| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.11% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1284 | | 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) | |
| 57.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1284 | | totalAiIsms | 11 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | word | "down her spine" | | count | 1 |
| | 8 | | | 9 | |
| | highlights | | 0 | "weight" | | 1 | "flicked" | | 2 | "echoed" | | 3 | "whisper" | | 4 | "silence" | | 5 | "tension" | | 6 | "charged" | | 7 | "down her spine" | | 8 | "traced" | | 9 | "pulse" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "let out a breath" | | count | 1 |
| | 1 | | label | "knuckles turned white" | | count | 1 |
|
| | highlights | | 0 | "let out a breath" | | 1 | "knuckles turned white" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 152 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 152 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 152 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1284 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 1284 | | uniqueNames | 18 | | maxNameDensity | 1.25 | | worstName | "You" | | maxWindowNameDensity | 3.5 | | worstWindowName | "You" | | discoveredNames | | Eva | 4 | | Moreau | 1 | | Aurora | 1 | | Rory | 11 | | Sumerian | 1 | | Lucien | 11 | | Golden | 1 | | Empress | 1 | | Yu-Fei | 1 | | Cardiff | 1 | | Evan | 6 | | London | 2 | | Wales | 1 | | Formica | 1 | | East | 1 | | End | 1 | | Frenchman | 1 | | You | 16 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Rory" | | 3 | "Sumerian" | | 4 | "Lucien" | | 5 | "Yu-Fei" | | 6 | "Evan" | | 7 | "You" |
| | places | | 0 | "Golden" | | 1 | "Cardiff" | | 2 | "London" | | 3 | "Wales" | | 4 | "East" | | 5 | "End" |
| | globalScore | 0.877 | | windowScore | 0.5 | |
| 96.24% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 93 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like a curse" | | 1 | "the black eye seemingly absorbing the dim l" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1284 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 152 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 49 | | mean | 26.2 | | std | 15.35 | | cv | 0.586 | | sampleLengths | | 0 | 32 | | 1 | 6 | | 2 | 49 | | 3 | 11 | | 4 | 24 | | 5 | 13 | | 6 | 22 | | 7 | 12 | | 8 | 17 | | 9 | 33 | | 10 | 41 | | 11 | 15 | | 12 | 35 | | 13 | 20 | | 14 | 32 | | 15 | 8 | | 16 | 41 | | 17 | 33 | | 18 | 9 | | 19 | 40 | | 20 | 56 | | 21 | 23 | | 22 | 8 | | 23 | 19 | | 24 | 48 | | 25 | 4 | | 26 | 23 | | 27 | 42 | | 28 | 4 | | 29 | 48 | | 30 | 35 | | 31 | 28 | | 32 | 4 | | 33 | 46 | | 34 | 20 | | 35 | 8 | | 36 | 39 | | 37 | 41 | | 38 | 34 | | 39 | 35 | | 40 | 29 | | 41 | 59 | | 42 | 6 | | 43 | 28 | | 44 | 28 | | 45 | 4 | | 46 | 47 | | 47 | 20 | | 48 | 5 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 152 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 230 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 152 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1287 | | adjectiveStacks | 1 | | stackExamples | | 0 | "No more cryptic warnings." |
| | adverbCount | 26 | | adverbRatio | 0.020202020202020204 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.003108003108003108 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 152 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 152 | | mean | 8.45 | | std | 5.45 | | cv | 0.646 | | sampleLengths | | 0 | 4 | | 1 | 11 | | 2 | 17 | | 3 | 6 | | 4 | 6 | | 5 | 9 | | 6 | 16 | | 7 | 18 | | 8 | 4 | | 9 | 7 | | 10 | 2 | | 11 | 8 | | 12 | 10 | | 13 | 4 | | 14 | 13 | | 15 | 3 | | 16 | 13 | | 17 | 6 | | 18 | 8 | | 19 | 3 | | 20 | 1 | | 21 | 8 | | 22 | 3 | | 23 | 2 | | 24 | 2 | | 25 | 2 | | 26 | 10 | | 27 | 15 | | 28 | 8 | | 29 | 15 | | 30 | 26 | | 31 | 6 | | 32 | 9 | | 33 | 5 | | 34 | 4 | | 35 | 11 | | 36 | 8 | | 37 | 5 | | 38 | 2 | | 39 | 9 | | 40 | 9 | | 41 | 2 | | 42 | 10 | | 43 | 14 | | 44 | 8 | | 45 | 4 | | 46 | 4 | | 47 | 4 | | 48 | 3 | | 49 | 10 |
| |
| 38.16% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.21052631578947367 | | totalSentences | 152 | | uniqueOpeners | 32 | |
| 22.99% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 145 | | matches | | 0 | "Then lead the way, Frenchman." |
| | ratio | 0.007 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 84 | | totalSentences | 145 | | matches | | 0 | "She hauled the heavy wooden" | | 1 | "He leaned his weight onto" | | 2 | "His platinum blond hair was" | | 3 | "You changed the locks." | | 4 | "His gaze flicked to the" | | 5 | "She values her privacy." | | 6 | "It is Rory." | | 7 | "She moved to slam the" | | 8 | "His gloved hand shot out," | | 9 | "She stepped back and pulled" | | 10 | "He crossed the threshold, bringing" | | 11 | "He paused in the entryway," | | 12 | "Your friend has a hoarding" | | 13 | "He stepped over a pile" | | 14 | "She has a research obsession." | | 15 | "We agreed to stay out" | | 16 | "He turned, his coat brushing" | | 17 | "Your beast dislikes me." | | 18 | "He is a rescue." | | 19 | "He dislikes everyone." |
| | ratio | 0.579 | |
| 22.07% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 127 | | totalSentences | 145 | | matches | | 0 | "The top deadbolt clicked." | | 1 | "Rory twisted the middle lock," | | 2 | "She hauled the heavy wooden" | | 3 | "The words died in her" | | 4 | "Lucien Moreau filled the cramped" | | 5 | "Rain darkened the shoulders of" | | 6 | "He leaned his weight onto" | | 7 | "His platinum blond hair was" | | 8 | "You changed the locks." | | 9 | "His gaze flicked to the" | | 10 | "Rory tightened her grip on" | | 11 | "The small crescent scar on" | | 12 | "She values her privacy." | | 13 | "It is Rory." | | 14 | "She moved to slam the" | | 15 | "His gloved hand shot out," | | 16 | "The leather creaked." | | 17 | "The single word hung in" | | 18 | "Lucien never begged." | | 19 | "Rory stared at his hand," |
| | ratio | 0.876 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 145 | | matches | | 0 | "If I stay, I need" | | 1 | "If we are doing this," | | 2 | "Now, are you going to" |
| | ratio | 0.021 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | |