| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva gestured vaguely [vaguely]" |
| | dialogueSentences | 42 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0.056 | | effectiveRatio | 0.048 | |
| 95.99% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1247 | | 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) | |
| 51.88% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1247 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "velvet" | | 1 | "echoing" | | 2 | "quivered" | | 3 | "perfect" | | 4 | "crystal" | | 5 | "scanned" | | 6 | "standard" | | 7 | "tracing" | | 8 | "whisper" |
| |
| 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 | 92 | | matches | (empty) | |
| 96.27% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 92 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 115 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1246 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 34.53% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 866 | | uniqueNames | 14 | | maxNameDensity | 2.31 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 20 | | Veil | 3 | | Market | 1 | | Tube | 1 | | Camden | 1 | | Morris | 3 | | Compass | 1 | | Kowalski | 1 | | Eva | 14 | | Oxford | 1 | | London | 1 | | Markets | 1 | | Shade | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Morris" | | 4 | "Kowalski" | | 5 | "Eva" |
| | places | | 0 | "Compass" | | 1 | "Oxford" | | 2 | "London" |
| | globalScore | 0.345 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 39.49% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.605 | | wordCount | 1246 | | matches | | 0 | "Not the blood, but the lapel" | | 1 | "not at a wall, but at a rift" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 115 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 31.15 | | std | 17.41 | | cv | 0.559 | | sampleLengths | | 0 | 76 | | 1 | 39 | | 2 | 21 | | 3 | 43 | | 4 | 21 | | 5 | 52 | | 6 | 7 | | 7 | 5 | | 8 | 47 | | 9 | 18 | | 10 | 9 | | 11 | 44 | | 12 | 29 | | 13 | 45 | | 14 | 48 | | 15 | 17 | | 16 | 9 | | 17 | 23 | | 18 | 33 | | 19 | 14 | | 20 | 36 | | 21 | 51 | | 22 | 6 | | 23 | 7 | | 24 | 36 | | 25 | 58 | | 26 | 30 | | 27 | 26 | | 28 | 24 | | 29 | 71 | | 30 | 32 | | 31 | 34 | | 32 | 21 | | 33 | 10 | | 34 | 41 | | 35 | 16 | | 36 | 42 | | 37 | 42 | | 38 | 21 | | 39 | 42 |
| |
| 86.19% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 92 | | matches | | 0 | "was gone" | | 1 | "was frozen" | | 2 | "been withdrawn" | | 3 | "was posted" | | 4 | "been killed" |
| |
| 59.15% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 142 | | matches | | 0 | "wasn’t pointing" | | 1 | "weren’t adding" | | 2 | "were assembling" |
| |
| 68.32% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 2 | | flaggedSentences | 3 | | totalSentences | 115 | | ratio | 0.026 | | matches | | 0 | "The compass in his grip wasn’t pointing north; its needle quivered, pointing at a bare, brick wall." | | 1 | "The man hadn’t been killed for his purchase; his purchase had made him a conduit." | | 2 | "The perfect blood pool, the stopped watch, the hollow brick—it was a pattern, a circuit." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 405 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.019753086419753086 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0024691358024691358 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 115 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 115 | | mean | 10.83 | | std | 7.26 | | cv | 0.67 | | sampleLengths | | 0 | 8 | | 1 | 20 | | 2 | 22 | | 3 | 26 | | 4 | 13 | | 5 | 11 | | 6 | 9 | | 7 | 6 | | 8 | 21 | | 9 | 12 | | 10 | 21 | | 11 | 10 | | 12 | 8 | | 13 | 13 | | 14 | 12 | | 15 | 5 | | 16 | 6 | | 17 | 17 | | 18 | 3 | | 19 | 9 | | 20 | 4 | | 21 | 3 | | 22 | 5 | | 23 | 11 | | 24 | 18 | | 25 | 18 | | 26 | 11 | | 27 | 7 | | 28 | 9 | | 29 | 13 | | 30 | 31 | | 31 | 10 | | 32 | 19 | | 33 | 15 | | 34 | 12 | | 35 | 18 | | 36 | 21 | | 37 | 4 | | 38 | 7 | | 39 | 2 | | 40 | 3 | | 41 | 11 | | 42 | 9 | | 43 | 4 | | 44 | 4 | | 45 | 5 | | 46 | 4 | | 47 | 10 | | 48 | 13 | | 49 | 3 |
| |
| 54.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.3739130434782609 | | totalSentences | 115 | | uniqueOpeners | 43 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 85 | | matches | | 0 | "Her partner, DS Morris, would" | | 1 | "He’d whispered about things like" | | 2 | "His face was frozen in" | | 3 | "She’d seen one in Morris’s" | | 4 | "She tucked a curly red" | | 5 | "She avoided looking at the" | | 6 | "She circled the body." | | 7 | "She scanned the floor around" | | 8 | "She walked over, her gaze" | | 9 | "She pulled on a glove" | | 10 | "It sounded hollow." | | 11 | "Her eyes, trained by eighteen" | | 12 | "They were assembling into a" | | 13 | "She looked back at the" | | 14 | "She met Quinn’s gaze, a" | | 15 | "It was in the two" |
| | ratio | 0.188 | |
| 24.71% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 85 | | matches | | 0 | "The air tasted of ozone" | | 1 | "Detective Harlow Quinn stood at" | | 2 | "The Veil Market, tucked into" | | 3 | "The usual hum of hushed" | | 4 | "Her partner, DS Morris, would" | | 5 | "He’d whispered about things like" | | 6 | "Quinn had filed his words" | | 7 | "That was before the unexplained" | | 8 | "The voice, crisp and professional," | | 9 | "Quinn ducked under the tape," | | 10 | "The victim lay in a" | | 11 | "His face was frozen in" | | 12 | "the constable reported" | | 13 | "Quinn crouched, her sharp jaw" | | 14 | "The positioning was too neat." | | 15 | "The compass in his grip" | | 16 | "A Veil Compass." | | 17 | "She’d seen one in Morris’s" | | 18 | "A rustle of fabric and" | | 19 | "Eva Kowalski emerged from the" |
| | ratio | 0.871 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 1 | | matches | | 0 | "It was in the two women standing over it, one representing the law, the other the lore, and the dead man between them holding a compass that had just changed it…" |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 6 | | matches | | 0 | "Eva insisted, her freckles standing out on her pale skin" | | 1 | "Eva said, her voice gaining a quiet urgency" | | 2 | "Eva had, her satchel bumping against her hip" | | 3 | "Quinn said, the words coming out slow" | | 4 | "Eva said, her voice barely a whisper" | | 5 | "Quinn replied, but her eyes were on the compass" |
| |
| 30.95% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 5 | | fancyTags | | 0 | "the constable reported (report)" | | 1 | "Eva insisted (insist)" | | 2 | "Quinn noted (note)" | | 3 | "Eva murmured (murmur)" | | 4 | "Quinn ordered (order)" |
| | dialogueSentences | 42 | | tagDensity | 0.31 | | leniency | 0.619 | | rawRatio | 0.385 | | effectiveRatio | 0.238 | |