| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 69 | | tagDensity | 0.232 | | leniency | 0.464 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2178 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 81.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2178 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "fractured" | | 1 | "familiar" | | 2 | "weight" | | 3 | "stomach" | | 4 | "flicked" | | 5 | "calculate" | | 6 | "silence" |
| |
| 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 | 123 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 123 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 175 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 74 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2176 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 25 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 76 | | wordCount | 1190 | | uniqueNames | 12 | | maxNameDensity | 2.52 | | worstName | "Rory" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Golden | 1 | | Empress | 1 | | November | 1 | | Rory | 30 | | Cardiff | 1 | | Eva | 28 | | Islington | 1 | | Silas | 9 | | Berlin | 1 | | Soho | 1 |
| | persons | | 0 | "Raven" | | 1 | "Rory" | | 2 | "Eva" | | 3 | "Silas" |
| | places | | 0 | "Cardiff" | | 1 | "Islington" | | 2 | "Berlin" | | 3 | "Soho" |
| | globalScore | 0.239 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 76 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed closer their lines like veins" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.46 | | wordCount | 2176 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 175 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 88 | | mean | 24.73 | | std | 19.67 | | cv | 0.795 | | sampleLengths | | 0 | 106 | | 1 | 60 | | 2 | 54 | | 3 | 6 | | 4 | 21 | | 5 | 1 | | 6 | 11 | | 7 | 5 | | 8 | 38 | | 9 | 16 | | 10 | 15 | | 11 | 6 | | 12 | 16 | | 13 | 21 | | 14 | 11 | | 15 | 9 | | 16 | 5 | | 17 | 11 | | 18 | 4 | | 19 | 5 | | 20 | 3 | | 21 | 21 | | 22 | 19 | | 23 | 36 | | 24 | 43 | | 25 | 5 | | 26 | 39 | | 27 | 9 | | 28 | 2 | | 29 | 70 | | 30 | 16 | | 31 | 42 | | 32 | 23 | | 33 | 34 | | 34 | 32 | | 35 | 2 | | 36 | 11 | | 37 | 32 | | 38 | 19 | | 39 | 44 | | 40 | 6 | | 41 | 11 | | 42 | 18 | | 43 | 55 | | 44 | 33 | | 45 | 4 | | 46 | 42 | | 47 | 46 | | 48 | 13 | | 49 | 48 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 123 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 214 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 175 | | ratio | 0.006 | | matches | | 0 | "“Mark has a housekeeper.” The admission cost her; Rory heard it in the pause." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1195 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.026778242677824266 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0041841004184100415 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 175 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 175 | | mean | 12.43 | | std | 10.88 | | cv | 0.875 | | sampleLengths | | 0 | 28 | | 1 | 30 | | 2 | 20 | | 3 | 17 | | 4 | 11 | | 5 | 28 | | 6 | 12 | | 7 | 12 | | 8 | 8 | | 9 | 2 | | 10 | 13 | | 11 | 20 | | 12 | 4 | | 13 | 15 | | 14 | 6 | | 15 | 5 | | 16 | 16 | | 17 | 1 | | 18 | 11 | | 19 | 4 | | 20 | 1 | | 21 | 6 | | 22 | 32 | | 23 | 8 | | 24 | 8 | | 25 | 5 | | 26 | 10 | | 27 | 6 | | 28 | 11 | | 29 | 5 | | 30 | 3 | | 31 | 8 | | 32 | 10 | | 33 | 4 | | 34 | 7 | | 35 | 3 | | 36 | 4 | | 37 | 2 | | 38 | 5 | | 39 | 11 | | 40 | 4 | | 41 | 4 | | 42 | 1 | | 43 | 3 | | 44 | 21 | | 45 | 13 | | 46 | 6 | | 47 | 8 | | 48 | 28 | | 49 | 19 |
| |
| 48.29% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.25142857142857145 | | totalSentences | 175 | | uniqueOpeners | 44 | |
| 30.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 110 | | matches | | 0 | "Bright blue against whatever colour" |
| | ratio | 0.009 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 110 | | matches | | 0 | "His left knee gave its" | | 1 | "Her black hair hung straight," | | 2 | "She watched the door out" | | 3 | "Her walk had changed too," | | 4 | "She left a gap, the" | | 5 | "She didn’t scratch it." | | 6 | "she indicated the swell" | | 7 | "His hazel eyes flicked to" | | 8 | "They sat with that." | | 9 | "She looked at her hands," | | 10 | "She had seen Silas disappear" | | 11 | "He didn’t speak." | | 12 | "She pushed it away." | | 13 | "They fell quiet." | | 14 | "She didn’t order another." | | 15 | "His back to them, he" | | 16 | "Her fingers brushed the scar," | | 17 | "She didn’t stand." | | 18 | "His ring tapped the wood." | | 19 | "He said nothing, but his" |
| | ratio | 0.2 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 104 | | totalSentences | 110 | | matches | | 0 | "The rain needled the windows" | | 1 | "Maps of vanished borders covered" | | 2 | "Silas stood behind the bar," | | 3 | "The silver signet ring on" | | 4 | "His left knee gave its" | | 5 | "Rory occupied the last stool," | | 6 | "Her black hair hung straight," | | 7 | "The crescent scar on her" | | 8 | "She watched the door out" | | 9 | "A woman stepped through, shaking" | | 10 | "The face had thinned." | | 11 | "Rory’s fingers stilled on the" | | 12 | "The woman crossed the room." | | 13 | "Her walk had changed too," | | 14 | "The name landed between them" | | 15 | "Rory turned the stool." | | 16 | "Eva stopped an arm’s length" | | 17 | "Silas glanced once, then returned" | | 18 | "The limp took him toward" | | 19 | "Eva took the next stool." |
| | ratio | 0.945 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 110 | | matches | (empty) | | ratio | 0 | |
| 31.75% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 7 | | matches | | 0 | "New hollows under the cheekbones, a tightness around the mouth that pulled the lips thin." | | 1 | "Up close the changes sharpened: a gold band on the left hand, a faint swell under the coat that the fabric tried to hide, eyes that had learned to look past peo…" | | 2 | "The delivery jacket, the rented room above this bar, the part-time hours that left her mind free to turn over problems no one else saw." | | 3 | "The bar’s hidden door, the bookshelf that wasn’t only a bookshelf, sat in Rory’s peripheral vision." | | 4 | "Rory thought of her own calculations: routes that avoided cameras, the way she clocked exits in every restaurant she delivered to, the cool that let her think t…" | | 5 | "His back to them, he reorganised the optics with the precision of a man who had once organised other things." | | 6 | "He said nothing, but his glance at Rory lasted a second longer than necessary, the look of a man who had seen old friends walk through doors before and known th…" |
| |
| 93.75% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 1 | | matches | | 0 | "Eva’s voice stayed, but her knuckles whitened on the tumbler" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 69 | | tagDensity | 0.13 | | leniency | 0.261 | | rawRatio | 0.111 | | effectiveRatio | 0.029 | |