| 84.62% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 25 | | adverbTagCount | 3 | | adverbTags | | 0 | "he finally said [finally]" | | 1 | "He reached slowly [slowly]" | | 2 | "he said quietly [quietly]" |
| | dialogueSentences | 52 | | tagDensity | 0.481 | | leniency | 0.962 | | rawRatio | 0.12 | | effectiveRatio | 0.115 | |
| 74.89% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1593 | | totalAiIsmAdverbs | 8 | | found | | | highlights | | 0 | "quickly" | | 1 | "suddenly" | | 2 | "cautiously" | | 3 | "slowly" | | 4 | "really" |
| |
| 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) | |
| 62.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1593 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "flickered" | | 1 | "footsteps" | | 2 | "quickened" | | 3 | "cascading" | | 4 | "gloom" | | 5 | "disrupting" | | 6 | "glinting" | | 7 | "flicker" | | 8 | "complex" | | 9 | "newfound" | | 10 | "intensity" | | 11 | "echoing" |
| |
| 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 | 99 | | matches | (empty) | |
| 70.71% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 4 | | narrationSentences | 99 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "appeared to" | | 2 | "begin to" |
| |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 126 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1579 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 71 | | wordCount | 1108 | | uniqueNames | 18 | | maxNameDensity | 2.35 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | London | 2 | | Soho | 1 | | Harlow | 1 | | Quinn | 26 | | Raven | 1 | | Nest | 1 | | Tomás | 3 | | Herrera | 22 | | Morris | 4 | | Camden | 1 | | Line | 1 | | Transport | 1 | | TfL | 1 | | Tube | 1 | | Spanish | 1 | | Saint | 1 | | Christopher | 1 | | Rain | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Morris" | | 5 | "TfL" | | 6 | "Spanish" | | 7 | "Saint" | | 8 | "Christopher" | | 9 | "Rain" |
| | places | | | globalScore | 0.327 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 75 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like a trap, but also like the bre" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.633 | | wordCount | 1579 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 126 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 54 | | mean | 29.24 | | std | 16.98 | | cv | 0.581 | | sampleLengths | | 0 | 66 | | 1 | 56 | | 2 | 10 | | 3 | 57 | | 4 | 41 | | 5 | 4 | | 6 | 55 | | 7 | 49 | | 8 | 47 | | 9 | 57 | | 10 | 50 | | 11 | 53 | | 12 | 23 | | 13 | 16 | | 14 | 23 | | 15 | 20 | | 16 | 9 | | 17 | 19 | | 18 | 12 | | 19 | 21 | | 20 | 11 | | 21 | 13 | | 22 | 45 | | 23 | 45 | | 24 | 16 | | 25 | 19 | | 26 | 30 | | 27 | 15 | | 28 | 30 | | 29 | 28 | | 30 | 17 | | 31 | 3 | | 32 | 25 | | 33 | 11 | | 34 | 23 | | 35 | 14 | | 36 | 24 | | 37 | 37 | | 38 | 39 | | 39 | 3 | | 40 | 52 | | 41 | 38 | | 42 | 31 | | 43 | 34 | | 44 | 17 | | 45 | 35 | | 46 | 60 | | 47 | 25 | | 48 | 11 | | 49 | 53 |
| |
| 98.17% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 99 | | matches | | 0 | "been sealed" | | 1 | "was involved" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 207 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 126 | | ratio | 0.087 | | matches | | 0 | "The tip had come in just after midnight—suspicious activity near The Raven's Nest, a bar she'd been watching for months." | | 1 | "She'd been about to call it a night when she spotted him—Tomás Herrera, leaving through the side door, looking over his shoulder with unmistakable paranoia." | | 2 | "Since Morris disappeared three years ago, Quinn had become obsessed with unexplained cases—disappearances, impossible crimes, witness reports that defied logic." | | 3 | "The file on Herrera was thin but troubling—former paramedic, lost his license under murky circumstances." | | 4 | "The entrance should have been sealed—Transport for London had shuttered it years ago—but Herrera pushed through without hesitation." | | 5 | "But Quinn knew what would happen if she called it in—hours of bureaucracy, warrants denied, evidence mysteriously missing." | | 6 | "The words triggered a memory—the last case she'd worked with Morris." | | 7 | "A flicker of something—not fear, but caution—crossed Herrera's face." | | 8 | "Quinn's rational mind screamed that this was a mistake—following a suspect deeper underground, alone, into unknown territory." | | 9 | "But the memory of Morris's empty desk, the official investigation that went nowhere, the nightmares that had plagued her for three years—they pushed her forward." | | 10 | "Together they moved deeper into the station, away from the rain-soaked world above, toward answers Quinn had sought for three years—and dangers she couldn't begin to imagine." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1125 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.027555555555555555 | | lyAdverbCount | 17 | | lyAdverbRatio | 0.015111111111111112 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 126 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 126 | | mean | 12.53 | | std | 6.63 | | cv | 0.529 | | sampleLengths | | 0 | 14 | | 1 | 20 | | 2 | 12 | | 3 | 20 | | 4 | 6 | | 5 | 5 | | 6 | 20 | | 7 | 25 | | 8 | 10 | | 9 | 20 | | 10 | 11 | | 11 | 26 | | 12 | 20 | | 13 | 9 | | 14 | 12 | | 15 | 4 | | 16 | 7 | | 17 | 9 | | 18 | 15 | | 19 | 4 | | 20 | 20 | | 21 | 8 | | 22 | 23 | | 23 | 18 | | 24 | 15 | | 25 | 11 | | 26 | 21 | | 27 | 4 | | 28 | 17 | | 29 | 18 | | 30 | 4 | | 31 | 14 | | 32 | 11 | | 33 | 22 | | 34 | 17 | | 35 | 18 | | 36 | 17 | | 37 | 18 | | 38 | 7 | | 39 | 7 | | 40 | 9 | | 41 | 10 | | 42 | 6 | | 43 | 16 | | 44 | 7 | | 45 | 6 | | 46 | 14 | | 47 | 9 | | 48 | 6 | | 49 | 13 |
| |
| 66.93% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.42063492063492064 | | totalSentences | 126 | | uniqueOpeners | 53 | |
| 37.45% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 89 | | matches | | 0 | "Nearly three in the morning." |
| | ratio | 0.011 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 89 | | matches | | 0 | "She'd been about to call" | | 1 | "she whispered, the words dissolving" | | 2 | "She'd been tracking members of" | | 3 | "She'd found connections, patterns that" | | 4 | "He turned suddenly, cutting through" | | 5 | "She drew her service weapon," | | 6 | "Her instincts screamed caution." | | 7 | "It had happened before." | | 8 | "She descended the stairs, entering" | | 9 | "Her eyes adjusted to the" | | 10 | "She killed her flashlight and" | | 11 | "She'd suspected an underground operation," | | 12 | "She took a breath, ready" | | 13 | "She flattened herself against the" | | 14 | "he told the woman, who" | | 15 | "he said, his voice surprisingly" | | 16 | "he said, slowly raising his" | | 17 | "he finally said, his voice" | | 18 | "He reached slowly into his" | | 19 | "He withdrew what appeared to" |
| | ratio | 0.258 | |
| 33.03% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 76 | | totalSentences | 89 | | matches | | 0 | "Detective Harlow Quinn pressed her" | | 1 | "Water trickled down her neck," | | 2 | "The tip had come in" | | 3 | "Quinn checked her worn leather" | | 4 | "The green neon sign of" | | 5 | "She'd been about to call" | | 6 | "she whispered, the words dissolving" | | 7 | "Herrera moved quickly despite the" | | 8 | "Quinn followed at a distance," | | 9 | "She'd been tracking members of" | | 10 | "She'd found connections, patterns that" | | 11 | "People like Tomás Herrera." | | 12 | "He turned suddenly, cutting through" | | 13 | "Quinn quickened her pace, careful" | | 14 | "The file on Herrera was" | | 15 | "Something about unauthorized treatments." | | 16 | "The alley opened onto a" | | 17 | "Quinn watched as Herrera checked" | | 18 | "The entrance should have been" | | 19 | "Quinn approached the stairs cautiously," |
| | ratio | 0.854 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 89 | | matches | (empty) | | ratio | 0 | |
| 86.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 4 | | matches | | 0 | "Herrera moved quickly despite the weather, carrying a battered medical bag that hadn't appeared in any of his previous surveillances." | | 1 | "Quinn watched as Herrera checked his surroundings again before descending a set of stairs that led to an abandoned Camden Line station entrance." | | 2 | "Quinn moved deeper into the station, following wet footprints that glistened in the beam of her pocket flashlight." | | 3 | "But the memory of Morris's empty desk, the official investigation that went nowhere, the nightmares that had plagued her for three years—they pushed her forward…" |
| |
| 45.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 25 | | uselessAdditionCount | 4 | | matches | | 0 | "she whispered, the words dissolving in the rain" | | 1 | "he said, his voice surprisingly calm" | | 2 | "he finally said, his voice softer" | | 3 | "Herrera replied, his expression earnest" |
| |
| 34.62% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 6 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "She'd (would)" | | 2 | "Herrera confirmed (confirm)" | | 3 | "Quinn demanded (demand)" | | 4 | "Quinn hissed (hiss)" | | 5 | "he explained (explain)" |
| | dialogueSentences | 52 | | tagDensity | 0.308 | | leniency | 0.615 | | rawRatio | 0.375 | | effectiveRatio | 0.231 | |