| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.29% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1148 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1148 | | totalAiIsms | 34 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | | | 23 | | | 24 | | | 25 | | | 26 | | | 27 | | | 28 | | word | "the last thing" | | count | 1 |
| | 29 | | | 30 | |
| | highlights | | 0 | "fleeting" | | 1 | "silence" | | 2 | "eyebrow" | | 3 | "mechanical" | | 4 | "echoes" | | 5 | "footsteps" | | 6 | "quickened" | | 7 | "familiar" | | 8 | "sinister" | | 9 | "clandestine" | | 10 | "cacophony" | | 11 | "etched" | | 12 | "glinting" | | 13 | "tinged" | | 14 | "anticipating" | | 15 | "could feel" | | 16 | "tension" | | 17 | "sense of" | | 18 | "pulse" | | 19 | "pounding" | | 20 | "stomach" | | 21 | "flicker" | | 22 | "echoed" | | 23 | "intricate" | | 24 | "calculating" | | 25 | "flickered" | | 26 | "comforting" | | 27 | "amidst" | | 28 | "the last thing" | | 29 | "steeled" | | 30 | "determined" |
| |
| 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 | 87 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 87 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 96 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1137 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 97.22% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 1042 | | uniqueNames | 14 | | maxNameDensity | 1.06 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | Soho | 1 | | London | 1 | | Raven | 1 | | Nest | 1 | | Silas | 1 | | Veil | 2 | | Market | 3 | | Tube | 1 | | Camden | 1 | | Harlow | 11 | | Saint | 1 | | Christopher | 1 | | Morris | 1 | | Quinn | 1 |
| | persons | | 0 | "Raven" | | 1 | "Silas" | | 2 | "Camden" | | 3 | "Harlow" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Morris" | | 7 | "Quinn" |
| | places | | | globalScore | 0.972 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | 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 | 1137 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 96 | | matches | (empty) | |
| 99.24% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 34.45 | | std | 17.14 | | cv | 0.497 | | sampleLengths | | 0 | 57 | | 1 | 33 | | 2 | 52 | | 3 | 12 | | 4 | 13 | | 5 | 35 | | 6 | 49 | | 7 | 57 | | 8 | 32 | | 9 | 50 | | 10 | 40 | | 11 | 38 | | 12 | 36 | | 13 | 42 | | 14 | 12 | | 15 | 24 | | 16 | 44 | | 17 | 72 | | 18 | 8 | | 19 | 18 | | 20 | 14 | | 21 | 39 | | 22 | 40 | | 23 | 10 | | 24 | 29 | | 25 | 22 | | 26 | 22 | | 27 | 47 | | 28 | 35 | | 29 | 2 | | 30 | 61 | | 31 | 37 | | 32 | 55 |
| |
| 97.20% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 87 | | matches | | 0 | "was involved" | | 1 | "was thrown" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 183 | | matches | | 0 | "was leading" | | 1 | "wasn’t losing" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 1 | | flaggedSentences | 8 | | totalSentences | 96 | | ratio | 0.083 | | matches | | 0 | "As she rounded a corner, the flash of a distinctive green neon sign sliced through the darkness—The Raven's Nest." | | 1 | "And that's when she saw it—a bone token lying on the damp ground." | | 2 | "Eyes followed her every move; the regulars could smell the outsider on her." | | 3 | "\"Who are you? Why lead me here?\" Without waiting, she glanced around the room, noticing a weathered leather bag in the corner, partially open and revealing odd trinkets—a mix of occult items and..." | | 4 | "Then, an overwhelming sense of déjà vu swept over her—her mind briefly flickering to DS Morris’s last moments." | | 5 | "Harlow’s eyes bore into his, and for a fleeting second, she thought she saw a flicker of something—fear, perhaps, or maybe regret." | | 6 | "But then, something flickered in his eyes—a decision made." | | 7 | "She may have lost the suspect, but she had gained something far more valuable—a lead." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 164 | | adjectiveStacks | 1 | | stackExamples | | 0 | "narrow, rain-slicked alleys," |
| | adverbCount | 5 | | adverbRatio | 0.03048780487804878 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 96 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 96 | | mean | 11.84 | | std | 5.97 | | cv | 0.504 | | sampleLengths | | 0 | 18 | | 1 | 20 | | 2 | 19 | | 3 | 11 | | 4 | 22 | | 5 | 19 | | 6 | 2 | | 7 | 14 | | 8 | 17 | | 9 | 7 | | 10 | 5 | | 11 | 10 | | 12 | 3 | | 13 | 14 | | 14 | 21 | | 15 | 10 | | 16 | 15 | | 17 | 15 | | 18 | 9 | | 19 | 15 | | 20 | 13 | | 21 | 7 | | 22 | 15 | | 23 | 7 | | 24 | 15 | | 25 | 3 | | 26 | 14 | | 27 | 20 | | 28 | 13 | | 29 | 17 | | 30 | 22 | | 31 | 18 | | 32 | 17 | | 33 | 10 | | 34 | 11 | | 35 | 16 | | 36 | 13 | | 37 | 7 | | 38 | 17 | | 39 | 11 | | 40 | 14 | | 41 | 12 | | 42 | 15 | | 43 | 9 | | 44 | 5 | | 45 | 9 | | 46 | 12 | | 47 | 18 | | 48 | 22 | | 49 | 15 |
| |
| 70.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.4479166666666667 | | totalSentences | 96 | | uniqueOpeners | 43 | |
| 81.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 82 | | matches | | 0 | "Somewhere in the crowd, she" | | 1 | "Then, an overwhelming sense of" |
| | ratio | 0.024 | |
| 73.66% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 82 | | matches | | 0 | "Her eyes, sharp and penetrating," | | 1 | "she muttered, jawline clenched in" | | 2 | "Her military precision and 18" | | 3 | "It seemed every step led" | | 4 | "She pushed past the dimly" | | 5 | "She barely spared a glance" | | 6 | "He raised an eyebrow, his" | | 7 | "She could hear the echoes" | | 8 | "Her breath quickened, the familiar" | | 9 | "She hesitated momentarily at the" | | 10 | "She bent down, picking it" | | 11 | "She tightened her grip on" | | 12 | "She ignored the cacophony of" | | 13 | "He slipped through a side" | | 14 | "She watched the man's movements," | | 15 | "She sidestepped, her reflexes honed" | | 16 | "She seized the opportunity, grabbing" | | 17 | "He tried to pull away," | | 18 | "she rasped, tightening her grip" | | 19 | "She could feel the tension" |
| | ratio | 0.366 | |
| 57.56% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 82 | | matches | | 0 | "Harlow splashed through puddles, the" | | 1 | "Her eyes, sharp and penetrating," | | 2 | "The suspect, a lanky figure" | | 3 | "she muttered, jawline clenched in" | | 4 | "Her military precision and 18" | | 5 | "It seemed every step led" | | 6 | "She pushed past the dimly" | | 7 | "She barely spared a glance" | | 8 | "He raised an eyebrow, his" | | 9 | "Harlow disappeared through the hidden" | | 10 | "The passage led her into" | | 11 | "She could hear the echoes" | | 12 | "Her breath quickened, the familiar" | | 13 | "This chase had transformed from" | | 14 | "She hesitated momentarily at the" | | 15 | "Someone's entry ticket to The" | | 16 | "She bent down, picking it" | | 17 | "The suspect was leading her" | | 18 | "The abandoned Tube station beneath" | | 19 | "The Veil Market." |
| | ratio | 0.805 | |
| 60.98% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 82 | | matches | | 0 | "Before she could react, the" |
| | ratio | 0.012 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 1 | | matches | | 0 | "As she struggled to rise, the last thing she saw was his silhouette slipping into the darkness, the secrets he harboured vanishing with him." |
| |
| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "Harlow responded, her voice steady, reflecting her years of experience" |
| |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 6 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "the suspect hissed (hiss)" | | 2 | "Harlow responded (respond)" | | 3 | "he growled (growl)" | | 4 | "Harlow demanded (demand)" | | 5 | "he choked (choke)" |
| | dialogueSentences | 16 | | tagDensity | 0.375 | | leniency | 0.75 | | rawRatio | 1 | | effectiveRatio | 0.75 | |