| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "Herrera shouted back [back]" |
| | dialogueSentences | 26 | | tagDensity | 0.654 | | leniency | 1 | | rawRatio | 0.059 | | effectiveRatio | 0.059 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1242 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 47.67% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1242 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "weight" | | 1 | "database" | | 2 | "flickered" | | 3 | "echoed" | | 4 | "depths" | | 5 | "chilled" | | 6 | "echo" | | 7 | "rhythmic" | | 8 | "constructed" | | 9 | "dancing" | | 10 | "silence" | | 11 | "standard" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 80 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 80 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 90 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 12 | | totalWords | 1240 | | ratio | 0.01 | | matches | | 0 | "Rules for surviving a pursuit," | | 1 | "Never follow a rabbit into its hole." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 1043 | | uniqueNames | 24 | | maxNameDensity | 1.53 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 16 | | Soho | 2 | | Metropolitan | 1 | | Police | 1 | | London | 2 | | Tomás | 1 | | Herrera | 9 | | Wardour | 1 | | Street | 1 | | Seville-born | 1 | | Raven | 1 | | Nest | 1 | | Spanish | 1 | | Egyptian | 1 | | Morris | 1 | | Victorian | 1 | | Camden | 1 | | Veil | 1 | | Market | 1 | | Tube | 1 | | Saint | 1 | | Christopher | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Police" | | 3 | "Tomás" | | 4 | "Herrera" | | 5 | "Raven" | | 6 | "Nest" | | 7 | "Morris" | | 8 | "Market" | | 9 | "Saint" | | 10 | "Christopher" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Wardour" | | 3 | "Street" | | 4 | "Seville-born" |
| | globalScore | 0.733 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 1 | | matches | | 0 | "flora that seemed to twitch in the draft" |
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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 | 1240 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 90 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 31.79 | | std | 23.14 | | cv | 0.728 | | sampleLengths | | 0 | 74 | | 1 | 14 | | 2 | 33 | | 3 | 97 | | 4 | 22 | | 5 | 12 | | 6 | 79 | | 7 | 9 | | 8 | 25 | | 9 | 10 | | 10 | 44 | | 11 | 59 | | 12 | 60 | | 13 | 15 | | 14 | 4 | | 15 | 74 | | 16 | 16 | | 17 | 64 | | 18 | 6 | | 19 | 53 | | 20 | 21 | | 21 | 21 | | 22 | 65 | | 23 | 34 | | 24 | 22 | | 25 | 16 | | 26 | 32 | | 27 | 33 | | 28 | 30 | | 29 | 25 | | 30 | 25 | | 31 | 21 | | 32 | 12 | | 33 | 8 | | 34 | 36 | | 35 | 14 | | 36 | 12 | | 37 | 27 | | 38 | 16 |
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| 92.11% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 80 | | matches | | 0 | "were choked" | | 1 | "been patterned" | | 2 | "were carved" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 160 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 90 | | ratio | 0.011 | | matches | | 0 | "People—or things that wore the shape of people with slight, unsettling discrepancies—moved between the stalls in a hushed, reverent silence." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 446 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.017937219730941704 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.006726457399103139 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 90 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 90 | | mean | 13.78 | | std | 8.54 | | cv | 0.62 | | sampleLengths | | 0 | 29 | | 1 | 3 | | 2 | 42 | | 3 | 13 | | 4 | 1 | | 5 | 8 | | 6 | 25 | | 7 | 6 | | 8 | 2 | | 9 | 17 | | 10 | 7 | | 11 | 21 | | 12 | 8 | | 13 | 4 | | 14 | 32 | | 15 | 3 | | 16 | 19 | | 17 | 12 | | 18 | 22 | | 19 | 20 | | 20 | 37 | | 21 | 9 | | 22 | 19 | | 23 | 6 | | 24 | 10 | | 25 | 8 | | 26 | 16 | | 27 | 20 | | 28 | 8 | | 29 | 5 | | 30 | 13 | | 31 | 3 | | 32 | 4 | | 33 | 26 | | 34 | 16 | | 35 | 16 | | 36 | 28 | | 37 | 8 | | 38 | 7 | | 39 | 4 | | 40 | 18 | | 41 | 10 | | 42 | 17 | | 43 | 5 | | 44 | 24 | | 45 | 16 | | 46 | 11 | | 47 | 13 | | 48 | 23 | | 49 | 17 |
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| 62.96% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.4111111111111111 | | totalSentences | 90 | | uniqueOpeners | 37 | |
| 43.86% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 76 | | matches | | 0 | "More importantly, she knew his" |
| | ratio | 0.013 | |
| 83.16% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 76 | | matches | | 0 | "She didn’t stop." | | 1 | "She checked the military-style stride" | | 2 | "He shoved past a couple" | | 3 | "Her lungs burned from the" | | 4 | "She pressed through the bottleneck" | | 5 | "She knew his face from" | | 6 | "She knew his record." | | 7 | "He slipped her grip with" | | 8 | "He scrambled toward a side" | | 9 | "His Spanish accent sounded thick," | | 10 | "He gripped the edge of" | | 11 | "It wasn't the usual London" | | 12 | "She reached into her heavy" | | 13 | "Her partner, DS Morris, had" | | 14 | "He had returned in a" | | 15 | "She climbed down anyway." | | 16 | "Her good heel struck solid" | | 17 | "She stood in a disused," | | 18 | "she called out, her voice" | | 19 | "She pushed the door." |
| | ratio | 0.342 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 76 | | matches | | 0 | "The cracked brick heel of" | | 1 | "She didn’t stop." | | 2 | "She checked the military-style stride" | | 3 | "Quinn roared, her voice cutting" | | 4 | "The suspect, Tomás Herrera, didn't" | | 5 | "He shoved past a couple" | | 6 | "Quinn checked her worn leather" | | 7 | "The streets were choked with" | | 8 | "Her lungs burned from the" | | 9 | "She pressed through the bottleneck" | | 10 | "She knew his face from" | | 11 | "She knew his record." | | 12 | "Herrera darted left." | | 13 | "The distinctive green neon sign" | | 14 | "Quinn lunged, her fingers brushing" | | 15 | "He slipped her grip with" | | 16 | "The long, jagged scar from" | | 17 | "He scrambled toward a side" | | 18 | "The grate stood half-open, propped" | | 19 | "Quinn warned, her voice dropping" |
| | ratio | 0.921 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 76 | | matches | | 0 | "Yet, the cool subterranean air" | | 1 | "Before Quinn could press him," |
| | ratio | 0.026 | |
| 27.03% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 6 | | matches | | 0 | "She checked the military-style stride that had kept her on the Metropolitan Police force for eighteen decorated years, shifting her weight to the ball of her fo…" | | 1 | "More importantly, she knew his signature: the unauthorised treatments, the patients who should have died but somehow walked out of back-alley clinics with their…" | | 2 | "He had returned in a pine box, the official report citing sudden cardiac arrest, though his skin had been patterned with geometric patterns that looked suspicio…" | | 3 | "Strange, triangular symbols were carved into the mortar, glowing with a faint, bioluminescent violet hue that made the hairs on Quinn's arms stand up." | | 4 | "Gas lamps flickered, casting long, dancing shadows across tables piled high with jarred specimens, shimmering silver vials, and bunches of dried, black flora th…" | | 5 | "People—or things that wore the shape of people with slight, unsettling discrepancies—moved between the stalls in a hushed, reverent silence." |
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| 36.76% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 3 | | matches | | 0 | "Quinn roared, her voice cutting through the heavy hum of London traffic" | | 1 | "Quinn lunged, her fingers brushing the wet nylon of his jacket" | | 2 | "Herrera said, his eyes darting to the exit tunnels behind her" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 8 | | fancyTags | | 0 | "Quinn roared (roar)" | | 1 | "Quinn warned (warn)" | | 2 | "Herrera shouted back (shout)" | | 3 | "she called out (call out)" | | 4 | "a vendor whispered (whisper)" | | 5 | "Herrera hissed (hiss)" | | 6 | "she demanded (demand)" | | 7 | "smooth voice murmured (murmur)" |
| | dialogueSentences | 26 | | tagDensity | 0.462 | | leniency | 0.923 | | rawRatio | 0.667 | | effectiveRatio | 0.615 | |