| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "Nyx’s voice scraped like [like]" |
| | dialogueSentences | 26 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.077 | | effectiveRatio | 0.077 | |
| 97.06% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1703 | | 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) | |
| 32.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1703 | | totalAiIsms | 23 | | found | | | highlights | | 0 | "pulsed" | | 1 | "chill" | | 2 | "weight" | | 3 | "pulse" | | 4 | "throbbed" | | 5 | "vibrated" | | 6 | "fractured" | | 7 | "perfect" | | 8 | "tension" | | 9 | "silk" | | 10 | "echoes" | | 11 | "flickered" | | 12 | "churning" | | 13 | "scanned" | | 14 | "shimmered" | | 15 | "echoed" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "knuckles turned white" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "Knuckles went white" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 188 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 188 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 201 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1703 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 1417 | | uniqueNames | 9 | | maxNameDensity | 1.27 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 1 | | London | 1 | | December | 1 | | Silver | 2 | | Rory | 18 | | Bark | 3 | | Nyx | 8 | | Heat | 3 | | Isolde | 6 |
| | persons | | 0 | "December" | | 1 | "Rory" | | 2 | "Bark" | | 3 | "Nyx" | | 4 | "Heat" | | 5 | "Isolde" |
| | places | | 0 | "Richmond" | | 1 | "London" | | 2 | "Silver" |
| | globalScore | 0.865 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 113 | | 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 | 1703 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 201 | | matches | (empty) | |
| 34.94% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 48.66 | | std | 13.25 | | cv | 0.272 | | sampleLengths | | 0 | 50 | | 1 | 39 | | 2 | 34 | | 3 | 63 | | 4 | 46 | | 5 | 36 | | 6 | 51 | | 7 | 56 | | 8 | 35 | | 9 | 25 | | 10 | 55 | | 11 | 45 | | 12 | 81 | | 13 | 54 | | 14 | 56 | | 15 | 31 | | 16 | 55 | | 17 | 44 | | 18 | 40 | | 19 | 34 | | 20 | 56 | | 21 | 43 | | 22 | 20 | | 23 | 60 | | 24 | 31 | | 25 | 70 | | 26 | 60 | | 27 | 53 | | 28 | 61 | | 29 | 48 | | 30 | 50 | | 31 | 52 | | 32 | 63 | | 33 | 38 | | 34 | 68 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 188 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 261 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 201 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1421 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.017593244194229415 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0007037297677691766 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 201 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 201 | | mean | 8.47 | | std | 5.78 | | cv | 0.682 | | sampleLengths | | 0 | 11 | | 1 | 9 | | 2 | 5 | | 3 | 9 | | 4 | 11 | | 5 | 5 | | 6 | 10 | | 7 | 14 | | 8 | 7 | | 9 | 8 | | 10 | 8 | | 11 | 4 | | 12 | 13 | | 13 | 9 | | 14 | 2 | | 15 | 2 | | 16 | 15 | | 17 | 3 | | 18 | 10 | | 19 | 17 | | 20 | 4 | | 21 | 10 | | 22 | 12 | | 23 | 10 | | 24 | 10 | | 25 | 2 | | 26 | 3 | | 27 | 9 | | 28 | 11 | | 29 | 15 | | 30 | 4 | | 31 | 6 | | 32 | 11 | | 33 | 9 | | 34 | 12 | | 35 | 10 | | 36 | 4 | | 37 | 5 | | 38 | 24 | | 39 | 8 | | 40 | 11 | | 41 | 13 | | 42 | 3 | | 43 | 11 | | 44 | 7 | | 45 | 4 | | 46 | 7 | | 47 | 3 | | 48 | 14 | | 49 | 11 |
| |
| 46.27% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.31343283582089554 | | totalSentences | 201 | | uniqueOpeners | 63 | |
| 19.27% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 173 | | matches | | | ratio | 0.006 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 47 | | totalSentences | 173 | | matches | | 0 | "Their silhouette bled into the" | | 1 | "She rolled her shoulders and" | | 2 | "Her bare feet kissed the" | | 3 | "She adjusted her stance and" | | 4 | "She tucked it under her" | | 5 | "She slowed her breathing." | | 6 | "They reached out a hand" | | 7 | "Her silhouette pooled at an" | | 8 | "It lagged a half-second behind" | | 9 | "She rolled her wrist." | | 10 | "She kept walking." | | 11 | "She plucked a petal." | | 12 | "It dissolved into silver mist" | | 13 | "She tilted her head toward" | | 14 | "They pushed through the brambles." | | 15 | "She focused on the weight" | | 16 | "Their form rippled, losing density," | | 17 | "She held the dagger over" | | 18 | "She lowered the tip." | | 19 | "They burst into whispers." |
| | ratio | 0.272 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 160 | | totalSentences | 173 | | matches | | 0 | "The oak stones rose from" | | 1 | "Bark split into spirals that" | | 2 | "Air thickened around the archway." | | 3 | "Rory’s thumb brushed the silver" | | 4 | "The crimson gem against her" | | 5 | "Heat bled through her jumper." | | 6 | "Nyx’s voice scraped like dry" | | 7 | "Their silhouette bled into the" | | 8 | "Violet light pulsed where eyes" | | 9 | "Rory shifted her grip on" | | 10 | "The moonsilver edge caught a" | | 11 | "She rolled her shoulders and" | | 12 | "The London damp vanished, replaced" | | 13 | "Gold pooled in the hollows" | | 14 | "Wildflowers carpeted the ground in" | | 15 | "Clocks meant nothing here." | | 16 | "The weight of minutes stretched" | | 17 | "Isolde glided past the threshold" | | 18 | "Her bare feet kissed the" | | 19 | "Rory watched her own boots" |
| | ratio | 0.925 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 173 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 2 | | matches | | 0 | "She tilted her head toward a narrow deer trail that vanished into a thicket of silver-leafed brambles." | | 1 | "Vines hung from the canopy, thick as ropes, studded with fruit that glowed with a faint inner bioluminescence." |
| |
| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 1 | | matches | | 0 | "Nyx’s form condensed, shoulders squaring, violet eyes fixed on the ripple" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |