| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 3 | | adverbTags | | 0 | "Sinead nodded then [then]" | | 1 | "She laughed again [again]" | | 2 | "She drank finally [finally]" |
| | dialogueSentences | 65 | | tagDensity | 0.323 | | leniency | 0.646 | | rawRatio | 0.143 | | effectiveRatio | 0.092 | |
| 88.30% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1282 | | 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) | |
| 92.20% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1282 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 56 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 56 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 99 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1276 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 628 | | uniqueNames | 8 | | maxNameDensity | 3.18 | | worstName | "Rory" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Rory" | | discoveredNames | | Tuesday | 1 | | Rory | 20 | | Cardiff | 1 | | Eva | 1 | | Crwys | 1 | | Road | 1 | | Sinead | 12 | | Silas | 3 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Sinead" | | 3 | "Silas" |
| | places | | 0 | "Cardiff" | | 1 | "Crwys" | | 2 | "Road" |
| | globalScore | 0 | | windowScore | 0.167 | |
| 84.21% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 38 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like grief gone stale" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1276 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 99 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 22 | | std | 21.94 | | cv | 0.997 | | sampleLengths | | 0 | 42 | | 1 | 6 | | 2 | 41 | | 3 | 1 | | 4 | 17 | | 5 | 23 | | 6 | 52 | | 7 | 8 | | 8 | 64 | | 9 | 3 | | 10 | 2 | | 11 | 15 | | 12 | 16 | | 13 | 5 | | 14 | 36 | | 15 | 2 | | 16 | 43 | | 17 | 6 | | 18 | 70 | | 19 | 16 | | 20 | 4 | | 21 | 15 | | 22 | 2 | | 23 | 48 | | 24 | 2 | | 25 | 4 | | 26 | 6 | | 27 | 76 | | 28 | 11 | | 29 | 5 | | 30 | 63 | | 31 | 12 | | 32 | 1 | | 33 | 23 | | 34 | 71 | | 35 | 6 | | 36 | 3 | | 37 | 35 | | 38 | 22 | | 39 | 8 | | 40 | 4 | | 41 | 3 | | 42 | 17 | | 43 | 43 | | 44 | 14 | | 45 | 8 | | 46 | 7 | | 47 | 57 | | 48 | 46 | | 49 | 24 |
| |
| 99.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 56 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 124 | | matches | | |
| 85.14% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 99 | | ratio | 0.02 | | matches | | 0 | "\"Flat upstairs. The man who poured your drink owns the place. He's—\" she searched for the word \"—a decent sort. Looks out for people.\"" | | 1 | "\"Aurora. She's three.\" Sinead pulled out her phone, swiped, held it up—a gap-toothed grin, a smear of jam, eyes screwed shut with laughter." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 597 | | adjectiveStacks | 1 | | stackExamples | | 0 | "usual half-empty Tuesday" |
| | adverbCount | 18 | | adverbRatio | 0.03015075376884422 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0016750418760469012 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 99 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 99 | | mean | 12.89 | | std | 11.31 | | cv | 0.877 | | sampleLengths | | 0 | 15 | | 1 | 14 | | 2 | 13 | | 3 | 6 | | 4 | 2 | | 5 | 39 | | 6 | 1 | | 7 | 4 | | 8 | 13 | | 9 | 15 | | 10 | 8 | | 11 | 17 | | 12 | 20 | | 13 | 15 | | 14 | 4 | | 15 | 4 | | 16 | 29 | | 17 | 32 | | 18 | 3 | | 19 | 3 | | 20 | 2 | | 21 | 7 | | 22 | 8 | | 23 | 3 | | 24 | 13 | | 25 | 5 | | 26 | 5 | | 27 | 31 | | 28 | 2 | | 29 | 6 | | 30 | 22 | | 31 | 15 | | 32 | 6 | | 33 | 29 | | 34 | 30 | | 35 | 11 | | 36 | 13 | | 37 | 3 | | 38 | 4 | | 39 | 11 | | 40 | 4 | | 41 | 2 | | 42 | 12 | | 43 | 36 | | 44 | 2 | | 45 | 4 | | 46 | 3 | | 47 | 3 | | 48 | 20 | | 49 | 40 |
| |
| 59.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.3939393939393939 | | totalSentences | 99 | | uniqueOpeners | 39 | |
| 65.36% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 51 | | matches | | 0 | "Somewhere a fridge motor cycled" |
| | ratio | 0.02 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 51 | | matches | | 0 | "She set the glass down" | | 1 | "He had a way of" | | 2 | "She wore it short now," | | 3 | "It wasn't a question" | | 4 | "She made the word sound" | | 5 | "She shrugged, a movement that" | | 6 | "She finished her drink and" | | 7 | "She stopped, pressed two fingers" | | 8 | "She laughed again, but it" | | 9 | "she searched for the word" | | 10 | "She drank, finally, the whisky" | | 11 | "She reached out and, after" | | 12 | "Her fingers were cold too." |
| | ratio | 0.255 | |
| 9.02% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 46 | | totalSentences | 51 | | matches | | 0 | "The green neon hummed above" | | 1 | "Rory shouldered through, shaking rain" | | 2 | "The woman at the bar" | | 3 | "The woman laughed, a sharp" | | 4 | "She set the glass down" | | 5 | "Rory crossed the room slow," | | 6 | "Silas, behind the bar, caught" | | 7 | "He had a way of" | | 8 | "She wore it short now," | | 9 | "Rory turned the glass in" | | 10 | "Sinead's eyebrow climbed." | | 11 | "It wasn't a question" | | 12 | "Sinead studied her with the" | | 13 | "Sinead nodded, then her eyes" | | 14 | "She made the word sound" | | 15 | "Rory looked at the bottles" | | 16 | "The honesty of it landed" | | 17 | "Rory turned her head." | | 18 | "Sinead's jaw tightened" | | 19 | "Rory turned back." |
| | ratio | 0.902 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 51 | | matches | (empty) | | ratio | 0 | |
| 47.62% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 15 | | technicalSentenceCount | 2 | | matches | | 0 | "Rory shouldered through, shaking rain from her jacket, expecting the usual half-empty Tuesday crowd." | | 1 | "Sinead glanced at Silas, who had retreated to the far end and was studying a ledger that needed no studying." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | 0 | "She laughed again (laugh)" |
| | dialogueSentences | 65 | | tagDensity | 0.062 | | leniency | 0.123 | | rawRatio | 0.25 | | effectiveRatio | 0.031 | |