| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.86% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1208 | | 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) | |
| 75.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1208 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "stomach" | | 1 | "lurching" | | 2 | "silk" | | 3 | "hulking" | | 4 | "pulsed" | | 5 | "scanned" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 143 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 143 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 146 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1199 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 95.42% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 1191 | | uniqueNames | 12 | | maxNameDensity | 1.09 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | London | 1 | | Quinn | 1 | | Raven | 1 | | Nest | 1 | | Harlow | 13 | | Soho | 2 | | Morris | 1 | | Tube | 1 | | Northern | 1 | | Line | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Harlow" | | 3 | "Morris" |
| | places | | | globalScore | 0.954 | | windowScore | 1 | |
| 57.41% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like an abandoned Tube station, bu" | | 1 | "felt like bringing a knife to a nuke fi" | | 2 | "sounded like stones grinding together" |
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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 | 1199 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 146 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 31.55 | | std | 19.74 | | cv | 0.626 | | sampleLengths | | 0 | 70 | | 1 | 2 | | 2 | 56 | | 3 | 16 | | 4 | 48 | | 5 | 26 | | 6 | 3 | | 7 | 48 | | 8 | 56 | | 9 | 40 | | 10 | 26 | | 11 | 38 | | 12 | 26 | | 13 | 54 | | 14 | 3 | | 15 | 29 | | 16 | 61 | | 17 | 25 | | 18 | 46 | | 19 | 39 | | 20 | 27 | | 21 | 34 | | 22 | 53 | | 23 | 41 | | 24 | 51 | | 25 | 69 | | 26 | 5 | | 27 | 46 | | 28 | 4 | | 29 | 38 | | 30 | 5 | | 31 | 28 | | 32 | 12 | | 33 | 13 | | 34 | 27 | | 35 | 1 | | 36 | 12 | | 37 | 21 |
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| 88.09% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 143 | | matches | | 0 | "was gone" | | 1 | "was gone" | | 2 | "was traded" | | 3 | "been carved" | | 4 | "been briefed" | | 5 | "being made" | | 6 | "was gone" |
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| 79.88% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 222 | | matches | | 0 | "was bleeding" | | 1 | "was scrambling" | | 2 | "was heading" | | 3 | "were talking" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 146 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1200 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 33 | | adverbRatio | 0.0275 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.0075 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 146 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 146 | | mean | 8.21 | | std | 5.77 | | cv | 0.702 | | sampleLengths | | 0 | 20 | | 1 | 17 | | 2 | 18 | | 3 | 15 | | 4 | 2 | | 5 | 15 | | 6 | 6 | | 7 | 19 | | 8 | 16 | | 9 | 12 | | 10 | 4 | | 11 | 14 | | 12 | 4 | | 13 | 3 | | 14 | 5 | | 15 | 22 | | 16 | 9 | | 17 | 5 | | 18 | 8 | | 19 | 2 | | 20 | 2 | | 21 | 3 | | 22 | 8 | | 23 | 6 | | 24 | 3 | | 25 | 3 | | 26 | 17 | | 27 | 5 | | 28 | 3 | | 29 | 1 | | 30 | 2 | | 31 | 13 | | 32 | 12 | | 33 | 7 | | 34 | 12 | | 35 | 4 | | 36 | 8 | | 37 | 7 | | 38 | 6 | | 39 | 21 | | 40 | 4 | | 41 | 2 | | 42 | 9 | | 43 | 3 | | 44 | 14 | | 45 | 6 | | 46 | 11 | | 47 | 21 | | 48 | 10 | | 49 | 11 |
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| 41.32% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.3219178082191781 | | totalSentences | 146 | | uniqueOpeners | 47 | |
| 26.25% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 127 | | matches | | 0 | "Just gone from a locked" |
| | ratio | 0.008 | |
| 49.92% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 54 | | totalSentences | 127 | | matches | | 0 | "He pumped his arms, legs" | | 1 | "She’d been watching this stretch" | | 2 | "She checked her watch, the" | | 3 | "He didn't slow down." | | 4 | "He didn't climb." | | 5 | "He simply ran through it." | | 6 | "She stared at the fence." | | 7 | "It rattled in the wind," | | 8 | "She slammed a hand against" | | 9 | "It rang out, solid and" | | 10 | "He was gone." | | 11 | "Her heart hammered against her" | | 12 | "She looked left, then right." | | 13 | "She reached out, fingers brushing" | | 14 | "It tasted like ozone." | | 15 | "She gritted her teeth, her" | | 16 | "She drew her service weapon," | | 17 | "She spun around, weapon raised." | | 18 | "She stood at the edge" | | 19 | "It looked like an abandoned" |
| | ratio | 0.425 | |
| 15.12% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 113 | | totalSentences | 127 | | matches | | 0 | "Rain lashed against the pavement," | | 1 | "Harlow Quinn vaulted over a" | | 2 | "The suspect was ahead, a" | | 3 | "That distinctive green neon sign" | | 4 | "Harlow’s voice cracked through the" | | 5 | "The runner didn't even look" | | 6 | "He pumped his arms, legs" | | 7 | "She’d been watching this stretch" | | 8 | "She checked her watch, the" | | 9 | "Time was bleeding away." | | 10 | "The suspect hit the chain-link" | | 11 | "He didn't slow down." | | 12 | "He didn't climb." | | 13 | "He simply ran through it." | | 14 | "The metal links seemed to" | | 15 | "Harlow skidded to a halt," | | 16 | "She stared at the fence." | | 17 | "It rattled in the wind," | | 18 | "She slammed a hand against" | | 19 | "It rang out, solid and" |
| | ratio | 0.89 | |
| 78.74% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 127 | | matches | | 0 | "Even down here, he was" | | 1 | "If it closed, he was" |
| | ratio | 0.016 | |
| 74.18% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 5 | | matches | | 0 | "Harlow Quinn vaulted over a discarded bin, her boots skidding on the slick cobblestones before finding purchase." | | 1 | "The arches were too high, the tiles stained with ancient soot that glowed with a faint, violet luminescence." | | 2 | "He had pulled off his hoodie, revealing a shock of white hair and a vest that glimmered with shifting scales." | | 3 | "A being made of writhing smoke brushed past her shoulder, leaving a trail of ice on her skin." | | 4 | "Every instinct screamed at her to run back to the rain-soaked alley, back to the world where the bad guys just carried guns and the worst thing that happened wa…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |