| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.563 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 71.15% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1213 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "tightly" | | 1 | "very" | | 2 | "quickly" | | 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) | |
| 5.19% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1213 | | totalAiIsms | 23 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "echoed" | | 1 | "pounding" | | 2 | "glinting" | | 3 | "familiar" | | 4 | "maw" | | 5 | "racing" | | 6 | "gloom" | | 7 | "flickered" | | 8 | "electric" | | 9 | "glint" | | 10 | "scanned" | | 11 | "clandestine" | | 12 | "chill" | | 13 | "race" | | 14 | "eyebrow" | | 15 | "dancing" | | 16 | "intensity" | | 17 | "weight" | | 18 | "echoes" | | 19 | "delve" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 61 | | matches | | |
| 96.02% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 61 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 65 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 66 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1201 | | ratio | 0 | | matches | (empty) | |
| 62.50% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 1 | | matches | | 0 | "The Veil Market, they called it." |
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| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 1068 | | uniqueNames | 9 | | maxNameDensity | 1.22 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 13 | | London | 1 | | Morris | 2 | | Veil | 2 | | Market | 4 | | Speak | 1 | | You | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Market" | | 4 | "You" |
| | places | | | globalScore | 0.891 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1201 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 65 | | matches | (empty) | |
| 72.69% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 48.04 | | std | 19.43 | | cv | 0.404 | | sampleLengths | | 0 | 50 | | 1 | 49 | | 2 | 71 | | 3 | 93 | | 4 | 68 | | 5 | 80 | | 6 | 47 | | 7 | 70 | | 8 | 67 | | 9 | 36 | | 10 | 58 | | 11 | 42 | | 12 | 42 | | 13 | 22 | | 14 | 41 | | 15 | 36 | | 16 | 35 | | 17 | 33 | | 18 | 44 | | 19 | 12 | | 20 | 42 | | 21 | 12 | | 22 | 43 | | 23 | 66 | | 24 | 42 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 61 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 185 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 3 | | flaggedSentences | 12 | | totalSentences | 65 | | ratio | 0.185 | | matches | | 0 | "The figure ahead—a silhouette darting through the honeycomb of alleyways—clutched a damp coat around them as they rounded the corner." | | 1 | "The clatter of her worn leather watch against her wrist rang in her ears, a metronome of urgency as she tracked the suspect—a shadow that slithered in and out of lamp's reach." | | 2 | "This chase was about more than catching a phantom in the night; it was about vengeance for her lost partner, DS Morris, whose demise echoed in her mind like a vengeful ghost." | | 3 | "Ahead, the alley entwined into another world, one she was reluctant to breach—one she had only heard whispered about in guarded conversations." | | 4 | "The rain quickly faded behind her, swallowed by a different kind of sound—a low hum buzzed like an electric current fusing through the air, growing louder with each step, pulling her deeper into the shadows." | | 5 | "The underground was more crowded than she had anticipated; figures flitted between hanging fabrics and dimly lit stalls." | | 6 | "Quinn quickly assessed her surroundings, noting the strange wares on display—crimson potions bubbling in glass containers, talismans swaying in the shimmering candlelight, and what appeared to be an assortment of bones arranged into strange patterns atop an old crate." | | 7 | "Suddenly, she spotted her shadow—her quarry—slipping into a back room, the glint of a hidden latch barely visible against the worn wooden door." | | 8 | "In the flickering light, figures populated the room—shady characters engaged in hushed conversations, exchanging clandestine tokens in the flickering firelight." | | 9 | "But she couldn't—this was her only lead." | | 10 | "“Very well, but information comes at a cost.” The woman’s eyes locked onto Quinn's; the intensity grew thick in the air. “That medallion is worth more than gold down here." | | 11 | "As the hum of the Veil Market enveloped her, Quinn clenched her fists. Answers lay ahead, and she was no longer merely a detective following shadows. No—she was a hunter carving her way through the dark, and she would not emerge empty-handed." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 901 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.0244173140954495 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.01553829078801332 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 65 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 65 | | mean | 18.48 | | std | 12 | | cv | 0.649 | | sampleLengths | | 0 | 20 | | 1 | 17 | | 2 | 13 | | 3 | 10 | | 4 | 20 | | 5 | 19 | | 6 | 21 | | 7 | 18 | | 8 | 32 | | 9 | 12 | | 10 | 7 | | 11 | 12 | | 12 | 30 | | 13 | 32 | | 14 | 30 | | 15 | 16 | | 16 | 22 | | 17 | 14 | | 18 | 22 | | 19 | 6 | | 20 | 14 | | 21 | 24 | | 22 | 21 | | 23 | 3 | | 24 | 4 | | 25 | 19 | | 26 | 12 | | 27 | 35 | | 28 | 23 | | 29 | 18 | | 30 | 39 | | 31 | 3 | | 32 | 7 | | 33 | 23 | | 34 | 13 | | 35 | 19 | | 36 | 17 | | 37 | 22 | | 38 | 20 | | 39 | 15 | | 40 | 7 | | 41 | 33 | | 42 | 9 | | 43 | 10 | | 44 | 12 | | 45 | 33 | | 46 | 8 | | 47 | 3 | | 48 | 12 | | 49 | 21 |
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| 82.05% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.5384615384615384 | | totalSentences | 65 | | uniqueOpeners | 35 | |
| 55.56% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 60 | | matches | | 0 | "Suddenly, she spotted her shadow—her" |
| | ratio | 0.017 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 10 | | totalSentences | 60 | | matches | | 0 | "she shouted, her voice rising" | | 1 | "She sprinted forward, pounding her" | | 2 | "She paused before the archway," | | 3 | "Her eyes flickered towards the" | | 4 | "She needed answers." | | 5 | "She needed them now." | | 6 | "Her gut twisted." | | 7 | "She had entered a den" | | 8 | "Her eyes glimmered with mischief" | | 9 | "You may find him at" |
| | ratio | 0.167 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 43 | | totalSentences | 60 | | matches | | 0 | "The rain fell in sheets," | | 1 | "Detective Harlow Quinn ducked beneath" | | 2 | "A heartbeat echoed behind her," | | 3 | "she shouted, her voice rising" | | 4 | "The figure ahead—a silhouette darting" | | 5 | "The street was glinting with" | | 6 | "Quinn felt the familiar surge" | | 7 | "She sprinted forward, pounding her" | | 8 | "The clatter of her worn" | | 9 | "The figure slipped into the" | | 10 | "Quinn ground to a halt," | | 11 | "Caution whispered in her ear," | | 12 | "The suspect had already cemented" | | 13 | "This chase was about more" | | 14 | "The alley stretched before her," | | 15 | "She paused before the archway," | | 16 | "The Veil Market, they called" | | 17 | "An underground market that shifted" | | 18 | "The stories painted it as" | | 19 | "Her eyes flickered towards the" |
| | ratio | 0.717 | |
| 83.33% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 60 | | matches | | 0 | "If the suspect had ties" |
| | ratio | 0.017 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 8 | | matches | | 0 | "The clatter of her worn leather watch against her wrist rang in her ears, a metronome of urgency as she tracked the suspect—a shadow that slithered in and out o…" | | 1 | "The suspect had already cemented their value in her investigation regarding the clique, and the streets had sung tales of their rumored dealings that draped ove…" | | 2 | "There was something restless beneath the surface, as if the very brick and mortar of this city held secrets, ancient and dark." | | 3 | "The stories painted it as a realm of enchantments, black market deals, and the likes of individuals who trafficked in both secrets and sorcery." | | 4 | "The darkness clung to her like a shroud, but she moved with purpose, pressing ahead, her instincts guiding her where light dared not." | | 5 | "Quinn quickly assessed her surroundings, noting the strange wares on display—crimson potions bubbling in glass containers, talismans swaying in the shimmering c…" | | 6 | "Squeezing through the crowded entryway, she quickly scanned for any sign of the suspect, her eyes narrowing." | | 7 | "As Quinn weighed her options, tides of doubt swept over her. The spiraling uncertainty tightened her insides. She could lose everything by playing this game, ve…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 3 | | matches | | 0 | "she shouted, her voice rising above the pounding rain" | | 1 | "Quinn countered, her tone steely" | | 2 | "The woman leaned, her voice low, laced with laughter" |
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| 87.50% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 16 | | tagDensity | 0.125 | | leniency | 0.25 | | rawRatio | 0.5 | | effectiveRatio | 0.125 | |