| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 139 | | tagDensity | 0.115 | | leniency | 0.23 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1982 | | 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) | |
| 87.39% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1982 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "eyebrow" | | 1 | "unsettled" | | 2 | "flicked" | | 3 | "familiar" | | 4 | "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 | 138 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 138 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 261 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1982 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 33 | | unquotedAttributions | 1 | | matches | | 0 | "At the far end of the bar, Silas asked the new couple what they wanted." |
| |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 90 | | wordCount | 1233 | | uniqueNames | 7 | | maxNameDensity | 3.33 | | worstName | "Rory" | | maxWindowNameDensity | 5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 41 | | London | 1 | | Silas | 8 | | Eva | 37 | | Cardiff | 1 | | Evan | 1 | | Nest | 1 |
| | persons | | 0 | "Rory" | | 1 | "Silas" | | 2 | "Eva" | | 3 | "Evan" | | 4 | "Nest" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 88 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like someone opening a drawer and" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1982 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 261 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 176 | | mean | 11.26 | | std | 13.23 | | cv | 1.175 | | sampleLengths | | 0 | 52 | | 1 | 16 | | 2 | 5 | | 3 | 11 | | 4 | 4 | | 5 | 82 | | 6 | 9 | | 7 | 4 | | 8 | 57 | | 9 | 1 | | 10 | 24 | | 11 | 8 | | 12 | 1 | | 13 | 20 | | 14 | 12 | | 15 | 6 | | 16 | 9 | | 17 | 16 | | 18 | 14 | | 19 | 6 | | 20 | 12 | | 21 | 9 | | 22 | 16 | | 23 | 7 | | 24 | 32 | | 25 | 14 | | 26 | 15 | | 27 | 6 | | 28 | 3 | | 29 | 6 | | 30 | 2 | | 31 | 7 | | 32 | 47 | | 33 | 61 | | 34 | 7 | | 35 | 16 | | 36 | 4 | | 37 | 9 | | 38 | 2 | | 39 | 27 | | 40 | 43 | | 41 | 7 | | 42 | 3 | | 43 | 4 | | 44 | 5 | | 45 | 1 | | 46 | 11 | | 47 | 2 | | 48 | 2 | | 49 | 5 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 138 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 216 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 261 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1238 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.025848142164781908 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0024232633279483036 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 261 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 261 | | mean | 7.59 | | std | 5.9 | | cv | 0.776 | | sampleLengths | | 0 | 19 | | 1 | 13 | | 2 | 20 | | 3 | 7 | | 4 | 9 | | 5 | 5 | | 6 | 11 | | 7 | 4 | | 8 | 5 | | 9 | 17 | | 10 | 14 | | 11 | 19 | | 12 | 6 | | 13 | 21 | | 14 | 9 | | 15 | 4 | | 16 | 7 | | 17 | 26 | | 18 | 9 | | 19 | 15 | | 20 | 1 | | 21 | 5 | | 22 | 6 | | 23 | 13 | | 24 | 8 | | 25 | 1 | | 26 | 5 | | 27 | 15 | | 28 | 7 | | 29 | 5 | | 30 | 6 | | 31 | 9 | | 32 | 16 | | 33 | 6 | | 34 | 8 | | 35 | 6 | | 36 | 12 | | 37 | 9 | | 38 | 7 | | 39 | 9 | | 40 | 3 | | 41 | 4 | | 42 | 11 | | 43 | 9 | | 44 | 12 | | 45 | 14 | | 46 | 9 | | 47 | 6 | | 48 | 6 | | 49 | 3 |
| |
| 44.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.21839080459770116 | | totalSentences | 261 | | uniqueOpeners | 57 | |
| 54.64% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 122 | | matches | | 0 | "Somewhere behind the bar, Silas" | | 1 | "Instead there was only the" |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 122 | | matches | | 0 | "His silver ring flashed each" | | 1 | "She had taken off her" | | 2 | "Her hair, once a bright" | | 3 | "She wore a dark suit" | | 4 | "She saw, too, how little" | | 5 | "It didn’t sound like a" | | 6 | "It sounded like someone opening" | | 7 | "His gaze moved from one" | | 8 | "He collected her jacket before" | | 9 | "Her gloves had stopped turning" | | 10 | "She pulled out a stool" | | 11 | "Her hands were still fine-boned," | | 12 | "He leaned one elbow on" | | 13 | "She had worn it smooth." | | 14 | "He didn’t look over." | | 15 | "Her fingers pressed into each" | | 16 | "His voice carried no strain," | | 17 | "She wanted to hear something" | | 18 | "She wanted a list of" | | 19 | "Her phone sat charging beside" |
| | ratio | 0.189 | |
| 5.08% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 111 | | totalSentences | 122 | | matches | | 0 | "Rain ran off Rory’s jacket" | | 1 | "The green neon sign outside" | | 2 | "Silas polished a glass with" | | 3 | "His silver ring flashed each" | | 4 | "Rory glanced towards the door." | | 5 | "A woman stood beneath the" | | 6 | "She had taken off her" | | 7 | "Her hair, once a bright" | | 8 | "A pale line crossed one" | | 9 | "She wore a dark suit" | | 10 | "Rory’s hand stopped on the" | | 11 | "The woman looked up." | | 12 | "Rory saw the old face" | | 13 | "She saw, too, how little" | | 14 | "Eva’s still held the room" | | 15 | "The name came out quiet." | | 16 | "It didn’t sound like a" | | 17 | "It sounded like someone opening" | | 18 | "Rory pulled her wet jacket" | | 19 | "Silas set the glass down." |
| | ratio | 0.91 | |
| 40.98% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 122 | | matches | | 0 | "Now she sat inside it." |
| | ratio | 0.008 | |
| 74.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 4 | | matches | | 0 | "Her hair, once a bright copper braid that had swung against her back, was cut close to her head." | | 1 | "Rory saw the old face beneath the new lines: the sharp chin, the dimple that appeared on one side when a smile got away from her." | | 2 | "Rory tried to picture the girl she’d known: copper braid, chipped black nail polish, a laugh that could outrun a teacher’s reprimand." | | 3 | "Rory could smell the damp wool of her jacket hanging somewhere behind the bar, the faint scent of fried garlic from the kitchen clinging to her delivery bag." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 139 | | tagDensity | 0.101 | | leniency | 0.201 | | rawRatio | 0.071 | | effectiveRatio | 0.014 | |