| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 37 | | tagDensity | 0.216 | | leniency | 0.432 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.26% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1397 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 60.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1397 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "weight" | | 1 | "tracing" | | 2 | "familiar" | | 3 | "measured" | | 4 | "calculated" | | 5 | "silence" | | 6 | "rhythmic" | | 7 | "flickered" | | 8 | "pristine" |
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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 | 60 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 60 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 89 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1395 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 57 | | wordCount | 1011 | | uniqueNames | 13 | | maxNameDensity | 1.98 | | worstName | "Eva" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Silas | 5 | | Soho | 3 | | Golden | 1 | | Empress | 1 | | Cardiff | 2 | | Cathays | 1 | | Eva | 20 | | Rory | 19 | | Cold | 1 | | War | 1 | | Central | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Empress" | | 4 | "Eva" | | 5 | "Rory" | | 6 | "Central" |
| | places | | 0 | "Soho" | | 1 | "Golden" | | 2 | "Cardiff" | | 3 | "Cathays" |
| | globalScore | 0.511 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | 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 | 1395 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 89 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 55 | | mean | 25.36 | | std | 18.62 | | cv | 0.734 | | sampleLengths | | 0 | 50 | | 1 | 61 | | 2 | 13 | | 3 | 64 | | 4 | 12 | | 5 | 32 | | 6 | 11 | | 7 | 1 | | 8 | 22 | | 9 | 1 | | 10 | 34 | | 11 | 18 | | 12 | 72 | | 13 | 39 | | 14 | 4 | | 15 | 4 | | 16 | 4 | | 17 | 12 | | 18 | 34 | | 19 | 21 | | 20 | 17 | | 21 | 6 | | 22 | 58 | | 23 | 3 | | 24 | 38 | | 25 | 27 | | 26 | 12 | | 27 | 5 | | 28 | 39 | | 29 | 31 | | 30 | 9 | | 31 | 23 | | 32 | 46 | | 33 | 14 | | 34 | 23 | | 35 | 52 | | 36 | 4 | | 37 | 59 | | 38 | 10 | | 39 | 37 | | 40 | 30 | | 41 | 5 | | 42 | 41 | | 43 | 34 | | 44 | 7 | | 45 | 21 | | 46 | 23 | | 47 | 4 | | 48 | 37 | | 49 | 18 |
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| 99.42% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 60 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 149 | | matches | (empty) | |
| 46.55% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 2 | | flaggedSentences | 3 | | totalSentences | 89 | | ratio | 0.034 | | matches | | 0 | "She did not sit immediately; she stood inspecting Rory’s face, tracing the hardened angles, the bright blue eyes that no longer hurried to apologize." | | 1 | "\"He wanted his daughter.\" Eva leaned in, her perfume—something crisp and citrusy that Rory remembered from second-year revision sessions—cutting through the stale smell of rain and old draft beer." | | 2 | "The soft wool jumpers and silver hoop earrings were gone; in their place sat a dark linen shirt buttoned to the throat, utilitarian trousers, and hands with cuticles roughened by salt, weather, and crate-straps." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1017 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.01966568338249754 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004916420845624385 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 89 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 89 | | mean | 15.67 | | std | 8.75 | | cv | 0.558 | | sampleLengths | | 0 | 23 | | 1 | 27 | | 2 | 17 | | 3 | 22 | | 4 | 22 | | 5 | 13 | | 6 | 19 | | 7 | 19 | | 8 | 26 | | 9 | 3 | | 10 | 9 | | 11 | 11 | | 12 | 21 | | 13 | 11 | | 14 | 1 | | 15 | 22 | | 16 | 1 | | 17 | 18 | | 18 | 16 | | 19 | 18 | | 20 | 13 | | 21 | 23 | | 22 | 36 | | 23 | 15 | | 24 | 24 | | 25 | 4 | | 26 | 4 | | 27 | 4 | | 28 | 12 | | 29 | 10 | | 30 | 24 | | 31 | 21 | | 32 | 8 | | 33 | 9 | | 34 | 6 | | 35 | 28 | | 36 | 30 | | 37 | 3 | | 38 | 38 | | 39 | 3 | | 40 | 24 | | 41 | 12 | | 42 | 5 | | 43 | 17 | | 44 | 22 | | 45 | 25 | | 46 | 6 | | 47 | 9 | | 48 | 16 | | 49 | 7 |
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| 45.51% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.29213483146067415 | | totalSentences | 89 | | uniqueOpeners | 26 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 60 | | matches | | 0 | "Her black hair fell straight" | | 1 | "She wore a tailored camel" | | 2 | "Her breath caught, fogging the" | | 3 | "Her left wrist, where the" | | 4 | "She let them drop to" | | 5 | "His hazel eyes moved between" | | 6 | "He reached down, drew a" | | 7 | "She did not sit immediately;" | | 8 | "She reached out, her fingertips" | | 9 | "She looked past Eva’s shoulder" | | 10 | "Her posture held the coiled," | | 11 | "He set the glasses down" | | 12 | "She set it next to" | | 13 | "She kept her palms flat" | | 14 | "She stared at Rory for" |
| | ratio | 0.25 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 60 | | matches | | 0 | "Rain streaked the front window" | | 1 | "Rory sat on the corner" | | 2 | "Her black hair fell straight" | | 3 | "A delivery jacket from Golden" | | 4 | "The brass bell above the" | | 5 | "A woman stepped out of" | | 6 | "She wore a tailored camel" | | 7 | "Eva stopped mid-step." | | 8 | "Her breath caught, fogging the" | | 9 | "Rory kept her hand flat" | | 10 | "Her left wrist, where the" | | 11 | "Eva took two cautious strides" | | 12 | "The name sounded foreign under" | | 13 | "Eva stood before the stool," | | 14 | "She let them drop to" | | 15 | "Silas set a clean coaster" | | 16 | "His hazel eyes moved between" | | 17 | "He reached down, drew a" | | 18 | "Eva pulled out the stool" | | 19 | "She did not sit immediately;" |
| | ratio | 0.967 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 59.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 5 | | matches | | 0 | "Rain streaked the front window of The Raven’s Nest, fracturing the green neon into bleeding ribbons of emerald across the dark mahogany tables." | | 1 | "A woman stepped out of the Soho downpour, wrestling with a collapsed umbrella that dripped onto the worn floorboards." | | 2 | "She did not sit immediately; she stood inspecting Rory’s face, tracing the hardened angles, the bright blue eyes that no longer hurried to apologize." | | 3 | "She reached out, her fingertips hovering near Rory’s sleeve before drawing back, settling instead on the rim of the rum glass Silas had left." | | 4 | "She stared at Rory for a long second, searching for any remnant of the girl who used to split bags of chips on the curb outside Cardiff Central, laughing into t…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "Eva whispered (whisper)" |
| | dialogueSentences | 37 | | tagDensity | 0.054 | | leniency | 0.108 | | rawRatio | 0.5 | | effectiveRatio | 0.054 | |