| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 79.17% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 720 | | totalAiIsmAdverbs | 3 | | 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) | |
| 72.22% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 720 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "perfect" | | 1 | "echo" | | 2 | "footsteps" | | 3 | "weight" |
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| 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 | 73 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 73 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 75 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 21 | | totalWords | 720 | | ratio | 0.029 | | matches | | 0 | "Don't eat anything, don't make promises, and for God's sake don't answer if someone calls you by your middle name." | | 1 | "Right." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 14 | | wordCount | 715 | | uniqueNames | 12 | | maxNameDensity | 0.28 | | worstName | "Heartstone" | | maxWindowNameDensity | 0.5 | | worstWindowName | "Heartstone" | | discoveredNames | | Heartstone | 2 | | Park | 1 | | October | 1 | | Sheen | 1 | | Gate | 1 | | God | 1 | | Mum | 1 | | Cardiff | 2 | | London | 1 | | Rory | 1 | | Laila | 1 | | Evan | 1 |
| | persons | | 0 | "Heartstone" | | 1 | "God" | | 2 | "Rory" | | 3 | "Laila" | | 4 | "Evan" |
| | places | | 0 | "Park" | | 1 | "Sheen" | | 2 | "Cardiff" | | 3 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 45 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 2.778 | | wordCount | 720 | | matches | | 0 | "Not hot, not yet, but warm the way a radiator feels" | | 1 | "not yet, but warm the way a radiator feels" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 75 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 24 | | mean | 30 | | std | 24.49 | | cv | 0.816 | | sampleLengths | | 0 | 13 | | 1 | 62 | | 2 | 15 | | 3 | 74 | | 4 | 10 | | 5 | 49 | | 6 | 56 | | 7 | 7 | | 8 | 54 | | 9 | 9 | | 10 | 53 | | 11 | 1 | | 12 | 42 | | 13 | 7 | | 14 | 8 | | 15 | 62 | | 16 | 31 | | 17 | 5 | | 18 | 4 | | 19 | 71 | | 20 | 44 | | 21 | 6 | | 22 | 32 | | 23 | 5 |
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| 90.84% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 73 | | matches | | 0 | "been carved" | | 1 | "been painted" | | 2 | "been trampled" |
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| 27.59% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 116 | | matches | | 0 | "were already rotting" | | 1 | "was coming" | | 2 | "were learning" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 75 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 717 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.029288702928870293 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0041841004184100415 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 75 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 75 | | mean | 9.6 | | std | 7.27 | | cv | 0.757 | | sampleLengths | | 0 | 13 | | 1 | 27 | | 2 | 12 | | 3 | 1 | | 4 | 22 | | 5 | 3 | | 6 | 12 | | 7 | 5 | | 8 | 2 | | 9 | 16 | | 10 | 27 | | 11 | 15 | | 12 | 5 | | 13 | 4 | | 14 | 10 | | 15 | 4 | | 16 | 13 | | 17 | 3 | | 18 | 7 | | 19 | 22 | | 20 | 2 | | 21 | 22 | | 22 | 12 | | 23 | 20 | | 24 | 7 | | 25 | 7 | | 26 | 12 | | 27 | 21 | | 28 | 8 | | 29 | 6 | | 30 | 9 | | 31 | 3 | | 32 | 14 | | 33 | 5 | | 34 | 14 | | 35 | 5 | | 36 | 1 | | 37 | 1 | | 38 | 10 | | 39 | 1 | | 40 | 9 | | 41 | 13 | | 42 | 2 | | 43 | 18 | | 44 | 7 | | 45 | 3 | | 46 | 5 | | 47 | 11 | | 48 | 5 | | 49 | 17 |
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| 85.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.56 | | totalSentences | 75 | | uniqueOpeners | 42 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 60 | | matches | | 0 | "Then, from somewhere past the" | | 1 | "Soft, deliberate, circling." | | 2 | "All converging on the split" | | 3 | "Then the shadow tilted its" |
| | ratio | 0.067 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 60 | | matches | | 0 | "I stopped, one palm flat" | | 1 | "I pulled my phone out." | | 2 | "I shoved it back into" | | 3 | "It was October." | | 4 | "I counted the stones as" | | 5 | "I reached seven and kept" | | 6 | "I hadn't seen it on" | | 7 | "I was almost certain I" | | 8 | "It was a pale shape" | | 9 | "I swung the light round." | | 10 | "My voice came back to" | | 11 | "it said, and it sounded" | | 12 | "I didn't answer." | | 13 | "I switched off the torch." | | 14 | "My eyes adjusted slowly, and" | | 15 | "It flared hot enough to" | | 16 | "It was tall and thin" | | 17 | "It bent forward, slowly, the" |
| | ratio | 0.3 | |
| 85.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 60 | | matches | | 0 | "The pendant burned against my" | | 1 | "I stopped, one palm flat" | | 2 | "The Heartstone glowed through the" | | 3 | "Hel was close." | | 4 | "Someone had opened a door" | | 5 | "I pulled my phone out." | | 6 | "The clock read 00:00, then" | | 7 | "I shoved it back into" | | 8 | "Richmond Park at night was" | | 9 | "Here, the traffic had stopped." | | 10 | "Nothing hummed at all." | | 11 | "The grove opened ahead of" | | 12 | "Wildflowers covered the clearing." | | 13 | "Bluebells, foxgloves, a carpet of" | | 14 | "It was October." | | 15 | "The name had been carved" | | 16 | "Eva had laughed when I" | | 17 | "Nobody knew my middle name" | | 18 | "I counted the stones as" | | 19 | "The circle had seven, according" |
| | ratio | 0.75 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 1 | | matches | | 0 | "I stopped, one palm flat against the bark of an oak that had no business being that old, and let the silver chain slide through my fingers." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |