| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.41% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 894 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 38.48% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 894 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "pulsed" | | 1 | "warmth" | | 2 | "silence" | | 3 | "predator" | | 4 | "weight" | | 5 | "throbbed" | | 6 | "traced" | | 7 | "glinting" |
| |
| 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 | 116 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 116 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 120 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 7 | | totalWords | 887 | | ratio | 0.008 | | matches | | 0 | "When it burns, go to the Grove." |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 93.12% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 879 | | uniqueNames | 10 | | maxNameDensity | 1.14 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 10 | | Richmond | 1 | | Park | 1 | | Grove | 3 | | December | 1 | | London | 2 | | Cardiff | 1 | | Evan | 2 | | Silas | 1 | | Thames | 1 |
| | persons | | | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Grove" | | 3 | "December" | | 4 | "London" | | 5 | "Cardiff" | | 6 | "Thames" |
| | globalScore | 0.931 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 87.26% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.127 | | wordCount | 887 | | matches | | 0 | "Not the stones, she saw now, but the space between them" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 120 | | matches | | 0 | "hated that habit" | | 1 | "knew that ring" |
| |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 25.34 | | std | 22.5 | | cv | 0.888 | | sampleLengths | | 0 | 41 | | 1 | 16 | | 2 | 75 | | 3 | 4 | | 4 | 50 | | 5 | 1 | | 6 | 19 | | 7 | 44 | | 8 | 4 | | 9 | 36 | | 10 | 33 | | 11 | 3 | | 12 | 42 | | 13 | 3 | | 14 | 76 | | 15 | 3 | | 16 | 63 | | 17 | 1 | | 18 | 2 | | 19 | 43 | | 20 | 11 | | 21 | 26 | | 22 | 55 | | 23 | 47 | | 24 | 1 | | 25 | 6 | | 26 | 55 | | 27 | 7 | | 28 | 37 | | 29 | 5 | | 30 | 10 | | 31 | 29 | | 32 | 14 | | 33 | 17 | | 34 | 8 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 116 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 160 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 120 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 886 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 12 | | adverbRatio | 0.013544018058690745 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.007900677200902935 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 120 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 120 | | mean | 7.39 | | std | 6.89 | | cv | 0.931 | | sampleLengths | | 0 | 16 | | 1 | 2 | | 2 | 23 | | 3 | 5 | | 4 | 11 | | 5 | 38 | | 6 | 2 | | 7 | 15 | | 8 | 20 | | 9 | 4 | | 10 | 17 | | 11 | 11 | | 12 | 6 | | 13 | 4 | | 14 | 12 | | 15 | 1 | | 16 | 14 | | 17 | 5 | | 18 | 3 | | 19 | 11 | | 20 | 6 | | 21 | 6 | | 22 | 10 | | 23 | 8 | | 24 | 4 | | 25 | 2 | | 26 | 4 | | 27 | 17 | | 28 | 4 | | 29 | 1 | | 30 | 8 | | 31 | 17 | | 32 | 5 | | 33 | 4 | | 34 | 5 | | 35 | 1 | | 36 | 1 | | 37 | 2 | | 38 | 1 | | 39 | 5 | | 40 | 18 | | 41 | 6 | | 42 | 1 | | 43 | 5 | | 44 | 7 | | 45 | 3 | | 46 | 5 | | 47 | 13 | | 48 | 7 | | 49 | 22 |
| |
| 65.28% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.44166666666666665 | | totalSentences | 120 | | uniqueOpeners | 53 | |
| 37.45% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 89 | | matches | | 0 | "Instead, she watched the wildflowers." |
| | ratio | 0.011 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 89 | | matches | | 0 | "Her fingers found the pendant." | | 1 | "She'd followed the warmth for" | | 2 | "They carpeted the clearing, snowdrops" | | 3 | "She checked her watch." | | 4 | "Her voice died in the" | | 5 | "She stepped between two stones." | | 6 | "She touched the crescent scar" | | 7 | "She forced her hand down." | | 8 | "She caught it in her" | | 9 | "Her heart hammered against her" | | 10 | "She wanted to rip it" | | 11 | "It had arrived three weeks" | | 12 | "It burned now." | | 13 | "Her legal mind grasped for" | | 14 | "She reached the centre." | | 15 | "She knew better." | | 16 | "They bent, stems bowing in" | | 17 | "She'd been eight." | | 18 | "They led from the archway" | | 19 | "She knew that ring." |
| | ratio | 0.247 | |
| 61.12% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 89 | | matches | | 0 | "The silver chain bit into" | | 1 | "The standing stones stood ahead," | | 2 | "Her fingers found the pendant." | | 3 | "The crimson gemstone pulsed against" | | 4 | "She'd followed the warmth for" | | 5 | "Isolde's Grove, the delivery drivers" | | 6 | "Rory had dismissed those stories" | | 7 | "The wildflowers proved otherwise." | | 8 | "They carpeted the clearing, snowdrops" | | 9 | "Rory's breath misted in the" | | 10 | "She checked her watch." | | 11 | "The minute hand spun backwards," | | 12 | "Her voice died in the" | | 13 | "She stepped between two stones." | | 14 | "The temperature dropped." | | 15 | "The crimson gem flared, casting" | | 16 | "Rory's training kicked in, analytical," | | 17 | "The warmth increased with proximity" | | 18 | "Something rustled behind her." | | 19 | "The archway gaped empty." |
| | ratio | 0.798 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 89 | | matches | (empty) | | ratio | 0 | |
| 12.99% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 6 | | matches | | 0 | "Isolde's Grove, the delivery drivers called it when they spoke of shortcuts that cost hours." | | 1 | "Rory had dismissed those stories as urban legend, the kind of bollocks that kept minimum wage workers entertained between orders." | | 2 | "They carpeted the clearing, snowdrops and bluebells and foxgloves blooming together in a riot that ignored season." | | 3 | "But her instincts, the primal survival mechanisms that had driven her from Cardiff to London, from Evan's fists to Silas's spare flat above the bar, those insti…" | | 4 | "Something approached in a winding path, feet that didn't touch earth, displacing air with the weight of centuries." | | 5 | "The grove pulled at her thoughts, rifling through her history like a prosecutor searching for weakness." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |