| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1221 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "very" | | 2 | "perfectly" |
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| 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) | |
| 34.48% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1221 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "vibrated" | | 1 | "rhythmic" | | 2 | "weight" | | 3 | "lurch" | | 4 | "chaotic" | | 5 | "sanctuary" | | 6 | "stark" | | 7 | "comfortable" | | 8 | "flicker" | | 9 | "calculated" | | 10 | "charged" | | 11 | "silence" | | 12 | "perfect" | | 13 | "tracing" | | 14 | "electric" | | 15 | "pulse" |
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| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
| | 2 | | label | "flicker of emotion" | | count | 1 |
|
| | highlights | | 0 | "blood ran cold" | | 1 | "hung in the air" | | 2 | "a flicker of amusement" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 98 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 98 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 134 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1212 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 14 | | wordCount | 912 | | uniqueNames | 9 | | maxNameDensity | 0.33 | | worstName | "Eva" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Eva" | | discoveredNames | | Eva | 3 | | Silas | 1 | | Welsh | 1 | | Rory | 3 | | Indian | 1 | | Tube | 1 | | Camden | 1 | | Cardiff | 2 | | Deptford | 1 |
| | persons | | | places | | 0 | "Tube" | | 1 | "Camden" | | 2 | "Cardiff" | | 3 | "Deptford" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | 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 | 1212 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 134 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 31.08 | | std | 20.1 | | cv | 0.647 | | sampleLengths | | 0 | 66 | | 1 | 67 | | 2 | 56 | | 3 | 50 | | 4 | 41 | | 5 | 1 | | 6 | 28 | | 7 | 19 | | 8 | 10 | | 9 | 26 | | 10 | 49 | | 11 | 60 | | 12 | 15 | | 13 | 17 | | 14 | 24 | | 15 | 39 | | 16 | 18 | | 17 | 56 | | 18 | 1 | | 19 | 18 | | 20 | 27 | | 21 | 9 | | 22 | 35 | | 23 | 48 | | 24 | 11 | | 25 | 4 | | 26 | 2 | | 27 | 19 | | 28 | 50 | | 29 | 22 | | 30 | 35 | | 31 | 30 | | 32 | 15 | | 33 | 18 | | 34 | 9 | | 35 | 74 | | 36 | 54 | | 37 | 43 | | 38 | 46 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 98 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 140 | | matches | | 0 | "wasn't looking" | | 1 | "was expecting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 134 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 286 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 5 | | adverbRatio | 0.017482517482517484 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0034965034965034965 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 134 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 134 | | mean | 9.04 | | std | 6.47 | | cv | 0.716 | | sampleLengths | | 0 | 9 | | 1 | 21 | | 2 | 11 | | 3 | 5 | | 4 | 14 | | 5 | 4 | | 6 | 2 | | 7 | 16 | | 8 | 24 | | 9 | 27 | | 10 | 2 | | 11 | 15 | | 12 | 17 | | 13 | 4 | | 14 | 6 | | 15 | 12 | | 16 | 5 | | 17 | 10 | | 18 | 4 | | 19 | 1 | | 20 | 14 | | 21 | 16 | | 22 | 13 | | 23 | 8 | | 24 | 20 | | 25 | 1 | | 26 | 4 | | 27 | 16 | | 28 | 8 | | 29 | 1 | | 30 | 12 | | 31 | 6 | | 32 | 5 | | 33 | 5 | | 34 | 4 | | 35 | 13 | | 36 | 9 | | 37 | 8 | | 38 | 1 | | 39 | 18 | | 40 | 22 | | 41 | 33 | | 42 | 14 | | 43 | 13 | | 44 | 15 | | 45 | 13 | | 46 | 1 | | 47 | 3 | | 48 | 16 | | 49 | 6 |
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| 48.51% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.3582089552238806 | | totalSentences | 134 | | uniqueOpeners | 48 | |
| 38.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 86 | | matches | | 0 | "Still trying to solve the" |
| | ratio | 0.012 | |
| 33.95% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 86 | | matches | | 0 | "It was a series of" | | 1 | "It wasn't Eva's frantic, triple-rat-a-tat-tat." | | 2 | "It wasn't Silas from the" | | 3 | "She placed the samosa back" | | 4 | "She slid the first one" | | 5 | "She put her weight into" | | 6 | "She leaned forward, her eye" | | 7 | "He wasn't looking at the" | | 8 | "Her heart gave a single," | | 9 | "She straightened up, her face" | | 10 | "She pulled the chain free" | | 11 | "He turned his head." | | 12 | "His eyes, one the colour" | | 13 | "I was expecting tea, maybe" | | 14 | "She hated that he could" | | 15 | "He stepped inside, bringing with" | | 16 | "His presence was an intrusion," | | 17 | "He closed the door behind" | | 18 | "He ran a gloved finger" | | 19 | "He smiled, a genuine curve" |
| | ratio | 0.465 | |
| 23.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 86 | | matches | | 0 | "The knock on the door" | | 1 | "It was a series of" | | 2 | "Rory paused, a half-eaten samosa" | | 3 | "It wasn't Eva's frantic, triple-rat-a-tat-tat." | | 4 | "It wasn't Silas from the" | | 5 | "This was something else." | | 6 | "She placed the samosa back" | | 7 | "The flat was quiet, save" | | 8 | "Ptolemy, Eva's tabby cat, lifted" | | 9 | "Eva was paranoid, but Rory" | | 10 | "She slid the first one" | | 11 | "The third was stiff." | | 12 | "She put her weight into" | | 13 | "She leaned forward, her eye" | | 14 | "A slice of the hallway." | | 15 | "A scuffed floor, the opposite" | | 16 | "A slash of platinum blond" | | 17 | "He wasn't looking at the" | | 18 | "Her heart gave a single," | | 19 | "She straightened up, her face" |
| | ratio | 0.872 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 86.47% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 3 | | matches | | 0 | "It was a series of heavy, deliberate thuds that vibrated through the floorboards and up the legs of the rickety table." | | 1 | "The memory of his hand on her arm, holding her back, holding her safe." | | 2 | "She stared at him, at the man who was a perfect, polished shell holding something monstrous and broken inside." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |