| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 24 | | tagDensity | 0.125 | | leniency | 0.25 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.28% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1295 | | totalAiIsmAdverbs | 2 | | 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) | |
| 72.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1295 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "echo" | | 1 | "weight" | | 2 | "throbbed" | | 3 | "pulse" | | 4 | "could feel" | | 5 | "warmth" |
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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 | 109 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 109 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 129 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 8 | | markdownWords | 20 | | totalWords | 1294 | | ratio | 0.015 | | matches | | 0 | "deer" | | 1 | "too much like candle" | | 2 | "product" | | 3 | "ory" | | 4 | "where" | | 5 | "Midnight. The stones. Come alone, Aurora." | | 6 | "Thank you for coming." | | 7 | "Au-ro-ra, love?" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 1119 | | uniqueNames | 12 | | maxNameDensity | 0.45 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Roehampton | 1 | | Gate | 1 | | Golden | 1 | | Empress | 1 | | Kingston | 1 | | October | 2 | | Rory | 5 | | Isolde | 4 | | January | 1 | | Eva | 4 | | May | 1 | | Cardiff | 1 |
| | persons | | 0 | "Rory" | | 1 | "Isolde" | | 2 | "January" | | 3 | "Eva" |
| | places | | 0 | "Roehampton" | | 1 | "Kingston" | | 2 | "October" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 66.67% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 2 | | matches | | 0 | "seemed loud enough to carry" | | 1 | "looked like a vein" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.773 | | wordCount | 1294 | | matches | | 0 | "no longer birdsong but" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 129 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 20.87 | | std | 22.8 | | cv | 1.092 | | sampleLengths | | 0 | 76 | | 1 | 6 | | 2 | 6 | | 3 | 5 | | 4 | 24 | | 5 | 16 | | 6 | 27 | | 7 | 22 | | 8 | 8 | | 9 | 13 | | 10 | 75 | | 11 | 3 | | 12 | 1 | | 13 | 9 | | 14 | 5 | | 15 | 56 | | 16 | 4 | | 17 | 44 | | 18 | 10 | | 19 | 3 | | 20 | 16 | | 21 | 86 | | 22 | 11 | | 23 | 5 | | 24 | 10 | | 25 | 1 | | 26 | 1 | | 27 | 17 | | 28 | 1 | | 29 | 5 | | 30 | 49 | | 31 | 3 | | 32 | 49 | | 33 | 6 | | 34 | 39 | | 35 | 35 | | 36 | 8 | | 37 | 53 | | 38 | 4 | | 39 | 4 | | 40 | 4 | | 41 | 57 | | 42 | 7 | | 43 | 41 | | 44 | 7 | | 45 | 11 | | 46 | 2 | | 47 | 28 | | 48 | 3 | | 49 | 70 |
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| 95.61% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 109 | | matches | | 0 | "been locked" | | 1 | "was flattened" | | 2 | "been between" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 178 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 129 | | ratio | 0.008 | | matches | | 0 | "\"—and I said, madam, that's the *product*—Rory? You've gone quiet.\"" |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 334 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 4 | | adverbRatio | 0.011976047904191617 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0029940119760479044 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 129 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 129 | | mean | 10.03 | | std | 9.26 | | cv | 0.923 | | sampleLengths | | 0 | 21 | | 1 | 27 | | 2 | 19 | | 3 | 9 | | 4 | 6 | | 5 | 6 | | 6 | 5 | | 7 | 24 | | 8 | 16 | | 9 | 27 | | 10 | 15 | | 11 | 2 | | 12 | 5 | | 13 | 8 | | 14 | 13 | | 15 | 31 | | 16 | 18 | | 17 | 26 | | 18 | 3 | | 19 | 1 | | 20 | 9 | | 21 | 5 | | 22 | 26 | | 23 | 10 | | 24 | 6 | | 25 | 14 | | 26 | 4 | | 27 | 2 | | 28 | 2 | | 29 | 8 | | 30 | 2 | | 31 | 30 | | 32 | 10 | | 33 | 3 | | 34 | 16 | | 35 | 7 | | 36 | 20 | | 37 | 23 | | 38 | 5 | | 39 | 31 | | 40 | 4 | | 41 | 7 | | 42 | 5 | | 43 | 4 | | 44 | 6 | | 45 | 1 | | 46 | 1 | | 47 | 4 | | 48 | 6 | | 49 | 7 |
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| 72.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.4566929133858268 | | totalSentences | 127 | | uniqueOpeners | 58 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 87 | | matches | | 0 | "Somewhere off to the left" | | 1 | "Then Eva's voice, slowed and" | | 2 | "Then a third." | | 3 | "Somewhere past the far stone," |
| | ratio | 0.046 | |
| 91.26% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 87 | | matches | | 0 | "She still smelled of the" | | 1 | "Her phone buzzed against her" | | 2 | "She'd stopped noticing it most" | | 3 | "It came a third time," | | 4 | "They weren't stones at all," | | 5 | "She'd been here twice in" | | 6 | "She stopped at the edge" | | 7 | "They were all closed." | | 8 | "She checked the time out" | | 9 | "She stepped over the boundary." | | 10 | "Her own heartbeat seemed loud" | | 11 | "She walked to the centre," | | 12 | "She heard it." | | 13 | "she said to nobody" | | 14 | "She pulled the leaf from" | | 15 | "She fished it out by" | | 16 | "She held her breath." | | 17 | "She took a step towards" | | 18 | "It stopped, one crunch late." | | 19 | "She lifted her foot and" |
| | ratio | 0.322 | |
| 97.93% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 87 | | matches | | 0 | "The last bus had dropped" | | 1 | "Rory went over the railings" | | 2 | "She still smelled of the" | | 3 | "Yu-Fei had let her go" | | 4 | "Her phone buzzed against her" | | 5 | "Rory laughed, and the sound" | | 6 | "The field swallowed it whole." | | 7 | "The track curved towards the" | | 8 | "Eva launched into something about" | | 9 | "The pendant lay cold against" | | 10 | "She'd stopped noticing it most" | | 11 | "Tonight she kept touching it" | | 12 | "The stag coughed again." | | 13 | "It came a third time," | | 14 | "\"—and I said, madam, that's" | | 15 | "The oak stones rose out" | | 16 | "They weren't stones at all," | | 17 | "She'd been here twice in" | | 18 | "She stopped at the edge" | | 19 | "They were all closed." |
| | ratio | 0.724 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 87 | | matches | | 0 | "Now it tasted of nothing." | | 1 | "Now there was only bracken," |
| | ratio | 0.023 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 1 | | matches | | 0 | "It came a third time, from the right now, and it was the identical sound, as though someone had recorded it and was playing it back from a different speaker." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 24 | | tagDensity | 0.083 | | leniency | 0.167 | | rawRatio | 0 | | effectiveRatio | 0 | |