| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 2 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.41% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1317 | | 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) | |
| 54.44% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1317 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "glistening" | | 1 | "rhythmic" | | 2 | "efficient" | | 3 | "standard" | | 4 | "warmth" | | 5 | "echoed" | | 6 | "constructed" | | 7 | "silk" | | 8 | "shimmered" | | 9 | "uncanny" | | 10 | "gleaming" | | 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 | 76 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 76 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 77 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 58 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1309 | | ratio | 0.001 | | matches | | |
| 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 | 41 | | wordCount | 1303 | | uniqueNames | 19 | | maxNameDensity | 1 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | London | 3 | | Harlow | 1 | | Quinn | 13 | | Herrera | 6 | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Camden | 1 | | Glock | 1 | | Saint | 1 | | Christopher | 1 | | Tube | 2 | | Morris | 2 | | Underground | 1 | | United | 1 | | Kingdom | 1 | | Veil | 1 | | Market | 1 | | Tomás | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Raven" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Morris" | | 7 | "Tomás" |
| | places | | 0 | "London" | | 1 | "Soho" | | 2 | "Camden" | | 3 | "United" | | 4 | "Kingdom" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like a crowded concourse, but twis" |
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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 | 1309 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 77 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 42.23 | | std | 26.94 | | cv | 0.638 | | sampleLengths | | 0 | 43 | | 1 | 72 | | 2 | 103 | | 3 | 21 | | 4 | 37 | | 5 | 17 | | 6 | 60 | | 7 | 16 | | 8 | 71 | | 9 | 22 | | 10 | 29 | | 11 | 76 | | 12 | 12 | | 13 | 5 | | 14 | 70 | | 15 | 29 | | 16 | 58 | | 17 | 12 | | 18 | 43 | | 19 | 46 | | 20 | 56 | | 21 | 35 | | 22 | 30 | | 23 | 104 | | 24 | 34 | | 25 | 3 | | 26 | 27 | | 27 | 84 | | 28 | 42 | | 29 | 10 | | 30 | 42 |
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| 77.56% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 76 | | matches | | 0 | "been made" | | 1 | "was lost" | | 2 | "was soaked" | | 3 | "been unclasped" | | 4 | "were piled" | | 5 | "being sold" | | 6 | "was obscured" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 202 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 1 | | flaggedSentences | 8 | | totalSentences | 77 | | ratio | 0.104 | | matches | | 0 | "Beneath a flickering streetlight, his profile caught the glare—olive skin glistening with sweat and rain, short curly dark brown hair plastered flat against his forehead." | | 1 | "She checked her left wrist—the worn leather watch strap was soaked, the second hand ticking past 1:22 AM." | | 2 | "A flash of silver caught the ambient light from the street—a Saint Christopher medallion swinging violently on a chain around his neck." | | 3 | "The lock wasn't broken; it had been unclasped and hung loosely from the latch." | | 4 | "It was an entrance to one of London's ghost stations—an abandoned Tube stop, decommissioned decades ago and wiped from the official maps." | | 5 | "Footprints—wet, muddy, and frantic—tracked ahead of her down the center of the corridor." | | 6 | "It sounded like a crowded concourse, but twisted—a murmur of dozens of voices speaking in heavy, overlapping cadences, punctuated by the sharp chime of metal on brass." | | 7 | "Figures moved between the stalls—some wrapped in heavy traveling cloaks, others dressed in tailored suits, and a few whose silhouettes moved with a subtle, uncanny grace that made Quinn's hand tighten on her grip." |
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| 70.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1331 | | adjectiveStacks | 5 | | stackExamples | | 0 | "erratic, head-long desperation" | | 1 | "narrow, shadow-drenched alleyway" | | 2 | "illuminating ancient white subway" | | 3 | "strange, chalk-drawn symbols" | | 4 | "strange, green-tinted flames," |
| | adverbCount | 26 | | adverbRatio | 0.019534184823441023 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.010518407212622089 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 77 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 77 | | mean | 17 | | std | 9.08 | | cv | 0.534 | | sampleLengths | | 0 | 25 | | 1 | 18 | | 2 | 9 | | 3 | 26 | | 4 | 12 | | 5 | 25 | | 6 | 14 | | 7 | 27 | | 8 | 9 | | 9 | 26 | | 10 | 27 | | 11 | 21 | | 12 | 19 | | 13 | 18 | | 14 | 12 | | 15 | 5 | | 16 | 3 | | 17 | 12 | | 18 | 23 | | 19 | 22 | | 20 | 16 | | 21 | 10 | | 22 | 15 | | 23 | 18 | | 24 | 14 | | 25 | 14 | | 26 | 22 | | 27 | 15 | | 28 | 14 | | 29 | 27 | | 30 | 11 | | 31 | 13 | | 32 | 25 | | 33 | 12 | | 34 | 5 | | 35 | 3 | | 36 | 7 | | 37 | 29 | | 38 | 2 | | 39 | 2 | | 40 | 3 | | 41 | 24 | | 42 | 29 | | 43 | 6 | | 44 | 20 | | 45 | 32 | | 46 | 12 | | 47 | 8 | | 48 | 17 | | 49 | 18 |
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| 71.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.4805194805194805 | | totalSentences | 77 | | uniqueOpeners | 37 | |
| 90.09% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 74 | | matches | | 0 | "Then she remembered DS Morris." | | 1 | "Just a room smelling of" |
| | ratio | 0.027 | |
| 68.65% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 74 | | matches | | 0 | "He sprinted with the erratic," | | 1 | "She kept her brown eyes" | | 2 | "She had picked up his" | | 3 | "He had thought he was" | | 4 | "She checked her left wrist—the" | | 5 | "she barked, her voice cutting" | | 6 | "He didn't stop." | | 7 | "He vaulted over a overturned" | | 8 | "He hit the damp brick" | | 9 | "It was an entrance to" | | 10 | "She stood at five-foot-nine, her" | | 11 | "You didn't march down a" | | 12 | "She reached for her radio," | | 13 | "She unclipped her heavy tactical" | | 14 | "She unbuttoned her coat, unholstered" | | 15 | "It smelled of wet earth," | | 16 | "Her leather soles slapped quietly" | | 17 | "She followed the trail, her" | | 18 | "It sounded like a crowded" | | 19 | "She took a slow, deep" |
| | ratio | 0.378 | |
| 81.62% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 74 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn ignored the" | | 2 | "Tomás Herrera was fast, but" | | 3 | "He sprinted with the erratic," | | 4 | "Every few paces, his boots" | | 5 | "Quinn adjusted her pace, her" | | 6 | "She kept her brown eyes" | | 7 | "She had picked up his" | | 8 | "He had thought he was" | | 9 | "Herrera cut hard to the" | | 10 | "Quinn closed the distance, her" | | 11 | "She checked her left wrist—the" | | 12 | "she barked, her voice cutting" | | 13 | "He didn't stop." | | 14 | "He vaulted over a overturned" | | 15 | "A flash of silver caught" | | 16 | "He hit the damp brick" | | 17 | "Quinn reached the bin, stepped" | | 18 | "The alley ended in a" | | 19 | "The lock wasn't broken; it" |
| | ratio | 0.757 | |
| 67.57% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 74 | | matches | | 0 | "If she waited for backup," |
| | ratio | 0.014 | |
| 72.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 61 | | technicalSentenceCount | 6 | | matches | | 0 | "He sprinted with the erratic, head-long desperation of a man who knew he’d been made, his dark green jacket flapping behind him like a broken wing." | | 1 | "You didn't march down a dark hole after a suspect with off-the-books medical skills and ties to people who didn't exist on any civil register." | | 2 | "The light sliced through the damp fog hanging in the stairwell, illuminating ancient white subway tiles coated in grime and strange, chalk-drawn symbols that ha…" | | 3 | "Stalls constructed from reclaimed timber and heavy silk tapestries were piled high with things that had no business being sold in the United Kingdom: dried bota…" | | 4 | "Figures moved between the stalls—some wrapped in heavy traveling cloaks, others dressed in tailored suits, and a few whose silhouettes moved with a subtle, unca…" | | 5 | "She had heard the name whispered in the dark corners of the precinct by informants who smelled of fear, but seeing it made her blood run cold." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 1 | | matches | | 0 | "she barked, her voice cutting through the hiss of the storm" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 2 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 1 | | effectiveRatio | 1 | |