| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 42 | | tagDensity | 0.071 | | leniency | 0.143 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 78.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1176 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slowly" | | 1 | "very" | | 2 | "really" | | 3 | "quickly" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 31.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1176 | | totalAiIsms | 16 | | found | | 0 | | | 1 | | word | "practiced ease" | | count | 1 |
| | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | |
| | highlights | | 0 | "navigated" | | 1 | "practiced ease" | | 2 | "predator" | | 3 | "familiar" | | 4 | "flicker" | | 5 | "traced" | | 6 | "weight" | | 7 | "warmth" | | 8 | "sentinels" | | 9 | "silence" | | 10 | "scanning" | | 11 | "intensity" | | 12 | "calculating" | | 13 | "chaotic" | | 14 | "glint" |
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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 | "hung in the air" | | count | 1 |
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| | highlights | | 0 | "knuckles went white" | | 1 | "hung thick in the air" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 52 | | matches | (empty) | |
| 87.91% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 52 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 91 | | 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 | 1176 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 706 | | uniqueNames | 8 | | maxNameDensity | 1.42 | | worstName | "Silas" | | maxWindowNameDensity | 3 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 2 | | Nest | 2 | | London | 1 | | Carter | 1 | | Blackwood | 1 | | Silas | 10 | | Aurora | 5 | | Europe | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Blackwood" | | 4 | "Silas" | | 5 | "Aurora" |
| | places | | | globalScore | 0.792 | | windowScore | 0.667 | |
| 36.36% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | glossingSentenceCount | 2 | | matches | | 0 | "seemed forgotten in the stillness of his posture" | | 1 | "felt like a trap" |
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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 | 1176 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 91 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 55 | | mean | 21.38 | | std | 18.31 | | cv | 0.856 | | sampleLengths | | 0 | 68 | | 1 | 49 | | 2 | 6 | | 3 | 39 | | 4 | 8 | | 5 | 8 | | 6 | 48 | | 7 | 4 | | 8 | 31 | | 9 | 13 | | 10 | 10 | | 11 | 23 | | 12 | 4 | | 13 | 32 | | 14 | 26 | | 15 | 10 | | 16 | 17 | | 17 | 52 | | 18 | 47 | | 19 | 15 | | 20 | 2 | | 21 | 17 | | 22 | 12 | | 23 | 42 | | 24 | 59 | | 25 | 5 | | 26 | 16 | | 27 | 5 | | 28 | 5 | | 29 | 27 | | 30 | 12 | | 31 | 14 | | 32 | 29 | | 33 | 33 | | 34 | 7 | | 35 | 35 | | 36 | 5 | | 37 | 24 | | 38 | 10 | | 39 | 2 | | 40 | 21 | | 41 | 4 | | 42 | 32 | | 43 | 11 | | 44 | 43 | | 45 | 3 | | 46 | 9 | | 47 | 35 | | 48 | 2 | | 49 | 7 |
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| 98.52% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 52 | | matches | | |
| 9.52% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 105 | | matches | | 0 | "were leaning" | | 1 | "wasn't looking" | | 2 | "was scanning" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 91 | | ratio | 0.011 | | matches | | 0 | "He didn't look at her; he looked toward the bar, his eyes calculating the distance between the exit and the back room." |
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| 82.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 712 | | adjectiveStacks | 3 | | stackExamples | | 0 | "hazy, low-ceilinged room" | | 1 | "heavy, brass-bound key" | | 2 | "sharp, dig-in sensation" |
| | adverbCount | 11 | | adverbRatio | 0.01544943820224719 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.004213483146067416 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 91 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 91 | | mean | 12.92 | | std | 8.21 | | cv | 0.636 | | sampleLengths | | 0 | 33 | | 1 | 4 | | 2 | 14 | | 3 | 17 | | 4 | 18 | | 5 | 14 | | 6 | 17 | | 7 | 6 | | 8 | 5 | | 9 | 17 | | 10 | 17 | | 11 | 8 | | 12 | 8 | | 13 | 8 | | 14 | 10 | | 15 | 30 | | 16 | 4 | | 17 | 11 | | 18 | 20 | | 19 | 13 | | 20 | 10 | | 21 | 5 | | 22 | 10 | | 23 | 8 | | 24 | 4 | | 25 | 9 | | 26 | 4 | | 27 | 19 | | 28 | 26 | | 29 | 10 | | 30 | 17 | | 31 | 17 | | 32 | 35 | | 33 | 14 | | 34 | 27 | | 35 | 6 | | 36 | 15 | | 37 | 2 | | 38 | 17 | | 39 | 12 | | 40 | 21 | | 41 | 21 | | 42 | 5 | | 43 | 6 | | 44 | 32 | | 45 | 5 | | 46 | 4 | | 47 | 7 | | 48 | 5 | | 49 | 16 |
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| 43.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.27472527472527475 | | totalSentences | 91 | | uniqueOpeners | 25 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 43.08% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 52 | | matches | | 0 | "She navigated the hazy, low-ceilinged" | | 1 | "She pushed past a cluster" | | 2 | "His grey-streaked auburn hair caught" | | 3 | "He traced the rim of" | | 4 | "She slid into the booth" | | 5 | "Her bright blue eyes tracked" | | 6 | "she said, her voice dropping" | | 7 | "He leaned forward, the movement" | | 8 | "Her knuckles went white." | | 9 | "She laughed, a sharp, jagged" | | 10 | "It was a museum of" | | 11 | "He leaned in closer, his" | | 12 | "It felt cold against the" | | 13 | "She remembered the nights they" | | 14 | "It had been high stakes." | | 15 | "It had been glorious." | | 16 | "She snatched her hand away" | | 17 | "His gaze drifted to the" | | 18 | "He wasn't looking for a" | | 19 | "He was scanning the room" |
| | ratio | 0.442 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 50 | | totalSentences | 52 | | matches | | 0 | "The heavy oak door of" | | 1 | "Aurora Carter didn’t hesitate." | | 2 | "She navigated the hazy, low-ceilinged" | | 3 | "The scent of stale tobacco" | | 4 | "She pushed past a cluster" | | 5 | "A man sat there, nursing" | | 6 | "His grey-streaked auburn hair caught" | | 7 | "Silas Blackwood didn’t look up." | | 8 | "He traced the rim of" | | 9 | "The slight limp that had" | | 10 | "She slid into the booth" | | 11 | "The wood groaned under the" | | 12 | "Her bright blue eyes tracked" | | 13 | "she said, her voice dropping" | | 14 | "Silas turned his glass slowly." | | 15 | "The amber liquid swirled, mirroring" | | 16 | "He leaned forward, the movement" | | 17 | "Aurora’s hand tightened on the" | | 18 | "Her knuckles went white." | | 19 | "She laughed, a sharp, jagged" |
| | ratio | 0.962 | |
| 96.15% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 52 | | matches | | 0 | "Now, it just felt like" |
| | ratio | 0.019 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 7 | | matches | | 0 | "The heavy oak door of The Raven’s Nest swung open, admitting a gust of damp London air and a woman who looked as though she had been carved from shadow and shar…" | | 1 | "Her bright blue eyes tracked the twitch in his jaw, noting the way his hazel irises locked onto the crescent-shaped scar on her wrist before snapping back to he…" | | 2 | "The room was decorated with decaying maps of cities long since rezoned and weathered photographs of people who had probably disappeared before the turn of the m…" | | 3 | "Silas smiled, a thin, mirthless expression that didn't reach his eyes." | | 4 | "The silence stretched, heavy and suffocating, until it felt as though the very walls were leaning in to listen." | | 5 | "The man in the trench coat began to move, pushing aside a group of patrons with a shove that lacked any pretense of apology." | | 6 | "Silas kicked the table, sending his glass shattering against the floorboards." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, her voice dropping an octave" | | 1 | "He leaned, his voice a low, abrasive rumble" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "Silas whispered (whisper)" |
| | dialogueSentences | 42 | | tagDensity | 0.048 | | leniency | 0.095 | | rawRatio | 0.5 | | effectiveRatio | 0.048 | |