| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 2 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 930 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 56.99% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 930 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "sense of" | | 1 | "warmth" | | 2 | "chill" | | 3 | "loomed" | | 4 | "eyebrow" | | 5 | "weight" | | 6 | "lilt" | | 7 | "searing" |
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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 | 42 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 42 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 44 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 930 | | ratio | 0 | | matches | (empty) | |
| 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 | 27 | | wordCount | 867 | | uniqueNames | 15 | | maxNameDensity | 0.58 | | worstName | "Leo" | | maxWindowNameDensity | 2 | | worstWindowName | "Evan" | | discoveredNames | | Richmond | 1 | | Park | 1 | | Heartstone | 3 | | Eva | 1 | | Leo | 5 | | Carter | 1 | | Golden | 1 | | Empress | 1 | | November | 2 | | Grove | 2 | | England | 1 | | May | 1 | | Christmas | 1 | | Evan | 4 | | Cardiff | 2 |
| | persons | | 0 | "Heartstone" | | 1 | "Eva" | | 2 | "Leo" | | 3 | "Carter" | | 4 | "Empress" | | 5 | "Grove" | | 6 | "May" | | 7 | "Evan" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "England" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 37 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 92.47% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.075 | | wordCount | 930 | | matches | | |
| 0.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 4 | | totalSentences | 44 | | matches | | 0 | "called that afternoon, screaming that Leo" | | 1 | "noticed that an" | | 2 | "miscounted, that the" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 10 | | mean | 93 | | std | 62.16 | | cv | 0.668 | | sampleLengths | | 0 | 167 | | 1 | 142 | | 2 | 135 | | 3 | 34 | | 4 | 20 | | 5 | 88 | | 6 | 163 | | 7 | 17 | | 8 | 14 | | 9 | 150 |
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| 96.91% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 42 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 142 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 104 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 4 | | adverbRatio | 0.038461538461538464 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.009615384615384616 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 44 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 44 | | mean | 21.14 | | std | 10.75 | | cv | 0.508 | | sampleLengths | | 0 | 16 | | 1 | 34 | | 2 | 53 | | 3 | 31 | | 4 | 33 | | 5 | 20 | | 6 | 21 | | 7 | 40 | | 8 | 28 | | 9 | 33 | | 10 | 11 | | 11 | 15 | | 12 | 4 | | 13 | 18 | | 14 | 22 | | 15 | 25 | | 16 | 22 | | 17 | 18 | | 18 | 17 | | 19 | 1 | | 20 | 16 | | 21 | 20 | | 22 | 18 | | 23 | 10 | | 24 | 21 | | 25 | 18 | | 26 | 4 | | 27 | 3 | | 28 | 14 | | 29 | 19 | | 30 | 26 | | 31 | 18 | | 32 | 21 | | 33 | 19 | | 34 | 38 | | 35 | 22 | | 36 | 17 | | 37 | 14 | | 38 | 1 | | 39 | 24 | | 40 | 33 | | 41 | 26 | | 42 | 40 | | 43 | 26 |
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| 46.97% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.36363636363636365 | | totalSentences | 44 | | uniqueOpeners | 16 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 40 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 40 | | matches | | 0 | "My palm scraped raw on" | | 1 | "I’d crossed the boundary four" | | 2 | "His mum had found a" | | 3 | "I lifted my torch, its" | | 4 | "I’d noticed that an hour" | | 5 | "I rubbed at it, the" | | 6 | "I’d counted seven standing stones" | | 7 | "I blinked, counted again." | | 8 | "I told myself I’d miscounted," | | 9 | "I scrambled to my feet," | | 10 | "My voice sounded wrong, flat," | | 11 | "I spun, the torch beam" | | 12 | "I grabbed a handful of" | | 13 | "I scrubbed my hand against" | | 14 | "My boot caught on something" | | 15 | "I reached out, my hand" | | 16 | "I flipped the backpack over," | | 17 | "I flipped to the last" | | 18 | "It was not just the" | | 19 | "I turned the pad in" |
| | ratio | 0.55 | |
| 10.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 36 | | totalSentences | 40 | | matches | | 0 | "My palm scraped raw on" | | 1 | "I’d crossed the boundary four" | | 2 | "The Heartstone around my neck" | | 3 | "Eva had called that afternoon," | | 4 | "His mum had found a" | | 5 | "I lifted my torch, its" | | 6 | "I’d noticed that an hour" | | 7 | "The Grove ran warm, like" | | 8 | "The crescent scar on my" | | 9 | "I rubbed at it, the" | | 10 | "I’d counted seven standing stones" | | 11 | "I blinked, counted again." | | 12 | "The new one stood directly" | | 13 | "I told myself I’d miscounted," | | 14 | "The faint crimson glow from" | | 15 | "A child’s laugh, high and" | | 16 | "I scrambled to my feet," | | 17 | "My voice sounded wrong, flat," | | 18 | "The laugh came again, this" | | 19 | "I spun, the torch beam" |
| | ratio | 0.9 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 40 | | matches | | | ratio | 0.025 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 11 | | matches | | 0 | "Eva had called that afternoon, screaming that Leo Carter, the eight year old who’d hung around Golden Empress begging for extra prawn crackers the week before, …" | | 1 | "His mum had found a crumpled drawing of this exact grove tucked under his mattress, three oak stones and a field of wildflowers that did not grow anywhere in th…" | | 2 | "I’d noticed that an hour in, my breath staying locked in my lungs instead of pluming white in front of me." | | 3 | "The Grove ran warm, like someone had left a heating pad tucked under the soil, and bluebells and daisies pushed through the loam at my feet, blooms that died ba…" | | 4 | "But the Heartstone picked up its pace, pulsing so hard it thumped against my chest, matching the beat of my own heart." | | 5 | "I scrambled to my feet, my gloves slipping on the damp grass, the torch swinging wildly." | | 6 | "I reached out, my hand closing on nylon stitched with T-Rex patches, the same ones Leo had gushed about buying with his tenth birthday pocket money." | | 7 | "I fumbled for the meat thermometer in my coat pocket, my hands shaking so bad I dropped the torch, its beam rolling across the grass to point at the smooth new …" | | 8 | "The stone’s bark split down the middle, peeling back like sunburnt skin, and Evan stepped out of the gap, his boots sinking into the blood-wild wildflowers." | | 9 | "He held Leo’s limp hand in his, the child’s head lolling against his shoulder, and behind him, dozens of figures stepped from the treeline, every one of them be…" | | 10 | "The Heartstone burned through my shirt, searing my skin, as the circle of standing stones began to shift, closing the only path out of the Grove." |
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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 | |