | | 0 | 81 | | 1 | 15 | | 2 | 26 | | 3 | 5 | | 4 | 69 | | 5 | 30 | | 6 | 5 | | 7 | 74 | | 8 | 69 | | 9 | 20 | | 10 | 14 | | 11 | 71 | | 12 | 5 | | 13 | 74 | | 14 | 25 | | 15 | 3 | | 16 | 50 | | 17 | 54 | | 18 | 47 | | 19 | 3 | | 20 | 46 | | 21 | 5 | | 22 | 9 | | 23 | 55 | | 24 | 3 | | 25 | 10 | | 26 | 4 | | 27 | 31 | | 28 | 3 | | 29 | 30 | | 30 | 2 | | 31 | 2 | | 32 | 20 | | 33 | 8 | | 34 | 6 | | 35 | 30 | | 36 | 9 | | 37 | 9 | | 38 | 6 | | 39 | 3 |
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| 93.44% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 89 | | matches | | 0 | "been pried" | | 1 | "been gutted" | | 2 | "was made" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 159 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 91 | | ratio | 0.077 | | matches | | 0 | "The suspect—*Tomás Herrera*—had already vanished into the maze of Soho’s back alleys, but Quinn knew these streets." | | 1 | "The sign above read *Camden Tube Station – Closed for Maintenance*, but the chain-link fence across the entrance had been pried open, the metal bent like tinfoil." | | 2 | "The air rising from the tunnel below was thick with the scent of damp earth and something sharper—copper, maybe, or the acrid tang of old magic." | | 3 | "A sound echoed up the stairwell—a scuffle, a grunt, the unmistakable clatter of something metallic hitting stone." | | 4 | "It cast just enough light to see the graffiti scrawled across the tiles—symbols that didn’t belong to any language she recognised, looping and jagged, like something clawed into the surface." | | 5 | "And the smell—God, the smell." | | 6 | "Then he turned his head—just slightly—and Quinn caught the glint of something metallic beneath the hood." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1017 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.02753195673549656 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.003933136676499509 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 91 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 91 | | mean | 11.33 | | std | 7.81 | | cv | 0.689 | | sampleLengths | | 0 | 27 | | 1 | 29 | | 2 | 3 | | 3 | 22 | | 4 | 10 | | 5 | 5 | | 6 | 4 | | 7 | 2 | | 8 | 2 | | 9 | 18 | | 10 | 5 | | 11 | 17 | | 12 | 19 | | 13 | 17 | | 14 | 16 | | 15 | 14 | | 16 | 1 | | 17 | 15 | | 18 | 5 | | 19 | 18 | | 20 | 29 | | 21 | 27 | | 22 | 11 | | 23 | 26 | | 24 | 9 | | 25 | 4 | | 26 | 19 | | 27 | 17 | | 28 | 3 | | 29 | 14 | | 30 | 13 | | 31 | 14 | | 32 | 14 | | 33 | 30 | | 34 | 5 | | 35 | 17 | | 36 | 18 | | 37 | 20 | | 38 | 19 | | 39 | 5 | | 40 | 20 | | 41 | 3 | | 42 | 6 | | 43 | 8 | | 44 | 6 | | 45 | 8 | | 46 | 11 | | 47 | 11 | | 48 | 18 | | 49 | 27 |
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| 54.58% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.37362637362637363 | | totalSentences | 91 | | uniqueOpeners | 34 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 81 | | matches | | 0 | "Just the crackle of a" | | 1 | "Then the tunnel opened up." | | 2 | "Then he stopped." | | 3 | "Then he turned his head—just" | | 4 | "Then he lifted a hand" |
| | ratio | 0.062 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 81 | | matches | | 0 | "She didn’t slow." | | 1 | "she muttered, voice low" | | 2 | "She didn’t wait for it." | | 3 | "She cut through a narrow" | | 4 | "Her fingers twitched toward her" | | 5 | "She exhaled through her nose," | | 6 | "It cast just enough light" | | 7 | "She’d heard whispers about this" | | 8 | "She ignored him." | | 9 | "She was losing him." | | 10 | "She pushed forward, shoving past" | | 11 | "He moved, quick and quiet," | | 12 | "She stepped forward." |
| | ratio | 0.16 | |
| 89.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 81 | | matches | | 0 | "The neon sign above *The" | | 1 | "The bar’s dim interior swallowed" | | 2 | "She didn’t slow." | | 3 | "The worn leather of her" | | 4 | "she muttered, voice low" | | 5 | "Static hissed in reply." | | 6 | "She didn’t wait for it." | | 7 | "The suspect—*Tomás Herrera*—had already vanished" | | 8 | "She cut through a narrow" | | 9 | "The scent of wet stone" | | 10 | "The Saint Christopher medallion around" | | 11 | "Quinn broke into a sprint." | | 12 | "The alley spilled into a" | | 13 | "Herrera glanced back, his warm" | | 14 | "The sign above read *Camden" | | 15 | "Quinn skidded to a halt" | | 16 | "The air rising from the" | | 17 | "Her fingers twitched toward her" | | 18 | "Backup still hadn’t responded." | | 19 | "A sound echoed up the" |
| | ratio | 0.741 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 81 | | matches | | 0 | "If she went down there" | | 1 | "Because something else had." | | 2 | "Even from this distance, she" |
| | ratio | 0.037 | |
| 79.37% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 4 | | matches | | 0 | "Herrera glanced back, his warm brown eyes locking onto hers for a split second before he veered left, disappearing down a set of stairs that led beneath the pav…" | | 1 | "It cast just enough light to see the graffiti scrawled across the tiles—symbols that didn’t belong to any language she recognised, looping and jagged, like some…" | | 2 | "Enchanted trinkets, banned substances, information that could get a person killed." | | 3 | "A stall to her left displayed rows of glass vials, their contents swirling with colours that made her eyes ache." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 1 | | matches | | 0 | "she muttered, voice low" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 3 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 1 | | effectiveRatio | 0.667 | |