| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 186 | | tagDensity | 0.108 | | leniency | 0.215 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2154 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2154 | | totalAiIsms | 0 | | found | (empty) | | highlights | (empty) | |
| 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 | 116 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 116 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 282 | | 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 | 2154 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 55 | | unquotedAttributions | 1 | | matches | | 0 | "She remembered a long table, her father carving beef, Eva refusing a second helping while his friend poured himself more…" |
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| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 98 | | wordCount | 1008 | | uniqueNames | 6 | | maxNameDensity | 4.27 | | worstName | "Eva" | | maxWindowNameDensity | 7 | | worstWindowName | "Eva" | | discoveredNames | | Soho | 1 | | Rory | 41 | | Eva | 43 | | Silas | 10 | | Cardiff | 1 | | Evan | 2 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Silas" | | 3 | "Evan" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 75 | | 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 | 2154 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 282 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 233 | | mean | 9.24 | | std | 8.92 | | cv | 0.965 | | sampleLengths | | 0 | 48 | | 1 | 6 | | 2 | 40 | | 3 | 1 | | 4 | 12 | | 5 | 1 | | 6 | 42 | | 7 | 7 | | 8 | 4 | | 9 | 6 | | 10 | 5 | | 11 | 39 | | 12 | 14 | | 13 | 3 | | 14 | 18 | | 15 | 20 | | 16 | 4 | | 17 | 6 | | 18 | 4 | | 19 | 3 | | 20 | 10 | | 21 | 32 | | 22 | 5 | | 23 | 5 | | 24 | 26 | | 25 | 4 | | 26 | 9 | | 27 | 6 | | 28 | 3 | | 29 | 5 | | 30 | 7 | | 31 | 15 | | 32 | 6 | | 33 | 5 | | 34 | 3 | | 35 | 1 | | 36 | 4 | | 37 | 2 | | 38 | 27 | | 39 | 3 | | 40 | 5 | | 41 | 3 | | 42 | 11 | | 43 | 32 | | 44 | 7 | | 45 | 11 | | 46 | 12 | | 47 | 7 | | 48 | 3 | | 49 | 10 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 116 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 187 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 2 | | totalSentences | 282 | | ratio | 0.007 | | matches | | 0 | "A thin line of foam stayed on her upper lip; she wiped it away with her thumb." | | 1 | "Silas had returned to the till; he lifted a bottle from a shelf and checked its label without looking at either of them." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1008 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 10 | | adverbRatio | 0.00992063492063492 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 282 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 282 | | mean | 7.64 | | std | 5.31 | | cv | 0.695 | | sampleLengths | | 0 | 22 | | 1 | 8 | | 2 | 18 | | 3 | 6 | | 4 | 3 | | 5 | 19 | | 6 | 18 | | 7 | 1 | | 8 | 6 | | 9 | 6 | | 10 | 1 | | 11 | 5 | | 12 | 10 | | 13 | 15 | | 14 | 12 | | 15 | 7 | | 16 | 4 | | 17 | 6 | | 18 | 5 | | 19 | 7 | | 20 | 32 | | 21 | 8 | | 22 | 6 | | 23 | 3 | | 24 | 12 | | 25 | 6 | | 26 | 12 | | 27 | 8 | | 28 | 4 | | 29 | 6 | | 30 | 4 | | 31 | 3 | | 32 | 10 | | 33 | 18 | | 34 | 14 | | 35 | 5 | | 36 | 5 | | 37 | 8 | | 38 | 18 | | 39 | 4 | | 40 | 9 | | 41 | 6 | | 42 | 3 | | 43 | 5 | | 44 | 7 | | 45 | 2 | | 46 | 13 | | 47 | 6 | | 48 | 5 | | 49 | 3 |
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| 41.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 24 | | diversityRatio | 0.1702127659574468 | | totalSentences | 282 | | uniqueOpeners | 48 | |
| 34.01% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 98 | | matches | | | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 98 | | matches | | 0 | "She held a folded umbrella" | | 1 | "Her hair had been cut" | | 2 | "She wore a charcoal suit" | | 3 | "She caught it before it" | | 4 | "His silver ring struck the" | | 5 | "She set her umbrella against" | | 6 | "His left leg lagged when" | | 7 | "She took two mugs down," | | 8 | "Her nails were short and" | | 9 | "She remembered standing guard at" | | 10 | "He gave her a look," | | 11 | "She remembered a long table," | | 12 | "She pulled it free and" | | 13 | "She had let it brew" | | 14 | "She turned it over, then" | | 15 | "She had a small burn" | | 16 | "She laid it on a" | | 17 | "She had asked why, and" |
| | ratio | 0.184 | |
| 5.92% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 89 | | totalSentences | 98 | | matches | | 0 | "Rory came down the stairs" | | 1 | "Rain darkened the shoulders of" | | 2 | "She held a folded umbrella" | | 3 | "Rory stopped on the last" | | 4 | "The woman turned." | | 5 | "Her hair had been cut" | | 6 | "She wore a charcoal suit" | | 7 | "The parcel slipped against Rory’s" | | 8 | "She caught it before it" | | 9 | "Rory shifted the parcel behind" | | 10 | "The hug pressed a wet" | | 11 | "Eva stepped back and looked" | | 12 | "Rory had expected the short" | | 13 | "Silas stood behind the bar," | | 14 | "His silver ring struck the" | | 15 | "Rory laid the parcel on" | | 16 | "Eva glanced at the parcel" | | 17 | "Eva smiled at him, then" | | 18 | "Rory wore her delivery jacket," | | 19 | "Eva took off her coat" |
| | ratio | 0.908 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 98 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 186 | | tagDensity | 0.086 | | leniency | 0.172 | | rawRatio | 0.063 | | effectiveRatio | 0.011 | |