| 66.67% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "Tomás said softly [softly]" |
| | dialogueSentences | 15 | | tagDensity | 0.467 | | leniency | 0.933 | | rawRatio | 0.143 | | effectiveRatio | 0.133 | |
| 81.88% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1104 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "suddenly" | | 1 | "sharply" | | 2 | "softly" |
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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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1104 | | totalAiIsms | 27 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | |
| | highlights | | 0 | "pounding" | | 1 | "echoed" | | 2 | "footsteps" | | 3 | "chill" | | 4 | "familiar" | | 5 | "tinged" | | 6 | "sinister" | | 7 | "could feel" | | 8 | "pulsed" | | 9 | "scanned" | | 10 | "navigated" | | 11 | "gleaming" | | 12 | "standard" | | 13 | "jaw clenched" | | 14 | "chaotic" | | 15 | "shimmered" | | 16 | "raced" | | 17 | "velvet" | | 18 | "silence" | | 19 | "weight" | | 20 | "pulse" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
| | 1 | | label | "weight of words/silence" | | count | 1 |
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| | highlights | | 0 | "jaw clenched" | | 1 | "the weight of the moment" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 78 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 78 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 86 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1081 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 93.36% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 971 | | uniqueNames | 10 | | maxNameDensity | 1.13 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 2 | | Quinn | 11 | | Soho | 1 | | Veil | 2 | | Market | 2 | | Tube | 1 | | Saint | 1 | | Christopher | 1 | | Herrera | 1 | | Tomás | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Herrera" | | 6 | "Tomás" |
| | places | | | globalScore | 0.934 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.925 | | wordCount | 1081 | | matches | | 0 | "not getting away,” she called out, voice low but sharp, cutting through the pounding rain" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 86 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 27.03 | | std | 17.39 | | cv | 0.644 | | sampleLengths | | 0 | 71 | | 1 | 16 | | 2 | 49 | | 3 | 42 | | 4 | 37 | | 5 | 45 | | 6 | 68 | | 7 | 8 | | 8 | 35 | | 9 | 29 | | 10 | 29 | | 11 | 6 | | 12 | 12 | | 13 | 53 | | 14 | 20 | | 15 | 11 | | 16 | 30 | | 17 | 17 | | 18 | 57 | | 19 | 35 | | 20 | 13 | | 21 | 51 | | 22 | 28 | | 23 | 4 | | 24 | 29 | | 25 | 29 | | 26 | 13 | | 27 | 1 | | 28 | 11 | | 29 | 18 | | 30 | 42 | | 31 | 22 | | 32 | 13 | | 33 | 22 | | 34 | 19 | | 35 | 19 | | 36 | 6 | | 37 | 9 | | 38 | 40 | | 39 | 22 |
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| 91.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 78 | | matches | | 0 | "get drawn" | | 1 | "was meant" | | 2 | "were frayed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 184 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 16 | | semicolonCount | 0 | | flaggedSentences | 14 | | totalSentences | 86 | | ratio | 0.163 | | matches | | 0 | "The city at night had a grit all its own in the rain—a slick sheen on cobblestones, neon washing over wet surfaces, shadows that moved just out of reach." | | 1 | "Quinn hesitated on the threshold—her breath visible in the cold air, mixing with the damp fog rising from the stairwell." | | 2 | "A faint murmur echoed from below—voices in a language she didn’t catch, footsteps heavy but careful." | | 3 | "The air hit her heavier here, tinged with hints of smoke, grime, and something far more pungent—alchemy, old and sinister." | | 4 | "She knew the risks—off-duty did not mean off-the-wall here." | | 5 | "Pausing, she scanned the crowd—a surge of bodies, faces half-hidden beneath hoods, eyes glittering with odd colours and unnatural light." | | 6 | "The former paramedic had slipped under her radar until recently—he stitched wounds unseen by standard medics, tending to others like..." | | 7 | "And the way they vanished—the stolen nights, whispered allegiances—it all surfaced here beneath the city’s restless feet." | | 8 | "Her eyes picked out the suspect again—a flash of a drenched trench coat slipping between merchant booths, disappearing through a curtain of aged velvet drapes." | | 9 | "She pulled out the bone token she’d found earlier, weighing it in her hand—a kind of admission into this underbelly, the price paid to enter this underground market." | | 10 | "Suddenly, the trench coat turned sharply—a flash of wild eyes meeting hers." | | 11 | "A sudden hand caught her wrist—cold and strong." | | 12 | "She felt the weight of the moment—the choice to descend further into unknown territory or cut the chase loose." | | 13 | "The underground market opened anew—ancient tunnels blossomed into cavernous halls crowded with figures trading in secrets and shadows." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 993 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.02920443101711984 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.011077542799597181 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 86 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 86 | | mean | 12.57 | | std | 7.28 | | cv | 0.579 | | sampleLengths | | 0 | 16 | | 1 | 29 | | 2 | 26 | | 3 | 16 | | 4 | 5 | | 5 | 16 | | 6 | 20 | | 7 | 8 | | 8 | 3 | | 9 | 13 | | 10 | 16 | | 11 | 4 | | 12 | 6 | | 13 | 9 | | 14 | 28 | | 15 | 11 | | 16 | 20 | | 17 | 14 | | 18 | 16 | | 19 | 7 | | 20 | 14 | | 21 | 17 | | 22 | 14 | | 23 | 8 | | 24 | 3 | | 25 | 9 | | 26 | 18 | | 27 | 5 | | 28 | 7 | | 29 | 12 | | 30 | 10 | | 31 | 20 | | 32 | 9 | | 33 | 6 | | 34 | 12 | | 35 | 21 | | 36 | 2 | | 37 | 20 | | 38 | 10 | | 39 | 14 | | 40 | 6 | | 41 | 4 | | 42 | 7 | | 43 | 30 | | 44 | 17 | | 45 | 3 | | 46 | 24 | | 47 | 13 | | 48 | 17 | | 49 | 10 |
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| 64.73% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.3953488372093023 | | totalSentences | 86 | | uniqueOpeners | 34 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 77 | | matches | | 0 | "Instead, they skidded around a" | | 1 | "Somewhere in this mess, her" | | 2 | "Suddenly, the trench coat turned" |
| | ratio | 0.039 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 77 | | matches | | 0 | "She kept her gaze locked" | | 1 | "she called out, voice low" | | 2 | "She glanced up." | | 3 | "She recognized the urgency." | | 4 | "She could feel the atmosphere" | | 5 | "She knew the risks—off—duty did" | | 6 | "he said, voice low, eyes" | | 7 | "he added, backing off into" | | 8 | "Her mind raced." | | 9 | "Her eyes picked out the" | | 10 | "She pulled out the bone" | | 11 | "Her breathing matched the quick" | | 12 | "She twisted sharply, breaking free." | | 13 | "He pushed a folded note" | | 14 | "Her heartbeat pulsed in her" | | 15 | "she shot back, voice sharp" | | 16 | "She felt the weight of" | | 17 | "Her eyes hardened." | | 18 | "Her grip tightened on the" | | 19 | "she whispered, and stepped forward" |
| | ratio | 0.273 | |
| 57.40% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 62 | | totalSentences | 77 | | matches | | 0 | "Detective Harlow Quinn’s boots slapped" | | 1 | "The city at night had" | | 2 | "She kept her gaze locked" | | 3 | "she called out, voice low" | | 4 | "The suspect didn’t look back." | | 5 | "Quinn hesitated on the threshold—her" | | 6 | "The place stank of wet" | | 7 | "She glanced up." | | 8 | "The street above died in" | | 9 | "A faint murmur echoed from" | | 10 | "She recognized the urgency." | | 11 | "The chase was far from" | | 12 | "Quinn tightened her jacket against" | | 13 | "Each step took her deeper" | | 14 | "The air hit her heavier" | | 15 | "She could feel the atmosphere" | | 16 | "The faint glow pulsed, tempting" | | 17 | "This was the Veil Market," | | 18 | "A place that moved every" | | 19 | "Dealers of forbidden charms and" |
| | ratio | 0.805 | |
| 64.94% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 77 | | matches | | 0 | "If she didn’t follow, the" |
| | ratio | 0.013 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 5 | | matches | | 0 | "The city at night had a grit all its own in the rain—a slick sheen on cobblestones, neon washing over wet surfaces, shadows that moved just out of reach." | | 1 | "She kept her gaze locked on the figure darting ahead, a silhouette hunched against the storm’s bite, weaving through narrow alleys like a rat seeking cover." | | 2 | "A place that moved every full moon, tucked away in forgotten underground tunnels and abandoned Tube stations." | | 3 | "Tomás exhaled, gaze drifting to the chaotic stalls piled with herbs that shimmered unnaturally, vials filled with sloshing iridescent liquid, and talismans that…" | | 4 | "Beyond the curtain, the air grew colder, tighter, thick with the scent of soot and something acrid as if burnt magic clung to the stone walls." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 3 | | matches | | 0 | "she called out, voice low but sharp, cutting through the pounding rain" | | 1 | "he said, voice low, eyes flicking towards the tunnel beyond" | | 2 | "she shot back, voice sharp as steel" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 3 | | fancyTags | | 0 | "she called out (call out)" | | 1 | "he added (add)" | | 2 | "she whispered (whisper)" |
| | dialogueSentences | 15 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.6 | | effectiveRatio | 0.4 | |