| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 27 | | adverbTagCount | 2 | | adverbTags | | 0 | "Eva snapped back [back]" | | 1 | "Quinn said evenly [evenly]" |
| | dialogueSentences | 59 | | tagDensity | 0.458 | | leniency | 0.915 | | rawRatio | 0.074 | | effectiveRatio | 0.068 | |
| 91.88% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1232 | | 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) | |
| 67.53% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1232 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "gloom" | | 1 | "familiar" | | 2 | "echoed" | | 3 | "measured" | | 4 | "glinting" | | 5 | "complex" | | 6 | "magnetic" | | 7 | "flickered" |
| |
| 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 | 110 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1232 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 825 | | uniqueNames | 8 | | maxNameDensity | 2.55 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 21 | | Camden | 1 | | Victorian | 1 | | Morris | 1 | | Two | 1 | | Oxford-polished | 1 | | Eva | 8 | | Vance | 11 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Eva" | | 3 | "Vance" |
| | places | | | globalScore | 0.227 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | 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 | 1232 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 23.69 | | std | 15.52 | | cv | 0.655 | | sampleLengths | | 0 | 14 | | 1 | 11 | | 2 | 20 | | 3 | 46 | | 4 | 31 | | 5 | 6 | | 6 | 44 | | 7 | 34 | | 8 | 31 | | 9 | 9 | | 10 | 59 | | 11 | 6 | | 12 | 65 | | 13 | 1 | | 14 | 17 | | 15 | 30 | | 16 | 20 | | 17 | 8 | | 18 | 7 | | 19 | 25 | | 20 | 14 | | 21 | 74 | | 22 | 29 | | 23 | 16 | | 24 | 21 | | 25 | 44 | | 26 | 8 | | 27 | 21 | | 28 | 30 | | 29 | 23 | | 30 | 36 | | 31 | 21 | | 32 | 4 | | 33 | 30 | | 34 | 21 | | 35 | 6 | | 36 | 25 | | 37 | 28 | | 38 | 11 | | 39 | 21 | | 40 | 23 | | 41 | 7 | | 42 | 44 | | 43 | 26 | | 44 | 30 | | 45 | 8 | | 46 | 44 | | 47 | 13 | | 48 | 15 | | 49 | 17 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 78 | | matches | (empty) | |
| 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 | 110 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 832 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 19 | | adverbRatio | 0.02283653846153846 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.016826923076923076 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 11.2 | | std | 5.7 | | cv | 0.509 | | sampleLengths | | 0 | 14 | | 1 | 11 | | 2 | 10 | | 3 | 10 | | 4 | 3 | | 5 | 19 | | 6 | 17 | | 7 | 7 | | 8 | 12 | | 9 | 7 | | 10 | 12 | | 11 | 6 | | 12 | 14 | | 13 | 15 | | 14 | 15 | | 15 | 9 | | 16 | 25 | | 17 | 15 | | 18 | 12 | | 19 | 4 | | 20 | 5 | | 21 | 4 | | 22 | 18 | | 23 | 18 | | 24 | 23 | | 25 | 6 | | 26 | 23 | | 27 | 13 | | 28 | 10 | | 29 | 19 | | 30 | 1 | | 31 | 10 | | 32 | 7 | | 33 | 25 | | 34 | 5 | | 35 | 20 | | 36 | 6 | | 37 | 2 | | 38 | 4 | | 39 | 3 | | 40 | 11 | | 41 | 14 | | 42 | 9 | | 43 | 5 | | 44 | 10 | | 45 | 17 | | 46 | 14 | | 47 | 9 | | 48 | 24 | | 49 | 16 |
| |
| 85.76% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5363636363636364 | | totalSentences | 110 | | uniqueOpeners | 59 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 70 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 70 | | matches | | 0 | "She dropped the final three" | | 1 | "It scorched the back of" | | 2 | "His breath wheezed in the" | | 3 | "Her closely cropped salt-and-pepper hair" | | 4 | "It stirred a three-year-old ache" | | 5 | "She tripped on the final" | | 6 | "She gripped a battered brown" | | 7 | "she said, her voice clipped," | | 8 | "Her green eyes darted past" | | 9 | "Her hand stopped midway to" | | 10 | "He kicked aside a cluster" | | 11 | "It ceased its frantic spin" |
| | ratio | 0.171 | |
| 17.14% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 62 | | totalSentences | 70 | | matches | | 0 | "Quinn stepped over the severed" | | 1 | "Water dripped somewhere behind the" | | 2 | "Vance called from the platform" | | 3 | "Quinn ignored him." | | 4 | "She dropped the final three" | | 5 | "The air in the disused" | | 6 | "It scorched the back of" | | 7 | "Vance said, lumbering down behind" | | 8 | "His breath wheezed in the" | | 9 | "The corpse sat propped against" | | 10 | "The man had died upright," | | 11 | "A halogen work lamp cast" | | 12 | "Vance pulled a latex glove" | | 13 | "Quinn knelt, her trouser hem" | | 14 | "Her closely cropped salt-and-pepper hair" | | 15 | "Vance crouched beside her, scowling." | | 16 | "Quinn drew a steel ruler" | | 17 | "The victim's cotton shirt flared" | | 18 | "Quinn adjusted the worn leather" | | 19 | "The second hand twitched erratically," |
| | ratio | 0.886 | |
| 71.43% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 70 | | matches | | | ratio | 0.014 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 27 | | uselessAdditionCount | 3 | | matches | | 0 | "Quinn knelt, her trouser hem brushing the grimy sleeper" | | 1 | "Eva said, her tone dropping into something icy" | | 2 | "Vance drew, his bravado vanishing into the black" |
| |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 20 | | fancyCount | 9 | | fancyTags | | 0 | "a uniform shouted (shout)" | | 1 | "the constable wheezed (wheeze)" | | 2 | "Vance barked (bark)" | | 3 | "Eva snapped back (snap)" | | 4 | "Vance demanded (demand)" | | 5 | "Vance interrupted (interrupt)" | | 6 | "Eva hissed (hiss)" | | 7 | "Quinn ordered (order)" | | 8 | "Eva shouted (shout)" |
| | dialogueSentences | 59 | | tagDensity | 0.339 | | leniency | 0.678 | | rawRatio | 0.45 | | effectiveRatio | 0.305 | |