| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 38 | | tagDensity | 0.368 | | leniency | 0.737 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1155 | | 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) | |
| 61.04% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1155 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "disrupting" | | 1 | "footsteps" | | 2 | "lilt" | | 3 | "silk" | | 4 | "synthetic" | | 5 | "weight" | | 6 | "familiar" | | 7 | "silence" | | 8 | "warmth" |
| |
| 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 | 75 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 75 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 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 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1148 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 51 | | wordCount | 767 | | uniqueNames | 11 | | maxNameDensity | 2.48 | | worstName | "Rory" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Golden | 1 | | Empress | 1 | | Rory | 19 | | October | 1 | | Welsh | 1 | | Mayfair | 1 | | Gemma | 18 | | Silas | 6 |
| | persons | | 0 | "Raven" | | 1 | "Rory" | | 2 | "Gemma" | | 3 | "Silas" |
| | places | | | globalScore | 0.261 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1148 | | 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 | 46 | | mean | 24.96 | | std | 19.79 | | cv | 0.793 | | sampleLengths | | 0 | 81 | | 1 | 73 | | 2 | 7 | | 3 | 38 | | 4 | 34 | | 5 | 1 | | 6 | 32 | | 7 | 39 | | 8 | 6 | | 9 | 39 | | 10 | 4 | | 11 | 49 | | 12 | 42 | | 13 | 11 | | 14 | 9 | | 15 | 15 | | 16 | 45 | | 17 | 4 | | 18 | 3 | | 19 | 4 | | 20 | 34 | | 21 | 45 | | 22 | 10 | | 23 | 5 | | 24 | 60 | | 25 | 28 | | 26 | 6 | | 27 | 16 | | 28 | 4 | | 29 | 3 | | 30 | 43 | | 31 | 4 | | 32 | 31 | | 33 | 12 | | 34 | 53 | | 35 | 5 | | 36 | 29 | | 37 | 29 | | 38 | 45 | | 39 | 31 | | 40 | 14 | | 41 | 5 | | 42 | 24 | | 43 | 27 | | 44 | 33 | | 45 | 16 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 75 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 126 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 99 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 774 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, crescent-shaped scar" |
| | adverbCount | 15 | | adverbRatio | 0.01937984496124031 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.007751937984496124 | |
| 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 | 11.6 | | std | 7.73 | | cv | 0.666 | | sampleLengths | | 0 | 22 | | 1 | 18 | | 2 | 7 | | 3 | 13 | | 4 | 21 | | 5 | 12 | | 6 | 11 | | 7 | 12 | | 8 | 25 | | 9 | 7 | | 10 | 6 | | 11 | 7 | | 12 | 24 | | 13 | 14 | | 14 | 13 | | 15 | 5 | | 16 | 16 | | 17 | 1 | | 18 | 2 | | 19 | 16 | | 20 | 2 | | 21 | 12 | | 22 | 5 | | 23 | 12 | | 24 | 10 | | 25 | 12 | | 26 | 6 | | 27 | 27 | | 28 | 12 | | 29 | 4 | | 30 | 35 | | 31 | 14 | | 32 | 8 | | 33 | 28 | | 34 | 6 | | 35 | 11 | | 36 | 4 | | 37 | 5 | | 38 | 15 | | 39 | 20 | | 40 | 25 | | 41 | 4 | | 42 | 3 | | 43 | 4 | | 44 | 9 | | 45 | 25 | | 46 | 4 | | 47 | 12 | | 48 | 8 | | 49 | 9 |
| |
| 42.93% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.29292929292929293 | | totalSentences | 99 | | uniqueOpeners | 29 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 71 | | matches | | 0 | "She scraped her thumbnail across" | | 1 | "Her windbreaker carried the thick," | | 2 | "His silver signet ring clacked" | | 3 | "He moved down the length" | | 4 | "He slid a rocks glass" | | 5 | "Her straight, shoulder-length black hair" | | 6 | "She wore a tailored camel" | | 7 | "Her posture mirrored the rigid" | | 8 | "He set a fresh coaster" | | 9 | "He didn't ask for her" | | 10 | "He retreated to the far" | | 11 | "Her nose wrinkled at the" | | 12 | "She set the glass down" | | 13 | "She looked older, burdened by" | | 14 | "Her knuckles whitened around the" | | 15 | "She set the glass down," | | 16 | "She reached into her pocket," | | 17 | "He offered a single, almost" | | 18 | "Her hand gripped the tarnished" | | 19 | "She looked over her shoulder," |
| | ratio | 0.282 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 71 | | matches | | 0 | "The distinctive green neon sign" | | 1 | "Rory sat on a worn" | | 2 | "She scraped her thumbnail across" | | 3 | "Her windbreaker carried the thick," | | 4 | "Silas stood across the counter," | | 5 | "His silver signet ring clacked" | | 6 | "The grey streaks in his" | | 7 | "He moved down the length" | | 8 | "He slid a rocks glass" | | 9 | "Amber liquid sloshed against the" | | 10 | "The brass bell above the" | | 11 | "A rush of damp October" | | 12 | "Rory kept her bright blue" | | 13 | "Footsteps fell heavy against the" | | 14 | "The newcomer stopped behind Rory." | | 15 | "A scent of expensive bergamot" | | 16 | "The syllables carried a crisp" | | 17 | "Her straight, shoulder-length black hair" | | 18 | "Gemma stood two feet away." | | 19 | "She wore a tailored camel" |
| | ratio | 0.986 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 1 | | matches | | 0 | "He retreated to the far end of the counter, picking up a newspaper and leaning against the heavy oak bookshelf that concealed the back room." |
| |
| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 1 | | matches | | 0 | "Gemma continued, her voice dropping" |
| |
| 97.37% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "Gemma continued (continue)" | | 1 | "Gemma whispered (whisper)" |
| | dialogueSentences | 38 | | tagDensity | 0.053 | | leniency | 0.105 | | rawRatio | 1 | | effectiveRatio | 0.105 | |