| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 94.40% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1785 | | totalAiIsmAdverbs | 2 | | 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) | |
| 32.77% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1785 | | totalAiIsms | 24 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | |
| | highlights | | 0 | "vibrated" | | 1 | "familiar" | | 2 | "shattered" | | 3 | "navigated" | | 4 | "scanning" | | 5 | "standard" | | 6 | "perfect" | | 7 | "shimmered" | | 8 | "etched" | | 9 | "trembled" | | 10 | "stark" | | 11 | "magnetic" | | 12 | "pulse" | | 13 | "whisper" | | 14 | "traced" | | 15 | "scanned" | | 16 | "calibrated" | | 17 | "weight" | | 18 | "unravel" | | 19 | "silence" | | 20 | "chill" |
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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 | 254 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 7 | | hedgeCount | 0 | | narrationSentences | 254 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 254 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1785 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 8 | | matches | | 0 | "Do not step on the blue chalk, Eva said without looking up." | | 1 | "Gravity is fine, Harlow said." | | 2 | "Do not touch that, Eva warned, straightening." | | 3 | "Your gangland theory, Harlow said, voice low." | | 4 | "Fits the physical evidence, Eva said." | | 5 | "Quinn, Eva said, voice tight." | | 6 | "Morris did not die in Docklands, Harlow said, not turning." | | 7 | "They did not rob him, Harlow said." |
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| 96.78% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 68 | | wordCount | 1785 | | uniqueNames | 21 | | maxNameDensity | 1.06 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 19 | | Quinn | 3 | | Camden | 1 | | Metropolitan | 1 | | Police | 1 | | Northern | 1 | | Line | 1 | | Veil | 3 | | Market | 1 | | London | 1 | | Kowalski | 2 | | British | 1 | | Museum | 1 | | Eva | 15 | | Compass | 1 | | Morris | 2 | | Docklands | 2 | | Shade | 2 | | Three | 3 | | You | 4 | | Fits | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Police" | | 3 | "Market" | | 4 | "Kowalski" | | 5 | "Museum" | | 6 | "Eva" | | 7 | "Morris" | | 8 | "You" |
| | places | | 0 | "Camden" | | 1 | "London" | | 2 | "British" | | 3 | "Docklands" |
| | globalScore | 0.968 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 141 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like a stage play dressed by someo" | | 1 | "tasted like ash and old coffee" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.56 | | wordCount | 1785 | | matches | | 0 | "not narcotics but alchemical reagents" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 254 | | matches | | 0 | "touch that, Eva" | | 1 | "make that mistake" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 51 | | std | 27.53 | | cv | 0.54 | | sampleLengths | | 0 | 93 | | 1 | 57 | | 2 | 101 | | 3 | 79 | | 4 | 36 | | 5 | 34 | | 6 | 84 | | 7 | 61 | | 8 | 9 | | 9 | 71 | | 10 | 48 | | 11 | 64 | | 12 | 35 | | 13 | 28 | | 14 | 57 | | 15 | 87 | | 16 | 17 | | 17 | 9 | | 18 | 54 | | 19 | 28 | | 20 | 4 | | 21 | 89 | | 22 | 10 | | 23 | 61 | | 24 | 46 | | 25 | 20 | | 26 | 59 | | 27 | 72 | | 28 | 43 | | 29 | 81 | | 30 | 11 | | 31 | 96 | | 32 | 38 | | 33 | 60 | | 34 | 43 |
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| 92.83% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 9 | | totalSentences | 254 | | matches | | 0 | "was scratched" | | 1 | "been forced" | | 2 | "was etched" | | 3 | "was anchored" | | 4 | "are staged" | | 5 | "was placed" | | 6 | "was dressed" | | 7 | "was pulled" | | 8 | "gets siphoned" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 327 | | matches | | 0 | "were lying" | | 1 | "was not pointing" | | 2 | "was falling" | | 3 | "were trying" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 254 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1792 | | adjectiveStacks | 2 | | stackExamples | | 0 | "heavier, pressing against her" | | 1 | "thick, cloth-bound folio." |
| | adverbCount | 41 | | adverbRatio | 0.022879464285714284 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.006696428571428571 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 254 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 254 | | mean | 7.03 | | std | 4.89 | | cv | 0.696 | | sampleLengths | | 0 | 14 | | 1 | 22 | | 2 | 26 | | 3 | 16 | | 4 | 15 | | 5 | 10 | | 6 | 14 | | 7 | 1 | | 8 | 4 | | 9 | 10 | | 10 | 18 | | 11 | 8 | | 12 | 13 | | 13 | 6 | | 14 | 19 | | 15 | 5 | | 16 | 5 | | 17 | 25 | | 18 | 12 | | 19 | 8 | | 20 | 13 | | 21 | 14 | | 22 | 2 | | 23 | 19 | | 24 | 24 | | 25 | 3 | | 26 | 4 | | 27 | 12 | | 28 | 17 | | 29 | 3 | | 30 | 4 | | 31 | 8 | | 32 | 10 | | 33 | 2 | | 34 | 3 | | 35 | 6 | | 36 | 5 | | 37 | 11 | | 38 | 1 | | 39 | 1 | | 40 | 7 | | 41 | 6 | | 42 | 6 | | 43 | 7 | | 44 | 9 | | 45 | 9 | | 46 | 2 | | 47 | 2 | | 48 | 8 | | 49 | 15 |
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| 47.09% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 28 | | diversityRatio | 0.3492063492063492 | | totalSentences | 252 | | uniqueOpeners | 88 | |
| 90.50% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 221 | | matches | | 0 | "Just a perfect, cauterized hole" | | 1 | "Then it stops." | | 2 | "Just a whisper of ozone" | | 3 | "Too shallow for a running" | | 4 | "Just a clean circle." | | 5 | "Then we move faster." |
| | ratio | 0.027 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 58 | | totalSentences | 221 | | matches | | 0 | "She checked the worn leather" | | 1 | "Her sharp jaw tightened." | | 2 | "She was technically a civilian" | | 3 | "She respected results more." | | 4 | "Her voice was steady, but" | | 5 | "I know how to walk" | | 6 | "She tapped a gloved finger" | | 7 | "They are running ballistics on" | | 8 | "Her knees protested, but she" | | 9 | "She pulled back the sheet." | | 10 | "She leaned closer." | | 11 | "Your angle is wrong." | | 12 | "It points to a territorial" | | 13 | "She moved toward it, gloved" | | 14 | "It trembled, spinning lazily before" | | 15 | "Her freckles stood out stark" | | 16 | "It is a Veil Compass." | | 17 | "It does not track magnetic" | | 18 | "It tracks tears in the" | | 19 | "She turned the compass over" |
| | ratio | 0.262 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 152 | | totalSentences | 221 | | matches | | 0 | "The rusted service ladder vibrated" | | 1 | "Each descent into the Camden" | | 2 | "The air thickened with every" | | 3 | "She checked the worn leather" | | 4 | "The glass was scratched, the" | | 5 | "Her sharp jaw tightened." | | 6 | "The briefing called it a" | | 7 | "The reality felt like a" | | 8 | "The abandoned station opened into" | | 9 | "Emergency floodlights cast sickly yellow" | | 10 | "Canvas stalls slumped like dead" | | 11 | "Glass vials lay shattered across" | | 12 | "This was the Veil Market." | | 13 | "The bone token in her" | | 14 | "The market moved with the" | | 15 | "Tonight, it had been forced" | | 16 | "A figure knelt near the" | | 17 | "She was technically a civilian" | | 18 | "Harlow respected degrees." | | 19 | "She respected results more." |
| | ratio | 0.688 | |
| 45.25% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 221 | | matches | | 0 | "If you crush one at" | | 1 | "If the market moves, the" |
| | ratio | 0.009 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 5 | | matches | | 0 | "The air thickened with every rung, carrying the scent of wet concrete, ozone, and a sharp, coppery sweetness that clung to the back of her throat." | | 1 | "Glass vials lay shattered across the tiled platform, leaking iridescent sludge that refused to mix with the standing water." | | 2 | "The bone token in her coat pocket, a confiscated curio that had granted her passage past the hidden wardens, felt unnaturally heavy against her ribs." | | 3 | "She was technically a civilian consultant, pulled from the British Museum's restricted archives because the forensics team kept finding ash that defied chemical…" | | 4 | "The face was etched with interlocking geometric patterns, protective sigils that made her eyes ache if she stared too long." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |