| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1171 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1171 | | totalAiIsms | 26 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "loomed" | | 1 | "familiar" | | 2 | "silence" | | 3 | "traced" | | 4 | "pulsed" | | 5 | "vibrated" | | 6 | "rhythmic" | | 7 | "warmth" | | 8 | "echoed" | | 9 | "scanned" | | 10 | "processed" | | 11 | "flickered" | | 12 | "searing" | | 13 | "profound" | | 14 | "weight" | | 15 | "pulse" | | 16 | "race" | | 17 | "cataloged" | | 18 | "mechanical" |
| |
| 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 | 129 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 129 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 132 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1158 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1139 | | uniqueNames | 10 | | maxNameDensity | 0.97 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Park | 2 | | London | 1 | | Richmond | 3 | | Silas | 1 | | Heartstone | 3 | | Fae | 3 | | Hel | 2 | | Earth-bound | 1 | | Cardiff | 1 | | Rory | 11 |
| | persons | | 0 | "Silas" | | 1 | "Heartstone" | | 2 | "Rory" |
| | places | | 0 | "Park" | | 1 | "London" | | 2 | "Richmond" | | 3 | "Fae" | | 4 | "Earth-bound" | | 5 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 86 | | 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 | 1158 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 132 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 34.06 | | std | 25.05 | | cv | 0.736 | | sampleLengths | | 0 | 48 | | 1 | 81 | | 2 | 63 | | 3 | 7 | | 4 | 44 | | 5 | 1 | | 6 | 33 | | 7 | 7 | | 8 | 30 | | 9 | 10 | | 10 | 2 | | 11 | 77 | | 12 | 12 | | 13 | 39 | | 14 | 43 | | 15 | 9 | | 16 | 60 | | 17 | 98 | | 18 | 13 | | 19 | 52 | | 20 | 4 | | 21 | 70 | | 22 | 17 | | 23 | 38 | | 24 | 41 | | 25 | 14 | | 26 | 43 | | 27 | 29 | | 28 | 7 | | 29 | 29 | | 30 | 11 | | 31 | 62 | | 32 | 39 | | 33 | 25 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 129 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 184 | | matches | (empty) | |
| 99.57% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 132 | | ratio | 0.015 | | matches | | 0 | "Yu-Fei’s restaurant, Silas’s bar, the flat in the city—none of it felt secure anymore." | | 1 | "Someone—or something—paced the perimeter of the standing stones, keeping just outside her direct line of sight." |
| |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1152 | | adjectiveStacks | 2 | | stackExamples | | 0 | "rhythmic, uneven slide-and-thud." | | 1 | "tight over jagged, protruding" |
| | adverbCount | 31 | | adverbRatio | 0.026909722222222224 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.010416666666666666 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 132 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 132 | | mean | 8.77 | | std | 5.23 | | cv | 0.597 | | sampleLengths | | 0 | 9 | | 1 | 5 | | 2 | 19 | | 3 | 2 | | 4 | 7 | | 5 | 6 | | 6 | 10 | | 7 | 14 | | 8 | 5 | | 9 | 8 | | 10 | 20 | | 11 | 10 | | 12 | 4 | | 13 | 10 | | 14 | 5 | | 15 | 10 | | 16 | 6 | | 17 | 20 | | 18 | 14 | | 19 | 8 | | 20 | 7 | | 21 | 17 | | 22 | 5 | | 23 | 12 | | 24 | 2 | | 25 | 8 | | 26 | 1 | | 27 | 7 | | 28 | 7 | | 29 | 12 | | 30 | 7 | | 31 | 7 | | 32 | 5 | | 33 | 14 | | 34 | 11 | | 35 | 5 | | 36 | 5 | | 37 | 2 | | 38 | 2 | | 39 | 11 | | 40 | 3 | | 41 | 14 | | 42 | 14 | | 43 | 11 | | 44 | 9 | | 45 | 2 | | 46 | 10 | | 47 | 1 | | 48 | 8 | | 49 | 4 |
| |
| 41.92% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.3333333333333333 | | totalSentences | 132 | | uniqueOpeners | 44 | |
| 86.96% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 115 | | matches | | 0 | "Just a void wrapped in" | | 1 | "Pale, translucent flesh stretched tight" | | 2 | "Then, three more shadows peeled" |
| | ratio | 0.026 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 115 | | matches | | 0 | "She stepped past the petrified" | | 1 | "Her thumb traced the crescent-shaped" | | 2 | "She came here for a" | | 3 | "She brought the object back" | | 4 | "Her bright blue eyes scanned" | | 5 | "She possessed no weapons, just" | | 6 | "Her legal-trained mind demanded logic," | | 7 | "She noted the distance to" | | 8 | "She spotted a dense thicket" | | 9 | "She kept her gaze fixed" | | 10 | "She focused on the gaps" | | 11 | "Her brain processed the shadows" | | 12 | "She unzipped her jacket pocket," | | 13 | "She tapped the flashlight icon." | | 14 | "She risked standing in this" | | 15 | "It echoed from the opposite" | | 16 | "She ignored the pain." | | 17 | "It stood too tall." | | 18 | "It didn't step forward." | | 19 | "It glided, the ongoing dragging" |
| | ratio | 0.217 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 107 | | totalSentences | 115 | | matches | | 0 | "Richmond Park stretched into a" | | 1 | "Rory stood at the perimeter." | | 2 | "The ancient oak standing stones" | | 3 | "The boundary line into a" | | 4 | "She stepped past the petrified" | | 5 | "The air shifted the moment" | | 6 | "The familiar hum of London" | | 7 | "Silence slammed into her ears." | | 8 | "An unnatural, suffocating quiet hung" | | 9 | "The blossoms opened wide, drinking" | | 10 | "Fae territory bred impossibilities." | | 11 | "Winter or summer, the Richmond" | | 12 | "Rory rubbed her left wrist." | | 13 | "Her thumb traced the crescent-shaped" | | 14 | "She came here for a" | | 15 | "The unknown benefactor who dropped" | | 16 | "Yu-Fei’s restaurant, Silas’s bar, the" | | 17 | "She brought the object back" | | 18 | "Rory hooked a finger under" | | 19 | "The deep crimson facets pulsed." |
| | ratio | 0.93 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 115 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 2 | | matches | | 0 | "The unknown benefactor who dropped the artifact into her life needed to answer for the chaos unspooling in her wake." | | 1 | "The certainty of outnumbering, of being hunted by things that defied natural law, settled heavy in her gut." |
| |
| 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 | |