| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 42 | | tagDensity | 0.452 | | leniency | 0.905 | | rawRatio | 0.053 | | effectiveRatio | 0.048 | |
| 91.05% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1676 | | totalAiIsmAdverbs | 3 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
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| | 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) | |
| 64.20% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1676 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "flicker" | | 1 | "scanned" | | 2 | "fragmented" | | 3 | "sturdy" | | 4 | "gloom" | | 5 | "maw" | | 6 | "perfect" | | 7 | "methodical" | | 8 | "database" | | 9 | "stark" | | 10 | "pulsed" |
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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 | 166 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 166 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 192 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 5 | | totalWords | 1676 | | ratio | 0.003 | | matches | | 0 | "Harlow." | | 1 | "TONIGHT. BRING THE COMPASS." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 1276 | | uniqueNames | 11 | | maxNameDensity | 1.33 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 17 | | Camden | 2 | | Town | 1 | | Veil | 2 | | Market | 3 | | Tuesday | 1 | | Morris | 6 | | Davies | 11 | | Compass | 1 | | Portobello | 1 | | Southwark | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Market" | | 2 | "Tuesday" | | 3 | "Morris" | | 4 | "Davies" |
| | places | | 0 | "Camden" | | 1 | "Town" | | 2 | "Portobello" |
| | globalScore | 0.834 | | windowScore | 0.667 | |
| 51.96% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 102 | | glossingSentenceCount | 4 | | matches | | 0 | "looked like a broken spiral" | | 1 | "substance that seemed to absorb the torchlight" | | 2 | "felt like a foreign country" | | 3 | "felt like a lump of ice in her pocket" |
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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 | 1676 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 192 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 61 | | mean | 27.48 | | std | 20.01 | | cv | 0.728 | | sampleLengths | | 0 | 56 | | 1 | 37 | | 2 | 3 | | 3 | 34 | | 4 | 62 | | 5 | 4 | | 6 | 31 | | 7 | 16 | | 8 | 37 | | 9 | 12 | | 10 | 86 | | 11 | 56 | | 12 | 17 | | 13 | 15 | | 14 | 52 | | 15 | 26 | | 16 | 21 | | 17 | 18 | | 18 | 19 | | 19 | 3 | | 20 | 10 | | 21 | 51 | | 22 | 11 | | 23 | 2 | | 24 | 52 | | 25 | 33 | | 26 | 4 | | 27 | 34 | | 28 | 6 | | 29 | 48 | | 30 | 31 | | 31 | 9 | | 32 | 27 | | 33 | 10 | | 34 | 44 | | 35 | 49 | | 36 | 17 | | 37 | 66 | | 38 | 25 | | 39 | 7 | | 40 | 38 | | 41 | 2 | | 42 | 36 | | 43 | 63 | | 44 | 3 | | 45 | 35 | | 46 | 1 | | 47 | 36 | | 48 | 44 | | 49 | 56 |
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| 92.58% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 166 | | matches | | 0 | "was frozen" | | 1 | "been scrawled" | | 2 | "been painted" | | 3 | "were drawn" | | 4 | "were coated" | | 5 | "was pitted" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 198 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 192 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 585 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.023931623931623933 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.005128205128205128 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 192 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 192 | | mean | 8.73 | | std | 6.01 | | cv | 0.688 | | sampleLengths | | 0 | 9 | | 1 | 21 | | 2 | 17 | | 3 | 5 | | 4 | 4 | | 5 | 14 | | 6 | 6 | | 7 | 17 | | 8 | 3 | | 9 | 4 | | 10 | 16 | | 11 | 14 | | 12 | 5 | | 13 | 14 | | 14 | 8 | | 15 | 1 | | 16 | 3 | | 17 | 3 | | 18 | 7 | | 19 | 11 | | 20 | 5 | | 21 | 5 | | 22 | 4 | | 23 | 12 | | 24 | 19 | | 25 | 7 | | 26 | 3 | | 27 | 2 | | 28 | 4 | | 29 | 15 | | 30 | 22 | | 31 | 4 | | 32 | 8 | | 33 | 10 | | 34 | 13 | | 35 | 10 | | 36 | 9 | | 37 | 33 | | 38 | 11 | | 39 | 6 | | 40 | 10 | | 41 | 5 | | 42 | 11 | | 43 | 7 | | 44 | 10 | | 45 | 5 | | 46 | 2 | | 47 | 7 | | 48 | 10 | | 49 | 12 |
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| 46.53% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 19 | | diversityRatio | 0.3385416666666667 | | totalSentences | 192 | | uniqueOpeners | 65 | |
| 44.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 150 | | matches | | 0 | "Then they entered the main" | | 1 | "Just an image." |
| | ratio | 0.013 | |
| 92.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 150 | | matches | | 0 | "She ducked under the yellow" | | 1 | "It was also immaculately clean." | | 2 | "He pointed with a gloved" | | 3 | "He gestured to a dark" | | 4 | "She examined the neat incision" | | 5 | "he said, gesturing" | | 6 | "She rose, her knees popping," | | 7 | "It dealt in banned alchemical" | | 8 | "It had, however, been scrawled" | | 9 | "Her light swept the vaulted" | | 10 | "She returned to the body." | | 11 | "His jacket was practical, high-end" | | 12 | "He looked prepared for something." | | 13 | "He held it out." | | 14 | "She pocketed the bone token" | | 15 | "She shone her torch." | | 16 | "She turned back." | | 17 | "He sighed, pulling out his" | | 18 | "They came down from an" | | 19 | "They joked about ghosts." |
| | ratio | 0.32 | |
| 66.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 118 | | totalSentences | 150 | | matches | | 0 | "The coppery stench hit Quinn" | | 1 | "She ducked under the yellow" | | 2 | "The abandoned platform was a" | | 3 | "It was also immaculately clean." | | 4 | "Davies approached, his shoes crunching" | | 5 | "He pointed with a gloved" | | 6 | "Davies checked his notebook." | | 7 | "He gestured to a dark" | | 8 | "Quinn knelt beside the corpse." | | 9 | "The man’s face was frozen" | | 10 | "She examined the neat incision" | | 11 | "The body was bloodless, yes," | | 12 | "he said, gesturing" | | 13 | "Quinn’s fingers hovered over the" | | 14 | "Quinn’s jaw tightened" | | 15 | "She rose, her knees popping," | | 16 | "The Veil Market, according to" | | 17 | "It dealt in banned alchemical" | | 18 | "A place where the impossible" | | 19 | "DS Morris had been sniffing" |
| | ratio | 0.787 | |
| 33.33% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 150 | | matches | | 0 | "By the time she reached" |
| | ratio | 0.007 | |
| 96.27% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 3 | | matches | | 0 | "A piece of rough-hewn stone, about the size of a domino, carved with a symbol that looked like a broken spiral." | | 1 | "It was a series of concentric circles, a pattern that made Quinn’s eyes water if she stared too long." | | 2 | "A brass trinket from a stall in Portobello that wasn’t there the next day." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | 0 | "Davies observed (observe)" |
| | dialogueSentences | 42 | | tagDensity | 0.119 | | leniency | 0.238 | | rawRatio | 0.2 | | effectiveRatio | 0.048 | |