| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 2 | | adverbTags | | 0 | "Rory asked quietly [quietly]" | | 1 | "the composure slipped just [just]" |
| | dialogueSentences | 47 | | tagDensity | 0.447 | | leniency | 0.894 | | rawRatio | 0.095 | | effectiveRatio | 0.085 | |
| 92.38% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1313 | | totalAiIsmAdverbs | 2 | | 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) | |
| 69.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1313 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "familiar" | | 1 | "warmth" | | 2 | "eyebrow" | | 3 | "silence" | | 4 | "measured" |
| |
| 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 | 63 | | matches | (empty) | |
| 97.51% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 63 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 87 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 86 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1307 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 52 | | wordCount | 881 | | uniqueNames | 11 | | maxNameDensity | 2.04 | | worstName | "Rory" | | maxWindowNameDensity | 5 | | worstWindowName | "Eva" | | discoveredNames | | Rory | 18 | | Berwick | 1 | | Street | 1 | | Raven | 1 | | Nest | 2 | | Silas | 7 | | Thursday | 1 | | Berlin | 1 | | Wall | 2 | | Eva | 16 | | Cardiff | 2 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Silas" | | 4 | "Wall" | | 5 | "Eva" |
| | places | | 0 | "Berwick" | | 1 | "Street" | | 2 | "Berlin" | | 3 | "Cardiff" |
| | globalScore | 0.478 | | windowScore | 0 | |
| 90.48% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 42 | | glossingSentenceCount | 1 | | matches | | 0 | "va's world had apparently been circling each" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1307 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 87 | | matches | | 0 | "learned that stillness" |
| |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 33.51 | | std | 29.88 | | cv | 0.892 | | sampleLengths | | 0 | 92 | | 1 | 67 | | 2 | 11 | | 3 | 4 | | 4 | 20 | | 5 | 49 | | 6 | 1 | | 7 | 116 | | 8 | 16 | | 9 | 27 | | 10 | 23 | | 11 | 52 | | 12 | 27 | | 13 | 5 | | 14 | 61 | | 15 | 47 | | 16 | 10 | | 17 | 31 | | 18 | 40 | | 19 | 8 | | 20 | 9 | | 21 | 60 | | 22 | 57 | | 23 | 8 | | 24 | 70 | | 25 | 27 | | 26 | 111 | | 27 | 1 | | 28 | 61 | | 29 | 56 | | 30 | 18 | | 31 | 2 | | 32 | 34 | | 33 | 1 | | 34 | 4 | | 35 | 3 | | 36 | 39 | | 37 | 14 | | 38 | 25 |
| |
| 88.55% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 63 | | matches | | 0 | "was composed" | | 1 | "was cropped" | | 2 | "being asked" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 158 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 1 | | flaggedSentences | 5 | | totalSentences | 87 | | ratio | 0.057 | | matches | | 0 | "She shook the water off the way a dog shakes off a bath, and the bar's familiar warmth closed around her—wood polish, spilled lager, the faint char of Silas's ever-present bowl of roasted almonds going cold on the counter." | | 1 | "His limp was bad tonight; she noticed he favoured the left leg on the turn." | | 2 | "This was not the Eva she remembered—Eva who talked over the endings of films, who once climbed the fire escape of the students' union at three in the morning to steal a plant." | | 3 | "\"That's what I came to say, I think. All those years I was becoming this—\" she touched her collar, the line of her close-cropped hair, the small white scar like an afterthought through her brow, \"—I kept the version of you from that flat in Cardiff in my head. Rory with the paint on her fingers. Rory who thought a plant counted as a felony. Every decision I've made since, I've half-made against you. What would she think. What would she have done.\"" | | 4 | "Eva looked at her for a long moment—the old friend and the new stranger occupying the same face—and then, slowly, she took off her coat." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 851 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.03525264394829612 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.010575793184488837 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 87 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 87 | | mean | 15.02 | | std | 13.23 | | cv | 0.88 | | sampleLengths | | 0 | 28 | | 1 | 25 | | 2 | 39 | | 3 | 7 | | 4 | 39 | | 5 | 21 | | 6 | 6 | | 7 | 5 | | 8 | 4 | | 9 | 17 | | 10 | 3 | | 11 | 26 | | 12 | 23 | | 13 | 1 | | 14 | 8 | | 15 | 32 | | 16 | 18 | | 17 | 10 | | 18 | 34 | | 19 | 14 | | 20 | 3 | | 21 | 3 | | 22 | 10 | | 23 | 5 | | 24 | 3 | | 25 | 16 | | 26 | 3 | | 27 | 9 | | 28 | 14 | | 29 | 2 | | 30 | 6 | | 31 | 29 | | 32 | 15 | | 33 | 15 | | 34 | 12 | | 35 | 5 | | 36 | 19 | | 37 | 35 | | 38 | 7 | | 39 | 4 | | 40 | 33 | | 41 | 10 | | 42 | 5 | | 43 | 5 | | 44 | 5 | | 45 | 15 | | 46 | 11 | | 47 | 14 | | 48 | 26 | | 49 | 8 |
| |
| 75.48% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.4942528735632184 | | totalSentences | 87 | | uniqueOpeners | 43 | |
| 61.73% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 54 | | matches | | 0 | "Instead, sitting in the booth" |
| | ratio | 0.019 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 54 | | matches | | 0 | "She shook the water off" | | 1 | "he said, without looking up" | | 2 | "He set the glass down" | | 3 | "She turned, expecting one of" | | 4 | "Her hair was cropped close" | | 5 | "She wore a charcoal coat" | | 6 | "She knew how." | | 7 | "She didn't take off her" | | 8 | "His limp was bad tonight;" | | 9 | "She picked up her whisky" | | 10 | "It wasn't a question either" | | 11 | "She finally drank, a small" | | 12 | "Her hands were steady, but" | | 13 | "she touched her collar, the" | | 14 | "She reached across the table" |
| | ratio | 0.278 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 54 | | matches | | 0 | "The rain had followed Rory" | | 1 | "She shook the water off" | | 2 | "The Nest was quiet for" | | 3 | "A couple of regulars hunched" | | 4 | "Silas was behind the bar," | | 5 | "he said, without looking up" | | 6 | "He set the glass down" | | 7 | "She turned, expecting one of" | | 8 | "The last time she'd seen" | | 9 | "The woman in the booth" | | 10 | "Her hair was cropped close" | | 11 | "She wore a charcoal coat" | | 12 | "A confirmation, as if she'd" | | 13 | "She knew how." | | 14 | "Silas's world and Eva's world" | | 15 | "Eva gestured at the seat" | | 16 | "She didn't take off her" | | 17 | "Silas appeared with two whiskies" | | 18 | "His limp was bad tonight;" | | 19 | "Eva said, after the silence" |
| | ratio | 0.833 | |
| 92.59% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 54 | | matches | | 0 | "By the time she pushed" |
| | ratio | 0.019 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 5 | | matches | | 0 | "The rain had followed Rory all the way from Berwick Street, shepherding her toward the green neon glow of the Raven's Nest like a sheepdog that wouldn't quit." | | 1 | "Silas was behind the bar, wiping a glass that was already clean, his silver signet ring catching the low amber light." | | 2 | "She turned, expecting one of Silas's odd assortment of hangers-on, someone with a parcel or a question or a job that paid in cash and favours." | | 3 | "The last time she'd seen Eva, they'd been twenty and twenty-one, crammed into a Cardiff flat that smelled of burnt toast and cheap wine, planning a future that …" | | 4 | "Rory looked at her whisky, then at the woman who had replaced her friend the way a city replaces itself, street by street, until only the street names remain." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, without looking up" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.213 | | leniency | 0.426 | | rawRatio | 0 | | effectiveRatio | 0 | |