| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 54 | | tagDensity | 0.296 | | leniency | 0.593 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.58% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1132 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 95.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1132 | | totalAiIsms | 1 | | found | | | highlights | | |
| 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 | 46 | | matches | (empty) | |
| 80.75% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 46 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 84 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 64 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1141 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 604 | | uniqueNames | 5 | | maxNameDensity | 2.15 | | worstName | "Niamh" | | maxWindowNameDensity | 4 | | worstWindowName | "Niamh" | | discoveredNames | | Silas | 4 | | Thursday | 1 | | Rory | 12 | | Niamh | 13 | | American | 1 |
| | persons | | | places | (empty) | | globalScore | 0.424 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 32 | | 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 | 1141 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 84 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 20.38 | | std | 24.04 | | cv | 1.18 | | sampleLengths | | 0 | 79 | | 1 | 25 | | 2 | 34 | | 3 | 1 | | 4 | 3 | | 5 | 76 | | 6 | 10 | | 7 | 57 | | 8 | 4 | | 9 | 2 | | 10 | 10 | | 11 | 49 | | 12 | 11 | | 13 | 15 | | 14 | 2 | | 15 | 2 | | 16 | 5 | | 17 | 4 | | 18 | 20 | | 19 | 36 | | 20 | 45 | | 21 | 2 | | 22 | 3 | | 23 | 2 | | 24 | 59 | | 25 | 13 | | 26 | 3 | | 27 | 5 | | 28 | 4 | | 29 | 89 | | 30 | 2 | | 31 | 65 | | 32 | 10 | | 33 | 5 | | 34 | 4 | | 35 | 1 | | 36 | 4 | | 37 | 63 | | 38 | 1 | | 39 | 8 | | 40 | 72 | | 41 | 7 | | 42 | 2 | | 43 | 10 | | 44 | 1 | | 45 | 33 | | 46 | 11 | | 47 | 43 | | 48 | 5 | | 49 | 3 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 46 | | matches | (empty) | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 108 | | matches | | 0 | "was nursing" | | 1 | "was turning" | | 2 | "was holding" | | 3 | "was carrying" | | 4 | "was looking" | | 5 | "was thinking" | | 6 | "was playing" | | 7 | "was listening" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 84 | | ratio | 0.012 | | matches | | 0 | "\"I know it wasn't about me.\" Niamh's voice wasn't raised; it had gone small instead, which was how she'd always argued, even at twenty." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 605 | | adjectiveStacks | 1 | | stackExamples | | 0 | "Same rust-coloured hair" |
| | adverbCount | 22 | | adverbRatio | 0.03636363636363636 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.006611570247933884 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 84 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 84 | | mean | 13.58 | | std | 14.2 | | cv | 1.046 | | sampleLengths | | 0 | 17 | | 1 | 50 | | 2 | 4 | | 3 | 8 | | 4 | 25 | | 5 | 5 | | 6 | 29 | | 7 | 1 | | 8 | 3 | | 9 | 11 | | 10 | 25 | | 11 | 23 | | 12 | 17 | | 13 | 10 | | 14 | 5 | | 15 | 20 | | 16 | 32 | | 17 | 4 | | 18 | 2 | | 19 | 10 | | 20 | 10 | | 21 | 38 | | 22 | 1 | | 23 | 11 | | 24 | 11 | | 25 | 4 | | 26 | 2 | | 27 | 2 | | 28 | 5 | | 29 | 4 | | 30 | 20 | | 31 | 25 | | 32 | 3 | | 33 | 8 | | 34 | 8 | | 35 | 30 | | 36 | 7 | | 37 | 2 | | 38 | 3 | | 39 | 2 | | 40 | 59 | | 41 | 6 | | 42 | 7 | | 43 | 3 | | 44 | 5 | | 45 | 4 | | 46 | 24 | | 47 | 65 | | 48 | 2 | | 49 | 38 |
| |
| 46.83% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.34523809523809523 | | totalSentences | 84 | | uniqueOpeners | 29 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 41 | | matches | (empty) | | ratio | 0 | |
| 83.41% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 41 | | matches | | 0 | "He knew the look." | | 1 | "She had been carrying it" | | 2 | "She was turning the glass" | | 3 | "She watched her own face" | | 4 | "She was holding a laptop" | | 5 | "She set the bag on" | | 6 | "Her hand flicked at the" | | 7 | "She looked at Rory properly" | | 8 | "She drank the rest of" | | 9 | "She had always touched it" | | 10 | "They sat with that." | | 11 | "She turned her glass" | | 12 | "She waved her hand again" | | 13 | "She didn't know if it" |
| | ratio | 0.341 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 39 | | totalSentences | 41 | | matches | | 0 | "The green neon bled through" | | 1 | "Rory had claimed the stool" | | 2 | "He knew the look." | | 3 | "She had been carrying it" | | 4 | "She was turning the glass" | | 5 | "Rory didn't turn at first." | | 6 | "She watched her own face" | | 7 | "Niamh hadn't changed, which was" | | 8 | "She was holding a laptop" | | 9 | "Niamh slid onto the stool." | | 10 | "She set the bag on" | | 11 | "Silas, at the other end" | | 12 | "Rory called, and Silas moved" | | 13 | "Niamh said it like a" | | 14 | "Her hand flicked at the" | | 15 | "Niamh laughed, a short sound," | | 16 | "Niamh put her forehead against" | | 17 | "The wine arrived." | | 18 | "Niamh drank half of it" | | 19 | "She looked at Rory properly" |
| | ratio | 0.951 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 41 | | matches | (empty) | | ratio | 0 | |
| 30.08% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 19 | | technicalSentenceCount | 3 | | matches | | 0 | "But there was a softness at the jaw now, a tiredness that sat under the skin the way damp sits in old walls." | | 1 | "Silas, at the other end of the bar, pretended to polish a glass and watched from the corner of his eye, which was the closest thing he ever offered to a blessin…" | | 2 | "Niamh was looking at the small scar on Rory's wrist, the crescent that had been there since they were nine years old and Rory had put her hand through a greenho…" |
| |
| 93.75% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 1 | | matches | | 0 | "Niamh laughed, a short sound, more air than voice" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 2 | | fancyTags | | 0 | "the door chimed (chime)" | | 1 | "Niamh laughed (laugh)" |
| | dialogueSentences | 54 | | tagDensity | 0.185 | | leniency | 0.37 | | rawRatio | 0.2 | | effectiveRatio | 0.074 | |