| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 30 | | tagDensity | 0.533 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 986 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 64.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 986 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "symphony" | | 1 | "scanned" | | 2 | "calculated" | | 3 | "weight" | | 4 | "familiar" | | 5 | "silence" | | 6 | "reminder" |
| |
| 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 | 51 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 51 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 93.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 66 | | gibberishSentences | 1 | | adjustedGibberishSentences | 1 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0.015 | | matches | | 0 | "\"I'd hoped to be further along. Must be, it knocks the beast out of you at least, doesn't it. The beast- the DA走吧 beast, I mean.\"" |
| |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 984 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 5.93% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 590 | | uniqueNames | 10 | | maxNameDensity | 2.88 | | worstName | "Silas" | | maxWindowNameDensity | 4 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Saturday | 1 | | Blackwood | 1 | | Jae | 14 | | Silas | 17 | | Acknowledgements | 1 | | Boxy | 1 | | Jaime | 1 | | Rory | 4 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Blackwood" | | 3 | "Jae" | | 4 | "Silas" | | 5 | "Acknowledgements" | | 6 | "Jaime" | | 7 | "Rory" |
| | places | (empty) | | globalScore | 0.059 | | windowScore | 0.333 | |
| 93.18% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | glossingSentenceCount | 1 | | matches | | 0 | "Evidently, the bar's newest s" |
| |
| 98.37% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.016 | | wordCount | 984 | | matches | | 0 | "not on the streets outside his door, but inside" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 66 | | matches | | |
| 79.18% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 39.36 | | std | 16.81 | | cv | 0.427 | | sampleLengths | | 0 | 3 | | 1 | 54 | | 2 | 37 | | 3 | 29 | | 4 | 40 | | 5 | 41 | | 6 | 13 | | 7 | 32 | | 8 | 26 | | 9 | 40 | | 10 | 36 | | 11 | 79 | | 12 | 35 | | 13 | 30 | | 14 | 49 | | 15 | 47 | | 16 | 58 | | 17 | 61 | | 18 | 35 | | 19 | 46 | | 20 | 66 | | 21 | 55 | | 22 | 22 | | 23 | 32 | | 24 | 18 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 51 | | matches | (empty) | |
| 70.55% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 103 | | matches | | 0 | "was handling" | | 1 | "was affronting" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 66 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 418 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 10 | | adverbRatio | 0.023923444976076555 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.007177033492822967 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 66 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 66 | | mean | 14.91 | | std | 8.9 | | cv | 0.597 | | sampleLengths | | 0 | 21 | | 1 | 18 | | 2 | 18 | | 3 | 16 | | 4 | 13 | | 5 | 8 | | 6 | 27 | | 7 | 2 | | 8 | 18 | | 9 | 14 | | 10 | 8 | | 11 | 18 | | 12 | 23 | | 13 | 3 | | 14 | 9 | | 15 | 1 | | 16 | 2 | | 17 | 30 | | 18 | 11 | | 19 | 12 | | 20 | 3 | | 21 | 12 | | 22 | 13 | | 23 | 15 | | 24 | 36 | | 25 | 22 | | 26 | 31 | | 27 | 23 | | 28 | 3 | | 29 | 4 | | 30 | 9 | | 31 | 18 | | 32 | 4 | | 33 | 13 | | 34 | 17 | | 35 | 14 | | 36 | 23 | | 37 | 12 | | 38 | 27 | | 39 | 20 | | 40 | 27 | | 41 | 20 | | 42 | 11 | | 43 | 31 | | 44 | 23 | | 45 | 7 | | 46 | 11 | | 47 | 8 | | 48 | 8 | | 49 | 8 |
| |
| 87.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5606060606060606 | | totalSentences | 66 | | uniqueOpeners | 37 | |
| 66.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 50 | | matches | | 0 | "Evidently, the bar's newest server" |
| | ratio | 0.02 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 50 | | matches | | 0 | "His servers weaved between tables," | | 1 | "He put queasy unfamiliarness at" | | 2 | "He turned his whiskey in" | | 3 | "They'd been friends, once, at" | | 4 | "He wove his fingers into" | | 5 | "He lit a cigarette, filling" | | 6 | "She was handling a table" | | 7 | "He knew he had the" | | 8 | "She swept past, the scrubbed-wood" | | 9 | "He looked back and forth" | | 10 | "He meant to say something," | | 11 | "she bit her lip, fixing" | | 12 | "She needed that walk badly." |
| | ratio | 0.26 | |
| 10.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 50 | | matches | | 0 | "Silas Blackwood tilted a tumbler" | | 1 | "His servers weaved between tables," | | 2 | "A tall man pushed through" | | 3 | "Hazel eyes scanned the bar," | | 4 | "Silas tensed as Jae's gaze" | | 5 | "Jae slid onto the barstool" | | 6 | "Silas slid a fresh whiskey" | | 7 | "Acknowledgements couldn't get the man" | | 8 | "Jae gave a mirthless laugh," | | 9 | "Silas appreciated evasiveness." | | 10 | "He put queasy unfamiliarness at" | | 11 | "He turned his whiskey in" | | 12 | "They'd been friends, once, at" | | 13 | "The nature of his death," | | 14 | "Silas broke the silence, figuring" | | 15 | "Silas rolled his whiskey in" | | 16 | "Jae's hand found its way" | | 17 | "He wove his fingers into" | | 18 | "He lit a cigarette, filling" | | 19 | "Silas followed his gaze." |
| | ratio | 0.9 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 50 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 19 | | technicalSentenceCount | 1 | | matches | | 0 | "His servers weaved between tables, deftly balancing trays of ales and hearty pies that would soon be devoured." |
| |
| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 2 | | matches | | 0 | "Jae gave, the sound dying before fading into the din" | | 1 | "Jae's hand found, fingers drumming" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |