| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 2 | | adverbTags | | 0 | "Eva asked softly [softly]" | | 1 | "Eva said suddenly [suddenly]" |
| | dialogueSentences | 40 | | tagDensity | 0.575 | | leniency | 1 | | rawRatio | 0.087 | | effectiveRatio | 0.087 | |
| 91.62% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2387 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | | 2 | | adverb | "deliberately" | | count | 1 |
| | 3 | |
| | highlights | | 0 | "slightly" | | 1 | "softly" | | 2 | "deliberately" | | 3 | "suddenly" |
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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) | |
| 85.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2387 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "etched" | | 1 | "flicked" | | 2 | "weight" | | 3 | "otherworldly" | | 4 | "perfect" | | 5 | "familiar" |
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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 | 139 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 139 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 155 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 73 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2362 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 59 | | wordCount | 1847 | | uniqueNames | 10 | | maxNameDensity | 1.3 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 24 | | Quinn | 2 | | Veil | 1 | | Market | 2 | | Kowalski | 1 | | Eva | 21 | | Morris | 4 | | Shade | 2 | | Platform | 1 | | Three | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Kowalski" | | 4 | "Eva" | | 5 | "Morris" | | 6 | "Shade" |
| | places | | | globalScore | 0.85 | | windowScore | 0.667 | |
| 13.64% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 110 | | glossingSentenceCount | 6 | | matches | | 0 | "something like lavender—an incense she could" | | 1 | "looked like the victim had dragged themse" | | 2 | "tasted like regret" | | 3 | "as if reading them into existence" | | 4 | "smelled like damp paper and old cedar and" | | 5 | "something like pleading in her face, \"—I tho" |
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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 | 2362 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 155 | | matches | | 0 | "meant—that it" | | 1 | "down that tunnel" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 52.49 | | std | 30.94 | | cv | 0.589 | | sampleLengths | | 0 | 111 | | 1 | 62 | | 2 | 81 | | 3 | 18 | | 4 | 56 | | 5 | 67 | | 6 | 51 | | 7 | 13 | | 8 | 99 | | 9 | 68 | | 10 | 27 | | 11 | 74 | | 12 | 11 | | 13 | 18 | | 14 | 69 | | 15 | 80 | | 16 | 32 | | 17 | 136 | | 18 | 109 | | 19 | 47 | | 20 | 21 | | 21 | 77 | | 22 | 27 | | 23 | 50 | | 24 | 73 | | 25 | 73 | | 26 | 17 | | 27 | 15 | | 28 | 6 | | 29 | 30 | | 30 | 35 | | 31 | 73 | | 32 | 19 | | 33 | 74 | | 34 | 72 | | 35 | 26 | | 36 | 8 | | 37 | 62 | | 38 | 26 | | 39 | 23 | | 40 | 64 | | 41 | 43 | | 42 | 58 | | 43 | 66 | | 44 | 95 |
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| 82.54% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 9 | | totalSentences | 139 | | matches | | 0 | "been stripped" | | 1 | "was compressed" | | 2 | "been given" | | 3 | "been placed" | | 4 | "been crafted" | | 5 | "been accompanied" | | 6 | "been bruised" | | 7 | "been used" | | 8 | "been laid" | | 9 | "were polished" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 317 | | matches | | 0 | "was tucking" | | 1 | "was riffling" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 22 | | semicolonCount | 6 | | flaggedSentences | 24 | | totalSentences | 155 | | ratio | 0.155 | | matches | | 0 | "Her shoes sank once into grit on the platform; the light from the forensic van made long, thin pools on the tracks." | | 1 | "Tape flapped in the stale wind, but it was the wrong kind of cordon for a place like this—police issue, neat and antiseptic—where the Veil Market preferred shadows and bone tokens." | | 2 | "Beneath the yellow tape the market had been stripped of its usual chaos: stalls shuttered, ropes furloughed, an overturned crate that still smelled faintly of cedar and something like lavender—an incense she could not name." | | 3 | "Detective Quinn kept her arms at her sides because that was how you tracked movement—you noticed what was compressed and what returned to shape." | | 4 | "The satchel at her hip bulged with the edges of paper and bindings; the leather was cracked from use." | | 5 | "She didn't say what she meant—that it was always busy, that lines and stairs and the city itself stalled and restarted and that now the world had a way of making people late right before something broke." | | 6 | "Observation in the little moments: the tug at the hair, the voice pitched an octave up—those were the cracks where reason aired itself." | | 7 | "She counted the scuff marks the way a carpenter counts nails—because the pattern told a story the person had not intended to tell." | | 8 | "The victim's hands bore the print of palms that had been roughly washed; the wash was deliberate." | | 9 | "There was a faint chemical smell—ozone?—but it had a sharp sweetness behind it, petroleum and spice: methylated spirits." | | 10 | "She looked at the knot that cinched the ribbon around the compass—it was a left-handed tie." | | 11 | "Left-handed knots weren't common; most people used right-handed." | | 12 | "It pointed steadily—not toward the dark farther down the track where the market would sit in secret—but toward the service tunnel that fed out under the borough." | | 13 | "She did not drink from it; she noted the dent in the lip instead." | | 14 | "The body had no trace of oxygen deprivation—no froth at the mouth." | | 15 | "It suggested a single strike delivered by someone who knew how to dampen an impact—an old trick from crowded alleys, a gloved fist with a blunt instrument hidden in a coat." | | 16 | "\"Same as fake watches and 'antique' silver. The market's goods are stamped like factory marks. Forgeries are a thing. More importantly—\" she tapped the needle with a gloved finger, careful, \"—it points away. The perpetrator wants us to look down that tunnel. They want us to follow the compass and find nothing. They want the idea of a rift out there, open and dangerous, to stay in the paper. A perfect scapegoat.\"" | | 17 | "Her memory flared—the soft, impossible absence at Morris's body." | | 18 | "\"I thought—\" she looked at Harlow, something like pleading in her face, \"—I thought maybe he fell through a portal and someone tried to patch the story because—\"" | | 19 | "She felt the old, brittle fear at her ribs—the one that had settled there the day Morris had died in a way she still couldn't prove—and she let it be a tool instead of a wound." | | 20 | "\"Don't eat your satchel, Evie. It'd be a mess. We dust everything. We canvass. We check the CCTV. And you—\" she softened, because some things needed gentleness, \"—you keep cataloguing the sigils. If someone's forging artifacts they're sloppy in different places. Their metalwork might be good, but their patterns repeat. The Market is full of makers. Forgeries are a signature too.\"" | | 21 | "Down here, under the market that moved with the moon, Harlow felt the familiar shape of a case beginning to form—a person whose fear had been used like a currency and a body who had been laid down like a ledger entry." | | 22 | "She had learned to watch for the fingerprints the clever left behind—the ones they thought no one would notice." | | 23 | "She had lost one person to the thing that had no shape and no smell; she would not lose her grip on the other things that were painfully, distinctly human." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1851 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 54 | | adverbRatio | 0.029173419773095625 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.00864397622906537 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 155 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 155 | | mean | 15.24 | | std | 11.82 | | cv | 0.775 | | sampleLengths | | 0 | 23 | | 1 | 22 | | 2 | 31 | | 3 | 35 | | 4 | 24 | | 5 | 16 | | 6 | 22 | | 7 | 15 | | 8 | 36 | | 9 | 19 | | 10 | 11 | | 11 | 7 | | 12 | 11 | | 13 | 16 | | 14 | 3 | | 15 | 37 | | 16 | 11 | | 17 | 6 | | 18 | 3 | | 19 | 4 | | 20 | 15 | | 21 | 18 | | 22 | 10 | | 23 | 24 | | 24 | 11 | | 25 | 16 | | 26 | 3 | | 27 | 10 | | 28 | 10 | | 29 | 23 | | 30 | 16 | | 31 | 27 | | 32 | 23 | | 33 | 2 | | 34 | 6 | | 35 | 15 | | 36 | 17 | | 37 | 18 | | 38 | 10 | | 39 | 22 | | 40 | 5 | | 41 | 5 | | 42 | 10 | | 43 | 16 | | 44 | 8 | | 45 | 3 | | 46 | 5 | | 47 | 17 | | 48 | 4 | | 49 | 6 |
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| 43.23% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.32903225806451614 | | totalSentences | 155 | | uniqueOpeners | 51 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 124 | | matches | (empty) | | ratio | 0 | |
| 81.29% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 43 | | totalSentences | 124 | | matches | | 0 | "Her shoes sank once into" | | 1 | "Her watch, a worn leather" | | 2 | "Her jaw tightened with a" | | 3 | "She had pushed her glasses" | | 4 | "She wore a shawl that" | | 5 | "Her voice had the patient" | | 6 | "She didn't say what she" | | 7 | "She moved around the tarp," | | 8 | "Her eyes found the platform" | | 9 | "She counted the scuff marks" | | 10 | "She could taste the memory" | | 11 | "It had been placed recently:" | | 12 | "She looked at the knot" | | 13 | "Her partner's absence widened it." | | 14 | "She felt the old weight" | | 15 | "He had not make left-handed" | | 16 | "Her voice was flat, practical." | | 17 | "She said it like an" | | 18 | "It pointed steadily—not toward the" | | 19 | "She sounded wounded the way" |
| | ratio | 0.347 | |
| 44.68% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 103 | | totalSentences | 124 | | matches | | 0 | "The stairwell smelled of rust" | | 1 | "Her shoes sank once into" | | 2 | "Tape flapped in the stale" | | 3 | "Detective Quinn kept her arms" | | 4 | "Her watch, a worn leather" | | 5 | "Her jaw tightened with a" | | 6 | "Eva Kowalski stood by the" | | 7 | "She had pushed her glasses" | | 8 | "The satchel at her hip" | | 9 | "She wore a shawl that" | | 10 | "Eva said without looking up" | | 11 | "Her voice had the patient" | | 12 | "Harlow glanced at the two" | | 13 | "She didn't say what she" | | 14 | "The body lay on a" | | 15 | "A pale smudge on the" | | 16 | "Eva's eyes were on the" | | 17 | "Someone had propped it to" | | 18 | "Harlow watched Eva's hand tremble" | | 19 | "Observation in the little moments:" |
| | ratio | 0.831 | |
| 40.32% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 124 | | matches | | 0 | "If you faked fire with" |
| | ratio | 0.008 | |
| 89.95% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 81 | | technicalSentenceCount | 6 | | matches | | 0 | "She looked at the knot that cinched the ribbon around the compass—it was a left-handed tie." | | 1 | "She felt the old weight of Morris at her shoulder, a phantom presence that tasted like regret." | | 2 | "Eva's mouth formed soft vowels as if reading them into existence." | | 3 | "It suggested a single strike delivered by someone who knew how to dampen an impact—an old trick from crowded alleys, a gloved fist with a blunt instrument hidde…" | | 4 | "She glanced at Eva, who had already returned to her notes, lips moving around half-formed words." | | 5 | "She had lost one person to the thing that had no shape and no smell; she would not lose her grip on the other things that were painfully, distinctly human." |
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| 38.04% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 4 | | matches | | 0 | "Eva asked softly, as if the question was for herself as much as for Harlow" | | 1 | "Harlow lowered, the wood protesting in tiny cracks" | | 2 | "she tapped, careful," | | 3 | "she softened, because some things needed gentleness," |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 2 | | fancyTags | | 0 | "Harlow corrected (correct)" | | 1 | "Eva murmured (murmur)" |
| | dialogueSentences | 40 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.125 | | effectiveRatio | 0.1 | |