| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1518 | | 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) | |
| 76.94% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1518 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "pulse" | | 1 | "warmth" | | 2 | "footsteps" | | 3 | "raced" | | 4 | "loomed" |
| |
| 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 | 161 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 161 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 164 | | 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 | 0 | | markdownWords | 0 | | totalWords | 1518 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 1509 | | uniqueNames | 13 | | maxNameDensity | 0.86 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 2 | | Park | 2 | | Golden | 1 | | Empress | 1 | | Rory | 13 | | Dymas | 1 | | Hel | 1 | | London | 1 | | Fae | 1 | | Grove | 1 | | Wildflowers | 2 | | Silas | 1 | | Eva | 2 |
| | persons | | 0 | "Rory" | | 1 | "Wildflowers" | | 2 | "Silas" | | 3 | "Eva" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Golden" | | 3 | "Dymas" | | 4 | "Hel" | | 5 | "London" | | 6 | "Fae" | | 7 | "Grove" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 118 | | 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 | 1518 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 164 | | matches | | 0 | "heard that it" | | 1 | "saw that its" |
| |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 61 | | mean | 24.89 | | std | 19.03 | | cv | 0.765 | | sampleLengths | | 0 | 7 | | 1 | 44 | | 2 | 30 | | 3 | 6 | | 4 | 74 | | 5 | 17 | | 6 | 62 | | 7 | 19 | | 8 | 8 | | 9 | 45 | | 10 | 3 | | 11 | 35 | | 12 | 41 | | 13 | 7 | | 14 | 53 | | 15 | 8 | | 16 | 13 | | 17 | 30 | | 18 | 2 | | 19 | 3 | | 20 | 68 | | 21 | 25 | | 22 | 27 | | 23 | 5 | | 24 | 37 | | 25 | 32 | | 26 | 15 | | 27 | 7 | | 28 | 16 | | 29 | 2 | | 30 | 50 | | 31 | 9 | | 32 | 34 | | 33 | 32 | | 34 | 4 | | 35 | 43 | | 36 | 7 | | 37 | 68 | | 38 | 61 | | 39 | 10 | | 40 | 37 | | 41 | 8 | | 42 | 23 | | 43 | 24 | | 44 | 7 | | 45 | 33 | | 46 | 49 | | 47 | 22 | | 48 | 1 | | 49 | 8 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 161 | | matches | | 0 | "being dragged" | | 1 | "was caught" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 248 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 164 | | ratio | 0 | | matches | (empty) | |
| 97.77% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 188 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.0425531914893617 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.010638297872340425 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 164 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 164 | | mean | 9.26 | | std | 5.48 | | cv | 0.592 | | sampleLengths | | 0 | 7 | | 1 | 16 | | 2 | 15 | | 3 | 4 | | 4 | 9 | | 5 | 4 | | 6 | 8 | | 7 | 18 | | 8 | 6 | | 9 | 9 | | 10 | 26 | | 11 | 3 | | 12 | 13 | | 13 | 23 | | 14 | 10 | | 15 | 7 | | 16 | 10 | | 17 | 4 | | 18 | 23 | | 19 | 25 | | 20 | 19 | | 21 | 8 | | 22 | 4 | | 23 | 16 | | 24 | 14 | | 25 | 11 | | 26 | 3 | | 27 | 7 | | 28 | 6 | | 29 | 2 | | 30 | 7 | | 31 | 13 | | 32 | 4 | | 33 | 7 | | 34 | 17 | | 35 | 13 | | 36 | 7 | | 37 | 23 | | 38 | 12 | | 39 | 9 | | 40 | 7 | | 41 | 2 | | 42 | 8 | | 43 | 3 | | 44 | 10 | | 45 | 5 | | 46 | 5 | | 47 | 10 | | 48 | 10 | | 49 | 2 |
| |
| 45.73% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.2926829268292683 | | totalSentences | 164 | | uniqueOpeners | 48 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 156 | | matches | | 0 | "Even the traffic beyond Richmond" | | 1 | "Exactly three notes, the same" | | 2 | "Somewhere behind her, a branch" | | 3 | "Once, a pale shape slipped" | | 4 | "Then the light steadied, and" | | 5 | "Then she heard herself breathe" |
| | ratio | 0.038 | |
| 68.72% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 59 | | totalSentences | 156 | | matches | | 0 | "It came from the trees" | | 1 | "It was nearly midnight." | | 2 | "She had spent the afternoon" | | 3 | "She went back in and" | | 4 | "It grew stronger whenever she" | | 5 | "She could have stayed in" | | 6 | "She had wanted to." | | 7 | "She knew of one place" | | 8 | "she said, and stepped between" | | 9 | "Their pale heads shone among" | | 10 | "She waited, expecting it to" | | 11 | "Her phone read 11:42." | | 12 | "She took a photograph of" | | 13 | "She put the phone away" | | 14 | "She kept her pace slow," | | 15 | "She swung the torch on" | | 16 | "She pointed the torch between" | | 17 | "She crossed toward it, keeping" | | 18 | "Its bare twigs cast long" | | 19 | "She reached beneath her shirt" |
| | ratio | 0.378 | |
| 78.59% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 119 | | totalSentences | 156 | | matches | | 0 | "The first wrong thing was" | | 1 | "It came from the trees" | | 2 | "Aurora stopped with one hand" | | 3 | "It was nearly midnight." | | 4 | "The bird sang again." | | 5 | "A recording, she thought, though" | | 6 | "The pendant warmed against her" | | 7 | "She had spent the afternoon" | | 8 | "She went back in and" | | 9 | "Yu-Fei had frowned at her" | | 10 | "It grew stronger whenever she" | | 11 | "She could have stayed in" | | 12 | "She had wanted to." | | 13 | "She knew of one place" | | 14 | "she said, and stepped between" | | 15 | "Wildflowers brushed her boots." | | 16 | "Their pale heads shone among" | | 17 | "Moonlight lay across the clearing," | | 18 | "The air was warmer than" | | 19 | "The birdsong stopped." |
| | ratio | 0.763 | |
| 96.15% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 156 | | matches | | 0 | "Now she stood at the" | | 1 | "If she ran blind, she" | | 2 | "If something had come around" |
| | ratio | 0.019 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 59 | | technicalSentenceCount | 2 | | matches | | 0 | "But a stone from Dymas that warmed near a Hel portal was a poor thing to leave unexplained in the middle of London." | | 1 | "For a few seconds she stood there looking at his name, wanting the ordinary sound of his voice badly enough to try again." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 5 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.5 | | effectiveRatio | 0.4 | |