| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 91.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 605 | | 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) | |
| 66.94% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 605 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "gloom" | | 1 | "scanned" | | 2 | "weight" | | 3 | "firmly" |
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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 | 45 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 45 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 45 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 604 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 604 | | uniqueNames | 17 | | maxNameDensity | 1.32 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Tomás" | | discoveredNames | | Soho | 1 | | Detective | 1 | | Harlow | 8 | | Quinn | 1 | | Raven | 1 | | Nest | 1 | | Greek | 1 | | Street | 1 | | Camden | 1 | | Tube | 1 | | Victorian | 1 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 6 | | Morris | 1 | | You | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Tomás" | | 7 | "Morris" | | 8 | "You" |
| | places | | 0 | "Soho" | | 1 | "Detective" | | 2 | "Greek" | | 3 | "Street" |
| | globalScore | 0.838 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | 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 | 604 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 45 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 20.13 | | std | 18.3 | | cv | 0.909 | | sampleLengths | | 0 | 61 | | 1 | 26 | | 2 | 59 | | 3 | 20 | | 4 | 12 | | 5 | 44 | | 6 | 19 | | 7 | 14 | | 8 | 79 | | 9 | 4 | | 10 | 31 | | 11 | 13 | | 12 | 16 | | 13 | 11 | | 14 | 14 | | 15 | 39 | | 16 | 5 | | 17 | 6 | | 18 | 12 | | 19 | 7 | | 20 | 6 | | 21 | 15 | | 22 | 5 | | 23 | 12 | | 24 | 15 | | 25 | 7 | | 26 | 9 | | 27 | 20 | | 28 | 4 | | 29 | 19 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 45 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 106 | | matches | (empty) | |
| 79.37% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 45 | | ratio | 0.022 | | matches | | 0 | "The smell hit her first—ozone, wet earth, and the unmistakable metallic tang of spilled blood." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 607 | | adjectiveStacks | 1 | | stackExamples | | 0 | "under greasy yellow sodium" |
| | adverbCount | 7 | | adverbRatio | 0.011532125205930808 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.006589785831960461 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 45 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 45 | | mean | 13.42 | | std | 6.14 | | cv | 0.458 | | sampleLengths | | 0 | 9 | | 1 | 21 | | 2 | 10 | | 3 | 21 | | 4 | 26 | | 5 | 17 | | 6 | 20 | | 7 | 6 | | 8 | 16 | | 9 | 6 | | 10 | 14 | | 11 | 12 | | 12 | 10 | | 13 | 15 | | 14 | 19 | | 15 | 19 | | 16 | 14 | | 17 | 18 | | 18 | 21 | | 19 | 15 | | 20 | 25 | | 21 | 4 | | 22 | 13 | | 23 | 18 | | 24 | 13 | | 25 | 16 | | 26 | 11 | | 27 | 14 | | 28 | 25 | | 29 | 14 | | 30 | 5 | | 31 | 6 | | 32 | 12 | | 33 | 7 | | 34 | 6 | | 35 | 15 | | 36 | 5 | | 37 | 12 | | 38 | 15 | | 39 | 7 | | 40 | 3 | | 41 | 6 | | 42 | 20 | | 43 | 4 | | 44 | 19 |
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| 77.78% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.4666666666666667 | | totalSentences | 45 | | uniqueOpeners | 21 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 45 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 9 | | totalSentences | 45 | | matches | | 0 | "She hit the bottom landing," | | 1 | "She descended deeper into the" | | 2 | "You take one more step" | | 3 | "I want the runner, Tomás." | | 4 | "You chase ghosts you cannot" | | 5 | "I make my own currency." | | 6 | "You walk blind into the" | | 7 | "I survived three years of" | | 8 | "You survived luck." |
| | ratio | 0.2 | |
| 4.44% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 41 | | totalSentences | 45 | | matches | | 0 | "The Soho asphalt gleamed under" | | 1 | "A worn leather strap dug" | | 2 | "Rain slicked her closely cropped" | | 3 | "Harlow closed the distance with" | | 4 | "Water cascaded down the rusted" | | 5 | "Cobwebs and soot choked the" | | 6 | "She hit the bottom landing," | | 7 | "Turnstile gates hung off their" | | 8 | "Graffiti smeared the tiled walls" | | 9 | "The suspect ducked beneath a" | | 10 | "Harlow vaulted the broken barrier," | | 11 | "The smell hit her first—ozone," | | 12 | "She descended deeper into the" | | 13 | "A heavy iron door at" | | 14 | "Harlow reached the threshold and" | | 15 | "Rows of makeshift stalls stretched" | | 16 | "Murmurs and low hisses rippled" | | 17 | "A vendor tossed a fistful" | | 18 | "The market swallowed sound." | | 19 | "Harlow scanned the sea of" |
| | ratio | 0.911 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 45 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 1 | | matches | | 0 | "A vendor tossed a fistful of dried roots into a copper brazier, sending up a choking column of blue smoke that smelled of rotting plums." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |