| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 91.02% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1114 | | 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) | |
| 46.14% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1114 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "echoing" | | 1 | "weight" | | 2 | "rhythmic" | | 3 | "symphony" | | 4 | "velvet" | | 5 | "measured" | | 6 | "chaotic" | | 7 | "shimmered" | | 8 | "intensity" | | 9 | "cacophony" | | 10 | "electric" | | 11 | "scanning" |
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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 | 68 | | matches | (empty) | |
| 58.82% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 1 | | narrationSentences | 68 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 68 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1112 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 1112 | | uniqueNames | 16 | | maxNameDensity | 0.63 | | worstName | "Tomás" | | maxWindowNameDensity | 1 | | worstWindowName | "Tomás" | | discoveredNames | | Quinn | 1 | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Herrera | 2 | | Tomás | 7 | | London | 1 | | Underground | 1 | | Veil | 1 | | Market | 2 | | Saint | 1 | | Christopher | 1 | | Morris | 1 | | Metropolitan | 1 | | Police | 1 | | Harlow | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Herrera" | | 4 | "Tomás" | | 5 | "Market" | | 6 | "Saint" | | 7 | "Christopher" | | 8 | "Morris" | | 9 | "Police" | | 10 | "Harlow" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 70.63% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like a fracture in reality, a tear" | | 1 | "felt like fever, a dry, suffocating pre" |
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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 | 1112 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 68 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 21 | | mean | 52.95 | | std | 29.82 | | cv | 0.563 | | sampleLengths | | 0 | 82 | | 1 | 66 | | 2 | 66 | | 3 | 37 | | 4 | 14 | | 5 | 79 | | 6 | 81 | | 7 | 14 | | 8 | 86 | | 9 | 70 | | 10 | 19 | | 11 | 69 | | 12 | 82 | | 13 | 42 | | 14 | 8 | | 15 | 85 | | 16 | 53 | | 17 | 8 | | 18 | 98 | | 19 | 42 | | 20 | 11 |
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| 94.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 68 | | matches | | 0 | "was muffled" | | 1 | "being rendered" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 179 | | matches | | 0 | "was stepping" | | 1 | "was heading" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 3 | | flaggedSentences | 5 | | totalSentences | 68 | | ratio | 0.074 | | matches | | 0 | "Tomás Herrera—the paramedic who knew too much, the man who vanished into corners of the city that didn't appear on any ordnance survey." | | 1 | "He didn't look back; he vaulted a chain-link fence shielding the entrance to an old, decommissioned ventilation shaft." | | 2 | "Flickering bioluminescent fungi lined the tunnel walls, casting a sickly violet glow over stalls piled high with curiosities that defied physics—bottles containing trapped lightning, daggers forged from solidified ash, and jars of humming teeth." | | 3 | "They didn't breathe; they merely existed, statues carved from nightmares." | | 4 | "It wasn't just a location; it was a living, breathing parasite buried beneath the city." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1119 | | adjectiveStacks | 1 | | stackExamples | | 0 | "heavy, moth-eaten velvet." |
| | adverbCount | 25 | | adverbRatio | 0.022341376228775692 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.008936550491510277 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 68 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 68 | | mean | 16.35 | | std | 7.58 | | cv | 0.464 | | sampleLengths | | 0 | 19 | | 1 | 15 | | 2 | 25 | | 3 | 23 | | 4 | 17 | | 5 | 14 | | 6 | 18 | | 7 | 3 | | 8 | 14 | | 9 | 12 | | 10 | 20 | | 11 | 7 | | 12 | 27 | | 13 | 12 | | 14 | 25 | | 15 | 7 | | 16 | 7 | | 17 | 12 | | 18 | 9 | | 19 | 5 | | 20 | 34 | | 21 | 19 | | 22 | 9 | | 23 | 11 | | 24 | 16 | | 25 | 13 | | 26 | 32 | | 27 | 14 | | 28 | 12 | | 29 | 10 | | 30 | 18 | | 31 | 10 | | 32 | 21 | | 33 | 15 | | 34 | 12 | | 35 | 28 | | 36 | 30 | | 37 | 19 | | 38 | 14 | | 39 | 21 | | 40 | 15 | | 41 | 3 | | 42 | 16 | | 43 | 13 | | 44 | 10 | | 45 | 11 | | 46 | 24 | | 47 | 24 | | 48 | 12 | | 49 | 30 |
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| 48.04% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.36764705882352944 | | totalSentences | 68 | | uniqueOpeners | 25 | |
| 99.50% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 67 | | matches | | 0 | "Somewhere below, the rhythmic hum" | | 1 | "Just one step, and there’s" |
| | ratio | 0.03 | |
| 11.04% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 67 | | matches | | 0 | "Her hand drifted to her" | | 1 | "She rounded the corner, heels" | | 2 | "He didn't look back; he" | | 3 | "He didn't climb." | | 4 | "He flowed over it, a" | | 5 | "She sprinted, her lungs burning," | | 6 | "She slammed a palm against" | | 7 | "I can smell the rot" | | 8 | "She spotted Tomás near a" | | 9 | "He looked entirely at ease," | | 10 | "He held a bone token" | | 11 | "I’m not letting you walk" | | 12 | "She tracked his movement, her" | | 13 | "They didn't breathe; they merely" | | 14 | "It wasn't just a location;" | | 15 | "She looked down at her" | | 16 | "She remembered DS Morris, the" | | 17 | "You think you can hide" | | 18 | "She vaulted the railing, dropping" | | 19 | "It hissed, a sound like" |
| | ratio | 0.522 | |
| 42.09% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 67 | | matches | | 0 | "Harlow Quinn’s boots slapped against" | | 1 | "Rain lashed at her face," | | 2 | "Tomás Herrera—the paramedic who knew" | | 3 | "Her hand drifted to her" | | 4 | "She rounded the corner, heels" | | 5 | "He didn't look back; he" | | 6 | "He didn't climb." | | 7 | "He flowed over it, a" | | 8 | "She sprinted, her lungs burning," | | 9 | "She slammed a palm against" | | 10 | "Dirt and rotted leaves cushioned" | | 11 | "The trail led deep, passing" | | 12 | "I can smell the rot" | | 13 | "The stairs ended abruptly on" | | 14 | "This was not the infrastructure" | | 15 | "Harlow gripped the metal railing," | | 16 | "She spotted Tomás near a" | | 17 | "He looked entirely at ease," | | 18 | "He held a bone token" | | 19 | "The paramedic, the man who" |
| | ratio | 0.836 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 67 | | matches | | 0 | "If she followed Tomás into" | | 1 | "If she stepped through, the" |
| | ratio | 0.03 | |
| 12.99% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 10 | | matches | | 0 | "Ahead, a figure turned the corner near the green neon buzz of The Raven's Nest, moving with a fluid, unnatural grace that defied the weather." | | 1 | "Flickering bioluminescent fungi lined the tunnel walls, casting a sickly violet glow over stalls piled high with curiosities that defied physics—bottles contain…" | | 2 | "Hooded figures milled through the crowd, their voices a discordant symphony of tongues that weren't meant for human ears." | | 3 | "He looked entirely at ease, checking his Saint Christopher medallion as if it were a shield." | | 4 | "The paramedic, the man who had supposedly lost his license for healing the impossible, stood at the threshold of the deep market, ready to disappear into the ch…" | | 5 | "If she followed Tomás into the thick of the market, she was stepping off the edge of the police report, into the territory that ate decoys and swallowed evidenc…" | | 6 | "She saw Tomás’s back through the shimmering gap, his silhouette flickering as if he were being rendered in low resolution." | | 7 | "The heat radiating from the rift felt like fever, a dry, suffocating pressure that crowded her chest." | | 8 | "The noise escalated, a cacophony of whispers and snapping gears that gnawed at her composure." | | 9 | "The environment screamed of things not meant for the city above, a sensory overload of color and sound that defied mapping." |
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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 | |