| 40.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 2 | | adverbTags | | 0 | "Tomás stepped back [back]" | | 1 | "Tomás said quietly [quietly]" |
| | dialogueSentences | 25 | | tagDensity | 0.36 | | leniency | 0.72 | | rawRatio | 0.222 | | effectiveRatio | 0.16 | |
| 95.43% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1093 | | totalAiIsmAdverbs | 1 | | 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) | |
| 45.11% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1093 | | totalAiIsms | 12 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | word | "the last thing" | | count | 1 |
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| | highlights | | 0 | "pulse" | | 1 | "stomach" | | 2 | "predictable" | | 3 | "tracing" | | 4 | "calculating" | | 5 | "flickered" | | 6 | "echoed" | | 7 | "glinting" | | 8 | "echoing" | | 9 | "scanning" | | 10 | "the last thing" |
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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 | 1 | | narrationSentences | 84 | | matches | | |
| 91.84% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 84 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 101 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 8 | | markdownWords | 36 | | totalWords | 1086 | | ratio | 0.033 | | matches | | 0 | "Too slow." | | 1 | "Medieval protection for a modern killer." | | 2 | "Copper. Blood." | | 3 | "Thirty feet down. Concrete, steel, probably booby-trapped." | | 4 | "Bone token requirement. Always was." | | 5 | "Entry requirement." | | 6 | "Property of the Consortium" | | 7 | "Slow acting. Give me time to find him." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 72.22% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 900 | | uniqueNames | 10 | | maxNameDensity | 1.56 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 14 | | Quinn | 1 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Greek | 1 | | Tomás | 10 | | Morris | 2 | | Tube | 1 | | Underneath | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Tomás" | | 6 | "Morris" |
| | places | (empty) | | globalScore | 0.722 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | 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 | 1086 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 101 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 28.58 | | std | 19.28 | | cv | 0.675 | | sampleLengths | | 0 | 38 | | 1 | 59 | | 2 | 12 | | 3 | 48 | | 4 | 57 | | 5 | 39 | | 6 | 26 | | 7 | 10 | | 8 | 30 | | 9 | 11 | | 10 | 45 | | 11 | 33 | | 12 | 3 | | 13 | 13 | | 14 | 23 | | 15 | 51 | | 16 | 4 | | 17 | 55 | | 18 | 49 | | 19 | 28 | | 20 | 6 | | 21 | 26 | | 22 | 3 | | 23 | 41 | | 24 | 12 | | 25 | 29 | | 26 | 58 | | 27 | 4 | | 28 | 24 | | 29 | 32 | | 30 | 2 | | 31 | 74 | | 32 | 2 | | 33 | 41 | | 34 | 8 | | 35 | 43 | | 36 | 27 | | 37 | 20 |
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| 96.91% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 84 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 161 | | matches | | 0 | "was weeping" | | 1 | "were running" |
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| 1.41% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 101 | | ratio | 0.05 | | matches | | 0 | "Tomás Herrera—if the scar on his forearm was any indication—moved like a man who’d spent too many nights patching up the wounded." | | 1 | "The air thickened with the smell of wet concrete and something else—something that made her stomach clench." | | 2 | "The hole opened into a tunnel lined with pipes that dripped rhythmically—drip, drip, drip—like a clock counting down." | | 3 | "Faces turned toward the sound, and she saw them—recognizable, but wrong." | | 4 | "Harlow’s training kicked in—cover, move, return fire—but her bullets passed through men who dissolved into smoke and feathers." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 665 | | adjectiveStacks | 1 | | stackExamples | | 0 | "far below, moving like" |
| | adverbCount | 17 | | adverbRatio | 0.02556390977443609 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.006015037593984963 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 101 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 101 | | mean | 10.75 | | std | 6.62 | | cv | 0.616 | | sampleLengths | | 0 | 22 | | 1 | 14 | | 2 | 2 | | 3 | 15 | | 4 | 22 | | 5 | 16 | | 6 | 6 | | 7 | 12 | | 8 | 4 | | 9 | 17 | | 10 | 8 | | 11 | 17 | | 12 | 1 | | 13 | 1 | | 14 | 8 | | 15 | 13 | | 16 | 14 | | 17 | 8 | | 18 | 14 | | 19 | 18 | | 20 | 15 | | 21 | 6 | | 22 | 20 | | 23 | 6 | | 24 | 6 | | 25 | 4 | | 26 | 18 | | 27 | 5 | | 28 | 7 | | 29 | 6 | | 30 | 5 | | 31 | 5 | | 32 | 22 | | 33 | 11 | | 34 | 7 | | 35 | 9 | | 36 | 3 | | 37 | 16 | | 38 | 5 | | 39 | 3 | | 40 | 7 | | 41 | 6 | | 42 | 23 | | 43 | 5 | | 44 | 12 | | 45 | 3 | | 46 | 19 | | 47 | 12 | | 48 | 4 | | 49 | 12 |
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| 78.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.4752475247524752 | | totalSentences | 101 | | uniqueOpeners | 48 | |
| 87.72% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 76 | | matches | | 0 | "Instead, he veered into the" | | 1 | "Always was.* She thought of" |
| | ratio | 0.026 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 76 | | matches | | 0 | "She pressed the worn leather" | | 1 | "She could see it now," | | 2 | "she barked, her voice cutting" | | 3 | "He didn’t break stride." | | 4 | "She wrenched free with a" | | 5 | "They emerged onto a rooftop," | | 6 | "She clipped her shoulder holster," | | 7 | "He laughed, but it sounded" | | 8 | "She stumbled toward the hole," | | 9 | "Her radio crackled with static." | | 10 | "She pressed her ear to" | | 11 | "She cut her hand on" | | 12 | "His medallion caught the light," | | 13 | "He prised open the grate" | | 14 | "He gestured to the tunnel" | | 15 | "His smile was sad." | | 16 | "She drew her weapon, scanning" | | 17 | "She dove behind a crate" |
| | ratio | 0.237 | |
| 38.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 76 | | matches | | 0 | "The rain hammered the pavement" | | 1 | "She pressed the worn leather" | | 2 | "The man ahead stumbled, his" | | 3 | "Tomás Herrera—if the scar on" | | 4 | "She could see it now," | | 5 | "*Medieval protection for a modern" | | 6 | "she barked, her voice cutting" | | 7 | "He didn’t break stride." | | 8 | "Harlow followed, boots slipping on" | | 9 | "The air thickened with the" | | 10 | "The alley dead-ended at a" | | 11 | "Tomás scaled it without hesitation," | | 12 | "Harlow launched herself onto the" | | 13 | "Halfway up, a loose bolt" | | 14 | "She wrenched free with a" | | 15 | "They emerged onto a rooftop," | | 16 | "Tomás paused at the edge," | | 17 | "She clipped her shoulder holster," | | 18 | "He laughed, but it sounded" | | 19 | "Harlow dropped to her knees," |
| | ratio | 0.842 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 76 | | matches | (empty) | | ratio | 0 | |
| 53.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 5 | | matches | | 0 | "The air thickened with the smell of wet concrete and something else—something that made her stomach clench." | | 1 | "Always was.* She thought of Morris’s last case, the footage that showed him descending into something that shouldn’t exist." | | 2 | "Something that stole men’s faces and replaced them with masks of kindness." | | 3 | "Harlow’s boots echoed off the walls as she descended further, the beam growing brighter until she saw it: the abandoned Tube station, its platforms crumbling un…" | | 4 | "The autopsy photos that showed her partner’s eyes swapped for something cold and hungry." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 3 | | matches | | 0 | "she barked, her voice cutting through the storm like a blade" | | 1 | "She clipped, the metal scraping against her leather watch" | | 2 | "Harlow dropped, fingers tracing a symbol carved into the rooftop’s stone slab" |
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| 70.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "she barked (bark)" | | 1 | "she whispered (whisper)" |
| | dialogueSentences | 25 | | tagDensity | 0.12 | | leniency | 0.24 | | rawRatio | 0.667 | | effectiveRatio | 0.16 | |