| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 92.05% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1258 | | 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) | |
| 56.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1258 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "familiar" | | 1 | "aftermath" | | 2 | "rhythmic" | | 3 | "porcelain" | | 4 | "standard" | | 5 | "fractured" | | 6 | "warmth" | | 7 | "flickered" | | 8 | "etched" | | 9 | "scanned" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
| | 1 | | label | "clenched jaw/fists" | | count | 1 |
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| | highlights | | 0 | "knuckles turned white" | | 1 | "clenched fist" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 90 | | matches | (empty) | |
| 79.37% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 1 | | narrationSentences | 90 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 90 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1254 | | ratio | 0.001 | | matches | | |
| 93.75% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 1 | | matches | | 0 | "The police report says this man was a drifter, an accident involving the old power grid, Harlow said, her voice dropping…" |
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| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 51 | | wordCount | 1254 | | uniqueNames | 14 | | maxNameDensity | 1.44 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Harlow" | | discoveredNames | | Camden | 1 | | Detective | 1 | | Harlow | 18 | | Quinn | 1 | | Tube | 2 | | Victorian | 1 | | Veil | 5 | | Market | 3 | | Kowalski | 1 | | Eva | 10 | | Morris | 1 | | Compass | 1 | | Shade | 1 | | You | 5 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Market" | | 4 | "Kowalski" | | 5 | "Eva" | | 6 | "Morris" | | 7 | "Compass" | | 8 | "You" |
| | places | | | globalScore | 0.782 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 79 | | glossingSentenceCount | 1 | | matches | | 0 | "circles that seemed to vibrate even in the stagnant air" |
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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 | 1254 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 90 | | matches | | 0 | "realized that rationality" |
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| 86.37% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 43.24 | | std | 19.56 | | cv | 0.452 | | sampleLengths | | 0 | 82 | | 1 | 36 | | 2 | 64 | | 3 | 7 | | 4 | 66 | | 5 | 26 | | 6 | 20 | | 7 | 46 | | 8 | 46 | | 9 | 51 | | 10 | 62 | | 11 | 21 | | 12 | 61 | | 13 | 30 | | 14 | 32 | | 15 | 63 | | 16 | 54 | | 17 | 21 | | 18 | 55 | | 19 | 53 | | 20 | 63 | | 21 | 65 | | 22 | 31 | | 23 | 20 | | 24 | 35 | | 25 | 10 | | 26 | 47 | | 27 | 65 | | 28 | 22 |
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| 81.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 90 | | matches | | 0 | "was bled" | | 1 | "was slumped" | | 2 | "was stolen" | | 3 | "been tampered" | | 4 | "get suppressed" | | 5 | "been sealed" |
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| 49.17% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 221 | | matches | | 0 | "was burning" | | 1 | "was just checking" | | 2 | "were looking" | | 3 | "was weeping" | | 4 | "wasn't drying" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 1 | | flaggedSentences | 5 | | totalSentences | 90 | | ratio | 0.056 | | matches | | 0 | "In the center of the derelict track bed—a space that, according to the local transit charts, shouldn't have been accessible via the tunnels leading to the Veil Market—lay a body." | | 1 | "Harlow, I—I was just checking the archives." | | 2 | "The blood wasn't drying; it was weeping upward, droplets hovering an inch off the floor." | | 3 | "You and your friends—you’ve been poking at the seams of this city for months." | | 4 | "She climbed, heading back toward the surface, toward the world that believed itself safe, leaving the darkness to its own devices—for now." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1262 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.01901743264659271 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.005546751188589541 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 90 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 90 | | mean | 13.93 | | std | 8.25 | | cv | 0.592 | | sampleLengths | | 0 | 17 | | 1 | 34 | | 2 | 31 | | 3 | 19 | | 4 | 17 | | 5 | 20 | | 6 | 14 | | 7 | 30 | | 8 | 7 | | 9 | 20 | | 10 | 22 | | 11 | 24 | | 12 | 19 | | 13 | 7 | | 14 | 11 | | 15 | 9 | | 16 | 14 | | 17 | 11 | | 18 | 7 | | 19 | 9 | | 20 | 5 | | 21 | 6 | | 22 | 7 | | 23 | 23 | | 24 | 10 | | 25 | 13 | | 26 | 7 | | 27 | 7 | | 28 | 3 | | 29 | 13 | | 30 | 8 | | 31 | 15 | | 32 | 17 | | 33 | 5 | | 34 | 25 | | 35 | 11 | | 36 | 10 | | 37 | 24 | | 38 | 10 | | 39 | 14 | | 40 | 3 | | 41 | 10 | | 42 | 30 | | 43 | 17 | | 44 | 8 | | 45 | 7 | | 46 | 16 | | 47 | 4 | | 48 | 8 | | 49 | 13 |
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| 35.93% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.32222222222222224 | | totalSentences | 90 | | uniqueOpeners | 29 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 89 | | matches | (empty) | | ratio | 0 | |
| 26.74% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 43 | | totalSentences | 89 | | matches | | 0 | "It was a thick, metallic" | | 1 | "She stepped off the rusted" | | 2 | "Her sharp jaw was set," | | 3 | "She looked uncharacteristically gaunt, her" | | 4 | "She wore her usual round" | | 5 | "She stopped a few feet" | | 6 | "Her green eyes flickered with" | | 7 | "I felt a shift in" | | 8 | "It isn’t murder, Harlow, Eva" | | 9 | "They’re necrotic pathways." | | 10 | "It used a rip in" | | 11 | "She pulled a pair of" | | 12 | "She studied the scorch marks." | | 13 | "She reached out, hovering her" | | 14 | "I’ve seen things like this" | | 15 | "She ignored the way her" | | 16 | "She reached into her inner" | | 17 | "Its casing, slick with a" | | 18 | "You didn’t just follow a" | | 19 | "You were looking for this," |
| | ratio | 0.483 | |
| 44.27% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 89 | | matches | | 0 | "The air a dozen feet" | | 1 | "It was a thick, metallic" | | 2 | "She stepped off the rusted" | | 3 | "Harlow didn't need to look" | | 4 | "Her sharp jaw was set," | | 5 | "Eva Kowalski stood near the" | | 6 | "She looked uncharacteristically gaunt, her" | | 7 | "She wore her usual round" | | 8 | "Harlow bypassed the forensics team," | | 9 | "She stopped a few feet" | | 10 | "Harlow asked, her voice clipped" | | 11 | "Eva jumped, her hands instinctively" | | 12 | "Her green eyes flickered with" | | 13 | "Harlow, I—I was just checking" | | 14 | "I felt a shift in" | | 15 | "A tremor in the Veil." | | 16 | "A tremor, Harlow repeated, stepping" | | 17 | "The detective’s gaze swept over" | | 18 | "The victim was slumped against" | | 19 | "That’s a convenient piece of" |
| | ratio | 0.831 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 89 | | matches | | 0 | "To the untrained eye, they" | | 1 | "If the signal doesn't get" | | 2 | "If you bring the light" |
| | ratio | 0.034 | |
| 38.96% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 8 | | matches | | 0 | "It was a thick, metallic tang that clung to the back of Detective Harlow Quinn’s throat, a familiar scent she had learned to identify in the aftermath of her pa…" | | 1 | "She stepped off the rusted service ladder and onto the grit-covered tiling of the abandoned Tube station, her boots clicking with a hollow, rhythmic military ca…" | | 2 | "Taped-off perimeters crisscrossed the platform, marking a crime scene that defied the physics of a standard homicide." | | 3 | "In the center of the derelict track bed—a space that, according to the local transit charts, shouldn't have been accessible via the tunnels leading to the Veil …" | | 4 | "The victim was slumped against the third rail, their clothes scorched in concentric circles that seemed to vibrate even in the stagnant air." | | 5 | "The police report says this man was a drifter, an accident involving the old power grid, Harlow said, her voice dropping to a low, dangerous frequency." | | 6 | "She had spent years trying to rationalize the death of her partner, trying to fit the impossible into the narrow, measurable boxes of a police report." | | 7 | "I’m doing it because if the department finds out what’s actually buried under the Tube, they’ll level this entire district, and they still won't catch the thing…" |
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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 | |