| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 97.09% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1719 | | 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) | |
| 56.37% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1719 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "gloom" | | 1 | "weight" | | 2 | "measured" | | 3 | "pulse" | | 4 | "silence" | | 5 | "calculate" | | 6 | "warmth" | | 7 | "glint" | | 8 | "chill" | | 9 | "tension" | | 10 | "traced" |
| |
| 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 | 279 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 7 | | hedgeCount | 0 | | narrationSentences | 279 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 279 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 3 | | totalWords | 1719 | | ratio | 0.002 | | matches | | 0 | "The Avaros Concordance" |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 1719 | | uniqueNames | 10 | | maxNameDensity | 1.22 | | worstName | "You" | | maxWindowNameDensity | 3.5 | | worstWindowName | "You" | | discoveredNames | | Avaros | 1 | | Wapping | 1 | | High | 1 | | Street | 1 | | Lucien | 4 | | Soho | 2 | | London | 1 | | Marseille | 1 | | Shoreditch | 1 | | You | 21 |
| | persons | | | places | | 0 | "Wapping" | | 1 | "High" | | 2 | "Street" | | 3 | "Soho" | | 4 | "London" | | 5 | "Marseille" | | 6 | "Shoreditch" |
| | globalScore | 0.889 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 138 | | 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 | 1719 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 279 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 67 | | mean | 25.66 | | std | 21.94 | | cv | 0.855 | | sampleLengths | | 0 | 31 | | 1 | 50 | | 2 | 3 | | 3 | 34 | | 4 | 3 | | 5 | 62 | | 6 | 4 | | 7 | 4 | | 8 | 66 | | 9 | 8 | | 10 | 7 | | 11 | 59 | | 12 | 6 | | 13 | 9 | | 14 | 13 | | 15 | 50 | | 16 | 9 | | 17 | 61 | | 18 | 4 | | 19 | 4 | | 20 | 74 | | 21 | 6 | | 22 | 53 | | 23 | 29 | | 24 | 21 | | 25 | 6 | | 26 | 3 | | 27 | 28 | | 28 | 5 | | 29 | 23 | | 30 | 50 | | 31 | 5 | | 32 | 27 | | 33 | 38 | | 34 | 18 | | 35 | 55 | | 36 | 4 | | 37 | 5 | | 38 | 1 | | 39 | 57 | | 40 | 59 | | 41 | 8 | | 42 | 2 | | 43 | 2 | | 44 | 47 | | 45 | 33 | | 46 | 36 | | 47 | 5 | | 48 | 5 | | 49 | 9 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 279 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 325 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 279 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1721 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.01801278326554329 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.003486345148169669 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 279 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 279 | | mean | 6.16 | | std | 3.25 | | cv | 0.528 | | sampleLengths | | 0 | 9 | | 1 | 3 | | 2 | 14 | | 3 | 5 | | 4 | 10 | | 5 | 5 | | 6 | 11 | | 7 | 7 | | 8 | 9 | | 9 | 8 | | 10 | 3 | | 11 | 10 | | 12 | 10 | | 13 | 10 | | 14 | 4 | | 15 | 3 | | 16 | 3 | | 17 | 3 | | 18 | 6 | | 19 | 7 | | 20 | 7 | | 21 | 6 | | 22 | 8 | | 23 | 7 | | 24 | 15 | | 25 | 4 | | 26 | 4 | | 27 | 9 | | 28 | 10 | | 29 | 10 | | 30 | 4 | | 31 | 1 | | 32 | 23 | | 33 | 9 | | 34 | 8 | | 35 | 7 | | 36 | 4 | | 37 | 11 | | 38 | 5 | | 39 | 8 | | 40 | 4 | | 41 | 27 | | 42 | 6 | | 43 | 9 | | 44 | 8 | | 45 | 2 | | 46 | 3 | | 47 | 4 | | 48 | 6 | | 49 | 7 |
| |
| 25.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 86 | | diversityRatio | 0.14695340501792115 | | totalSentences | 279 | | uniqueOpeners | 41 | |
| 38.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 261 | | matches | | 0 | "Ever since that night in" | | 1 | "Then we do it your" | | 2 | "Then do not cross it" |
| | ratio | 0.011 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 166 | | totalSentences | 261 | | matches | | 0 | "He held an ivory-handled cane" | | 1 | "You came back." | | 2 | "She kept her weight on" | | 3 | "Her thumb found the crescent" | | 4 | "She rubbed it raw." | | 5 | "I had to." | | 6 | "He stepped forward." | | 7 | "She stepped back." | | 8 | "His polished oxfords pressed against" | | 9 | "He did not shrug off" | | 10 | "You blocked my number." | | 11 | "I deleted them all." | | 12 | "He set the cane against" | | 13 | "He ran a gloved finger" | | 14 | "His movements stayed measured." | | 15 | "You said you could not" | | 16 | "I said you would not" | | 17 | "He turned his head." | | 18 | "He looked at the scar" | | 19 | "He always noticed it." |
| | ratio | 0.636 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 245 | | totalSentences | 261 | | matches | | 0 | "The first deadbolt slid back" | | 1 | "The second followed." | | 2 | "The third resisted, sticking in" | | 3 | "Rory pulled the door inward." | | 4 | "Lucien stood on the other" | | 5 | "Charcoal wool swallowed his frame." | | 6 | "Platinum blond hair caught the" | | 7 | "The other held the flat" | | 8 | "He held an ivory-handled cane" | | 9 | "You came back." | | 10 | "The words left her mouth" | | 11 | "She kept her weight on" | | 12 | "Her thumb found the crescent" | | 13 | "She rubbed it raw." | | 14 | "I had to." | | 15 | "He stepped forward." | | 16 | "She stepped back." | | 17 | "The door clicked shut behind" | | 18 | "His polished oxfords pressed against" | | 19 | "He did not shrug off" |
| | ratio | 0.939 | |
| 57.47% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 261 | | matches | | 0 | "If I had stayed, they" | | 1 | "If I fall through the" | | 2 | "If the iron bends, you" |
| | ratio | 0.011 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 1 | | matches | | 0 | "The same restraint that had kept him at arm’s length three months ago in the rain outside the warehouse on Wapping High Street." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |