| 73.68% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 28 | | adverbTagCount | 6 | | adverbTags | | 0 | "She smiled thinly [thinly]" | | 1 | "She pulled back [back]" | | 2 | "He gestured vaguely [vaguely]" | | 3 | "Marcus said finally [finally]" | | 4 | "She nodded slowly [slowly]" | | 5 | "Marcus asked finally [finally]" |
| | dialogueSentences | 95 | | tagDensity | 0.295 | | leniency | 0.589 | | rawRatio | 0.214 | | effectiveRatio | 0.126 | |
| 63.01% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1487 | | totalAiIsmAdverbs | 11 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "very" | | 3 | "sharply" | | 4 | "suddenly" | | 5 | "really" |
| |
| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 49.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1487 | | totalAiIsms | 15 | | found | | 0 | | | 1 | | word | "down her spine" | | count | 1 |
| | 2 | | | 3 | | | 4 | | word | "carried the weight" | | count | 1 |
| | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | |
| | highlights | | 0 | "sanctuary" | | 1 | "down her spine" | | 2 | "gleaming" | | 3 | "weight" | | 4 | "carried the weight" | | 5 | "tracing" | | 6 | "familiar" | | 7 | "glistening" | | 8 | "footsteps" | | 9 | "traced" | | 10 | "unspoken" | | 11 | "silence" |
| |
| 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 | 1 | | narrationSentences | 72 | | matches | | |
| 83.33% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 72 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 137 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1494 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 55.91% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 744 | | uniqueNames | 16 | | maxNameDensity | 1.88 | | worstName | "Marcus" | | maxWindowNameDensity | 3 | | worstWindowName | "Marcus" | | discoveredNames | | Raven | 1 | | Nest | 1 | | London | 1 | | Soho | 1 | | Cardiff | 1 | | Evan | 2 | | Silas | 8 | | Prague | 1 | | Whitley | 1 | | Aurora | 10 | | Marcus | 14 | | Gone | 1 | | Heat | 1 | | Golden | 1 | | Empress | 1 | | Silence | 2 |
| | persons | | 0 | "Raven" | | 1 | "Evan" | | 2 | "Silas" | | 3 | "Whitley" | | 4 | "Aurora" | | 5 | "Marcus" | | 6 | "Silence" |
| | places | | 0 | "London" | | 1 | "Soho" | | 2 | "Cardiff" | | 3 | "Prague" |
| | globalScore | 0.559 | | windowScore | 0.667 | |
| 57.41% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | glossingSentenceCount | 2 | | matches | | 0 | "appeared behind the bar, cloth in hand, polishing an already gleaming glass" | | 1 | "not quite meeting her eyes" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1494 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 137 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 91 | | mean | 16.42 | | std | 11.83 | | cv | 0.72 | | sampleLengths | | 0 | 56 | | 1 | 43 | | 2 | 31 | | 3 | 11 | | 4 | 31 | | 5 | 19 | | 6 | 30 | | 7 | 3 | | 8 | 23 | | 9 | 1 | | 10 | 34 | | 11 | 20 | | 12 | 13 | | 13 | 39 | | 14 | 31 | | 15 | 11 | | 16 | 27 | | 17 | 27 | | 18 | 20 | | 19 | 9 | | 20 | 20 | | 21 | 24 | | 22 | 13 | | 23 | 9 | | 24 | 25 | | 25 | 31 | | 26 | 13 | | 27 | 6 | | 28 | 12 | | 29 | 13 | | 30 | 1 | | 31 | 25 | | 32 | 15 | | 33 | 21 | | 34 | 14 | | 35 | 20 | | 36 | 16 | | 37 | 2 | | 38 | 16 | | 39 | 12 | | 40 | 16 | | 41 | 5 | | 42 | 2 | | 43 | 10 | | 44 | 8 | | 45 | 12 | | 46 | 1 | | 47 | 5 | | 48 | 26 | | 49 | 2 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 72 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 138 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 137 | | ratio | 0.073 | | matches | | 0 | "Friday night, and the bar hummed with the usual crowd – city professionals unwinding after a long week, locals seeking refuge from London's persistent drizzle, and the occasional tourist who'd stumbled upon this hidden gem in Soho by happy accident." | | 1 | "The thought of Evan still sent a cold shiver down her spine – his messages, his \"apologies,\" his threats." | | 2 | "He leaned slightly against the bar, taking weight off his left leg – the old Prague injury acting up again with the damp weather." | | 3 | "Aurora didn't look up, tracing the rim of her glass with her finger, until—" | | 4 | "Familiar, yet altered somehow – deeper, more confident than she remembered." | | 5 | "Marcus Whitley – her university debate partner, once her closest friend, now practically a stranger." | | 6 | "Aurora's finger traced the small crescent-shaped scar on her left wrist – a nervous habit." | | 7 | "The image of Evan flashed through her mind – his smile, his rage, the sound of breaking glass." | | 8 | "She studied him – the designer watch, the manicured nails, the careful distance in his eyes despite his intimate questions." | | 9 | "Silence fell again, but different now – reflective rather than tense." |
| |
| 77.82% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 737 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 40 | | adverbRatio | 0.054274084124830396 | | lyAdverbCount | 18 | | lyAdverbRatio | 0.024423337856173677 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 137 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 137 | | mean | 10.91 | | std | 7.58 | | cv | 0.695 | | sampleLengths | | 0 | 16 | | 1 | 40 | | 2 | 13 | | 3 | 19 | | 4 | 11 | | 5 | 17 | | 6 | 14 | | 7 | 7 | | 8 | 4 | | 9 | 7 | | 10 | 24 | | 11 | 15 | | 12 | 4 | | 13 | 16 | | 14 | 14 | | 15 | 3 | | 16 | 5 | | 17 | 11 | | 18 | 7 | | 19 | 1 | | 20 | 13 | | 21 | 15 | | 22 | 6 | | 23 | 20 | | 24 | 13 | | 25 | 10 | | 26 | 13 | | 27 | 16 | | 28 | 21 | | 29 | 10 | | 30 | 9 | | 31 | 2 | | 32 | 27 | | 33 | 12 | | 34 | 15 | | 35 | 5 | | 36 | 15 | | 37 | 9 | | 38 | 20 | | 39 | 15 | | 40 | 9 | | 41 | 13 | | 42 | 9 | | 43 | 10 | | 44 | 15 | | 45 | 31 | | 46 | 8 | | 47 | 5 | | 48 | 6 | | 49 | 10 |
| |
| 68.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.4233576642335766 | | totalSentences | 137 | | uniqueOpeners | 58 | |
| 47.62% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 70 | | matches | | 0 | "Of course he'd spotted her" |
| | ratio | 0.014 | |
| 48.57% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 70 | | matches | | 0 | "She took another sip, letting" | | 1 | "She smiled thinly" | | 2 | "He leaned slightly against the" | | 3 | "His voice carried the weight" | | 4 | "She turned slowly, disbelief washing" | | 5 | "He stood just inside the" | | 6 | "His face broke into a" | | 7 | "She pulled back, studying him" | | 8 | "He gestured vaguely around the" | | 9 | "She gestured to the stool" | | 10 | "She took a sip of" | | 11 | "He loosened his tie slightly" | | 12 | "She nodded at his platinum" | | 13 | "He trailed off, perhaps remembering" | | 14 | "she said, meaning it despite" | | 15 | "She drained her glass" | | 16 | "She studied him – the" | | 17 | "She signaled to Silas for" | | 18 | "Her voice softened" | | 19 | "She accepted the fresh whiskey" |
| | ratio | 0.429 | |
| 2.86% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 70 | | matches | | 0 | "Aurora nursed her whiskey, watching" | | 1 | "Friday night, and the bar" | | 2 | "The thought of Evan still" | | 3 | "She took another sip, letting" | | 4 | "Silas appeared behind the bar," | | 5 | "The silver signet ring on" | | 6 | "She smiled thinly" | | 7 | "Silas nodded, understanding in his" | | 8 | "He leaned slightly against the" | | 9 | "His voice carried the weight" | | 10 | "The door swung open, letting" | | 11 | "Aurora didn't look up, tracing" | | 12 | "The voice froze her mid-motion." | | 13 | "She turned slowly, disbelief washing" | | 14 | "He stood just inside the" | | 15 | "Marcus Whitley – her university" | | 16 | "His face broke into a" | | 17 | "Aurora stood, accepting the hug" | | 18 | "She pulled back, studying him" | | 19 | "This Marcus was polished, tailored," |
| | ratio | 0.914 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 70 | | matches | (empty) | | ratio | 0 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 2 | | matches | | 0 | "Friday night, and the bar hummed with the usual crowd – city professionals unwinding after a long week, locals seeking refuge from London's persistent drizzle, …" | | 1 | "Marcus slid onto the seat, ordering a scotch from Silas, who introduced himself with a firm handshake and searching look before moving away to give them space." |
| |
| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 28 | | uselessAdditionCount | 2 | | matches | | 0 | "His face broke, arms opening for an embrace" | | 1 | "Marcus swirled, not quite meeting her eyes" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 95 | | tagDensity | 0.053 | | leniency | 0.105 | | rawRatio | 0.2 | | effectiveRatio | 0.021 | |