| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 60.75% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1019 | | totalAiIsmAdverbs | 8 | | found | | | highlights | | 0 | "very" | | 1 | "slightly" | | 2 | "slowly" | | 3 | "softly" |
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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) | |
| 75.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1019 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "weight" | | 1 | "stomach" | | 2 | "footsteps" | | 3 | "measured" |
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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 | 78 | | matches | (empty) | |
| 87.91% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 78 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 78 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 94.01% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 7 | | markdownWords | 54 | | totalWords | 1019 | | ratio | 0.053 | | matches | | 0 | "you will need this" | | 1 | "Stay on the path," | | 2 | "Do not answer your name." | | 3 | "An hour inside can be minutes or days outside," | | 4 | "Which means I could be missing a week right now. Or I could be missing the last ten minutes. Or I could already have been missing for years." | | 5 | "Rory" | | 6 | "Do not answer." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 10 | | wordCount | 992 | | uniqueNames | 3 | | maxNameDensity | 0.71 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | | persons | | | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 1 | | matches | | 0 | "as though listening to the stone" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.981 | | wordCount | 1019 | | matches | | 0 | "Not sun-warm, which was impossible, but blood-warm, the way a sleeping animal is warm" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 78 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 36.39 | | std | 25.37 | | cv | 0.697 | | sampleLengths | | 0 | 66 | | 1 | 51 | | 2 | 47 | | 3 | 51 | | 4 | 4 | | 5 | 82 | | 6 | 16 | | 7 | 83 | | 8 | 36 | | 9 | 40 | | 10 | 5 | | 11 | 72 | | 12 | 8 | | 13 | 61 | | 14 | 29 | | 15 | 5 | | 16 | 42 | | 17 | 54 | | 18 | 51 | | 19 | 9 | | 20 | 9 | | 21 | 3 | | 22 | 63 | | 23 | 16 | | 24 | 24 | | 25 | 60 | | 26 | 3 | | 27 | 29 |
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| 78.27% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 78 | | matches | | 0 | "been locked" | | 1 | "were supposed" | | 2 | "been carved" | | 3 | "was turned" | | 4 | "being poured" | | 5 | "being allowed" | | 6 | "been destined" |
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| 35.39% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 162 | | matches | | 0 | "was not laughing" | | 1 | "was not warming" | | 2 | "was warming" | | 3 | "was waiting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 78 | | ratio | 0 | | matches | (empty) | |
| 70.71% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 245 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.07346938775510205 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.00816326530612245 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 78 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 78 | | mean | 13.06 | | std | 11.11 | | cv | 0.85 | | sampleLengths | | 0 | 24 | | 1 | 16 | | 2 | 10 | | 3 | 16 | | 4 | 7 | | 5 | 4 | | 6 | 1 | | 7 | 39 | | 8 | 14 | | 9 | 4 | | 10 | 15 | | 11 | 14 | | 12 | 1 | | 13 | 2 | | 14 | 11 | | 15 | 7 | | 16 | 30 | | 17 | 4 | | 18 | 6 | | 19 | 47 | | 20 | 10 | | 21 | 19 | | 22 | 8 | | 23 | 8 | | 24 | 12 | | 25 | 33 | | 26 | 38 | | 27 | 19 | | 28 | 3 | | 29 | 14 | | 30 | 8 | | 31 | 32 | | 32 | 5 | | 33 | 17 | | 34 | 24 | | 35 | 11 | | 36 | 20 | | 37 | 8 | | 38 | 5 | | 39 | 1 | | 40 | 8 | | 41 | 26 | | 42 | 7 | | 43 | 14 | | 44 | 4 | | 45 | 22 | | 46 | 1 | | 47 | 1 | | 48 | 1 | | 49 | 5 |
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| 74.79% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.48717948717948717 | | totalSentences | 78 | | uniqueOpeners | 38 | |
| 95.24% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 70 | | matches | | 0 | "Then even that thinned out," | | 1 | "Then, when she glanced at" |
| | ratio | 0.029 | |
| 94.29% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 70 | | matches | | 0 | "She landed badly on the" | | 1 | "She stood and brushed off" | | 2 | "Her phone showed 11:52." | | 3 | "It was the second week" | | 4 | "She didn't touch them." | | 5 | "She had worn it for" | | 6 | "She was not sure she" | | 7 | "She reached the first standing" | | 8 | "It was taller than she" | | 9 | "She put her palm flat" | | 10 | "It was warm." | | 11 | "She was not laughing now." | | 12 | "She turned her head slowly." | | 13 | "It was turned away from" | | 14 | "She counted her breaths, the" | | 15 | "Her watch said 12:07." | | 16 | "Her phone buzzed in her" | | 17 | "She did not take it" | | 18 | "She knew who it would" | | 19 | "It was warming because something" |
| | ratio | 0.314 | |
| 88.57% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 70 | | matches | | 0 | "The park gate had been" | | 1 | "She landed badly on the" | | 2 | "Traffic hummed somewhere beyond the" | | 3 | "She stood and brushed off" | | 4 | "Her phone showed 11:52." | | 5 | "Midnight was when the old" | | 6 | "The path bent left, then" | | 7 | "The air smelled wrong, too" | | 8 | "Halfway along, she stopped at" | | 9 | "A cluster of white campion," | | 10 | "It was the second week" | | 11 | "Frost should have been silvering" | | 12 | "She didn't touch them." | | 13 | "The pendant shifted against her" | | 14 | "She had worn it for" | | 15 | "Tonight it had been warm" | | 16 | "Rory had told herself that" | | 17 | "She was not sure she" | | 18 | "She reached the first standing" | | 19 | "It was taller than she" |
| | ratio | 0.743 | |
| 71.43% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 70 | | matches | | 0 | "to check the messages, the" |
| | ratio | 0.014 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 5 | | matches | | 0 | "Midnight was when the old oaks were supposed to be most open, according to the one page on the internet that had got the directions right, written by someone wh…" | | 1 | "It was taller than she had expected, grey-green with lichen, and it leaned slightly, as if it had been listening to something for a very long time and had grown…" | | 2 | "Oak had been carved into its surface in a pattern of knots that might have been accidental, except that when she looked at them directly they seemed to rearrang…" | | 3 | "*An hour inside can be minutes or days outside,* she thought, with the dry, precise part of her mind that had once been destined for courtrooms." | | 4 | "Where the boundary bank should have run, there was only a long, unbroken line of oaks, each one leaning a little toward the centre of the grove, as though they …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |