| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 84 | | tagDensity | 0.048 | | leniency | 0.095 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.50% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2224 | | totalAiIsmAdverbs | 2 | | 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) | |
| 79.77% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2224 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "silence" | | 1 | "stomach" | | 2 | "flicked" | | 3 | "weight" | | 4 | "restrained" | | 5 | "eyebrow" | | 6 | "unreadable" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | 0 | "eyes widened" | | 1 | "stomach dropped" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 144 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 144 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 224 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2224 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 104 | | wordCount | 1694 | | uniqueNames | 8 | | maxNameDensity | 3.01 | | worstName | "Rory" | | maxWindowNameDensity | 5 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Europe | 1 | | Rory | 51 | | Cardiff | 2 | | Eva | 38 | | Penarth | 1 | | Silas | 9 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Eva" | | 4 | "Silas" |
| | places | | 0 | "Europe" | | 1 | "Cardiff" | | 2 | "Penarth" |
| | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 109 | | glossingSentenceCount | 2 | | matches | | 0 | "not quite land" | | 1 | "looked like she belonged in a glass offic" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.45 | | wordCount | 2224 | | matches | | 0 | "not surprise exactly, but interest sharpened to a blade’s edge" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 224 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 168 | | mean | 13.24 | | std | 15.47 | | cv | 1.168 | | sampleLengths | | 0 | 65 | | 1 | 24 | | 2 | 3 | | 3 | 5 | | 4 | 12 | | 5 | 9 | | 6 | 21 | | 7 | 29 | | 8 | 5 | | 9 | 75 | | 10 | 28 | | 11 | 20 | | 12 | 57 | | 13 | 6 | | 14 | 7 | | 15 | 1 | | 16 | 35 | | 17 | 1 | | 18 | 29 | | 19 | 25 | | 20 | 8 | | 21 | 10 | | 22 | 5 | | 23 | 93 | | 24 | 9 | | 25 | 9 | | 26 | 3 | | 27 | 11 | | 28 | 1 | | 29 | 49 | | 30 | 6 | | 31 | 5 | | 32 | 3 | | 33 | 17 | | 34 | 5 | | 35 | 38 | | 36 | 8 | | 37 | 2 | | 38 | 17 | | 39 | 3 | | 40 | 9 | | 41 | 6 | | 42 | 9 | | 43 | 5 | | 44 | 36 | | 45 | 10 | | 46 | 3 | | 47 | 2 | | 48 | 7 | | 49 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 144 | | matches | | 0 | "being watched" | | 1 | "been said" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 279 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 224 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1700 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 67 | | adverbRatio | 0.039411764705882354 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.005294117647058823 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 224 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 224 | | mean | 9.93 | | std | 8.03 | | cv | 0.809 | | sampleLengths | | 0 | 27 | | 1 | 38 | | 2 | 24 | | 3 | 3 | | 4 | 5 | | 5 | 12 | | 6 | 9 | | 7 | 21 | | 8 | 6 | | 9 | 23 | | 10 | 5 | | 11 | 14 | | 12 | 40 | | 13 | 21 | | 14 | 28 | | 15 | 20 | | 16 | 19 | | 17 | 27 | | 18 | 11 | | 19 | 6 | | 20 | 7 | | 21 | 1 | | 22 | 15 | | 23 | 20 | | 24 | 1 | | 25 | 29 | | 26 | 10 | | 27 | 8 | | 28 | 7 | | 29 | 8 | | 30 | 10 | | 31 | 5 | | 32 | 6 | | 33 | 12 | | 34 | 3 | | 35 | 4 | | 36 | 3 | | 37 | 8 | | 38 | 35 | | 39 | 22 | | 40 | 9 | | 41 | 9 | | 42 | 3 | | 43 | 11 | | 44 | 1 | | 45 | 7 | | 46 | 27 | | 47 | 15 | | 48 | 6 | | 49 | 5 |
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| 47.32% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.20982142857142858 | | totalSentences | 224 | | uniqueOpeners | 47 | |
| 48.66% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 137 | | matches | | 0 | "Even her hair looked deliberate," | | 1 | "Somewhere near the door, someone" |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 137 | | matches | | 0 | "He nodded at the bag." | | 1 | "He took the bag with" | | 2 | "She rubbed at the inside" | | 3 | "She sat with her back" | | 4 | "Her voice came out with" | | 5 | "She stopped three feet away" | | 6 | "He set a tumbler down" | | 7 | "He moved off without another" | | 8 | "She folded her arms tight" | | 9 | "She hated that too, the" | | 10 | "She looked at Eva’s hands" | | 11 | "It landed on the crescent" | | 12 | "She set the glass down" | | 13 | "He set the bottle down" | | 14 | "he muttered, and the words" | | 15 | "She gripped the glass harder" | | 16 | "It carried years in it." |
| | ratio | 0.124 | |
| 14.74% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 122 | | totalSentences | 137 | | matches | | 0 | "The green neon above The" | | 1 | "Rory pushed through the door" | | 2 | "Silas looked up from behind" | | 3 | "He nodded at the bag." | | 4 | "Rory huffed a breath and" | | 5 | "Silas’s mouth twitched at one" | | 6 | "He took the bag with" | | 7 | "Rory slipped onto the nearest" | | 8 | "The usual clutter sat in" | | 9 | "The room stayed half-full, a" | | 10 | "She rubbed at the inside" | | 11 | "Silas was halfway to the" | | 12 | "She sat with her back" | | 13 | "Rory caught the shape of" | | 14 | "The woman turned her head" | | 15 | "Rory’s stomach dropped clean through" | | 16 | "The face had changed, but" | | 17 | "The woman’s eyes widened first," | | 18 | "Her voice came out with" | | 19 | "Rory slid off the stool" |
| | ratio | 0.891 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 137 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 67 | | technicalSentenceCount | 3 | | matches | | 0 | "Rory caught the shape of a tailored coat, dark and expensive-looking, the sharp line of a jaw, hair cut into a blunt swing that skimmed her collar." | | 1 | "The woman turned her head as if she’d felt the stare." | | 2 | "The polished surface cracked a little, and underneath there was still the girl who had once slept on Rory’s floor after a row with her mother, who had drawn sta…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 1 | | matches | | 0 | "he muttered, and the words came with the dry patience of a man speaking to weather" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 3 | | fancyTags | | 0 | "Eva murmured (murmur)" | | 1 | "he muttered (mutter)" | | 2 | "she repeated (repeat)" |
| | dialogueSentences | 84 | | tagDensity | 0.048 | | leniency | 0.095 | | rawRatio | 0.75 | | effectiveRatio | 0.071 | |