| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 90.37% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 519 | | totalAiIsmAdverbs | 1 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 519 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "loomed" | | 1 | "sentinels" | | 2 | "shimmered" | | 3 | "scanning" | | 4 | "pulse" | | 5 | "pulsed" | | 6 | "footsteps" | | 7 | "weight" | | 8 | "could feel" | | 9 | "throbbed" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 64 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 64 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 64 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 19 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 6 | | totalWords | 517 | | ratio | 0.012 | | matches | | 0 | "Hel portal." | | 1 | "watched" | | 2 | "Aurora, Laila, Malphora" |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 11 | | wordCount | 517 | | uniqueNames | 6 | | maxNameDensity | 0.77 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Heartstone | 1 | | Richmond | 2 | | Park | 2 | | Laila | 1 | | London | 1 | | Rory | 4 |
| | persons | | | places | | 0 | "Heartstone" | | 1 | "Richmond" | | 2 | "Park" | | 3 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 37 | | 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 | 517 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 64 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 22 | | mean | 23.5 | | std | 23.22 | | cv | 0.988 | | sampleLengths | | 0 | 6 | | 1 | 68 | | 2 | 3 | | 3 | 5 | | 4 | 55 | | 5 | 3 | | 6 | 55 | | 7 | 4 | | 8 | 52 | | 9 | 9 | | 10 | 44 | | 11 | 3 | | 12 | 2 | | 13 | 52 | | 14 | 4 | | 15 | 43 | | 16 | 5 | | 17 | 44 | | 18 | 2 | | 19 | 43 | | 20 | 5 | | 21 | 10 |
| |
| 99.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 64 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 88 | | matches | | |
| 53.57% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 64 | | ratio | 0.031 | | matches | | 0 | "She caught fragments—her name, half-swallowed, then something older, guttural." | | 1 | "The whispers had become a chant, a litany of her names—*Aurora, Laila, Malphora*—each one a needle pricking her skin." |
| |
| 92.85% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 519 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.04816955684007707 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.011560693641618497 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 64 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 64 | | mean | 8.08 | | std | 5.18 | | cv | 0.641 | | sampleLengths | | 0 | 6 | | 1 | 17 | | 2 | 2 | | 3 | 2 | | 4 | 19 | | 5 | 10 | | 6 | 18 | | 7 | 3 | | 8 | 5 | | 9 | 12 | | 10 | 15 | | 11 | 11 | | 12 | 9 | | 13 | 8 | | 14 | 3 | | 15 | 2 | | 16 | 8 | | 17 | 7 | | 18 | 1 | | 19 | 10 | | 20 | 3 | | 21 | 5 | | 22 | 9 | | 23 | 10 | | 24 | 4 | | 25 | 13 | | 26 | 9 | | 27 | 5 | | 28 | 11 | | 29 | 14 | | 30 | 9 | | 31 | 2 | | 32 | 10 | | 33 | 13 | | 34 | 11 | | 35 | 4 | | 36 | 2 | | 37 | 2 | | 38 | 3 | | 39 | 2 | | 40 | 16 | | 41 | 9 | | 42 | 12 | | 43 | 15 | | 44 | 4 | | 45 | 17 | | 46 | 7 | | 47 | 19 | | 48 | 5 | | 49 | 8 |
| |
| 48.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.328125 | | totalSentences | 64 | | uniqueOpeners | 21 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 52 | | matches | | 0 | "Just the mist, coiling like" | | 1 | "Only the thud of her" | | 2 | "Then, the whispering started." | | 3 | "Just trees, just darkness." |
| | ratio | 0.077 | |
| 96.92% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 52 | | matches | | 0 | "She’d followed the signal for" | | 1 | "She stepped through." | | 2 | "She’d come for answers, not" | | 3 | "She turned slowly, scanning the" | | 4 | "Her breath hitched." | | 5 | "It came from everywhere and" | | 6 | "She caught fragments—her name, half-swallowed," | | 7 | "She yanked it free, the" | | 8 | "Its limbs bent at impossible" | | 9 | "She took a step back," | | 10 | "She didn’t slow down." | | 11 | "She could feel it, cold" | | 12 | "She burst through the stones." | | 13 | "She stumbled, gasping, her lungs" | | 14 | "She turned back." | | 15 | "She clenched her fist around" |
| | ratio | 0.308 | |
| 27.31% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 52 | | matches | | 0 | "The pendant burned against her" | | 1 | "Rory’s fingers flew to the" | | 2 | "She’d followed the signal for" | | 3 | "The standing stones loomed ahead," | | 4 | "She stepped through." | | 5 | "The grove swallowed her whole." | | 6 | "Wildflowers carpeted the ground, their" | | 7 | "A silver mist curled between" | | 8 | "The pendant’s heat ebbed, then" | | 9 | "*Hel portal.* The words slithered" | | 10 | "She’d come for answers, not" | | 11 | "A twig snapped." | | 12 | "The sound came from behind," | | 13 | "She turned slowly, scanning the" | | 14 | "Her breath hitched." | | 15 | "The grove was too quiet." | | 16 | "It came from everywhere and" | | 17 | "She caught fragments—her name, half-swallowed," | | 18 | "The pendant seared her skin." | | 19 | "She yanked it free, the" |
| | ratio | 0.865 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 85.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 2 | | matches | | 0 | "She’d followed the signal for hours, cutting through Richmond Park’s skeletal trees, their branches clawing at a moonless sky." | | 1 | "The crimson stone pulsed in time with the whispers, as if it were listening." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |