| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.44% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1405 | | 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) | |
| 46.62% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1405 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "etched" | | 1 | "warmth" | | 2 | "chill" | | 3 | "weight" | | 4 | "vibrated" | | 5 | "aligned" | | 6 | "scanned" | | 7 | "calculated" | | 8 | "measured" | | 9 | "silence" | | 10 | "perfect" | | 11 | "spectral" |
| |
| 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 | 100 | | matches | (empty) | |
| 85.71% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 0 | | narrationSentences | 100 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 111 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1405 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 1168 | | uniqueNames | 6 | | maxNameDensity | 0.94 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 11 | | Quinn | 1 | | Camden | 2 | | Kowalski | 1 | | Eva | 11 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Camden" | | 3 | "Kowalski" | | 4 | "Eva" | | 5 | "Morris" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 85 | | glossingSentenceCount | 1 | | matches | | 0 | "as if reaching for a door that never existed" |
| |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.135 | | wordCount | 1405 | | matches | | 0 | "no common watch or necklace but" | | 1 | "not blood, not water, but clear" | | 2 | "not water, but clear" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 111 | | matches | (empty) | |
| 87.01% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 46.83 | | std | 21.29 | | cv | 0.455 | | sampleLengths | | 0 | 63 | | 1 | 30 | | 2 | 19 | | 3 | 102 | | 4 | 19 | | 5 | 22 | | 6 | 89 | | 7 | 56 | | 8 | 42 | | 9 | 78 | | 10 | 42 | | 11 | 46 | | 12 | 22 | | 13 | 68 | | 14 | 28 | | 15 | 49 | | 16 | 25 | | 17 | 52 | | 18 | 76 | | 19 | 26 | | 20 | 67 | | 21 | 40 | | 22 | 49 | | 23 | 22 | | 24 | 54 | | 25 | 38 | | 26 | 32 | | 27 | 47 | | 28 | 63 | | 29 | 39 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 100 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 200 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 111 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1113 | | adjectiveStacks | 1 | | stackExamples | | 0 | "closed under unexplained circumstances." |
| | adverbCount | 27 | | adverbRatio | 0.02425876010781671 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.0071877807726864335 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 111 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 111 | | mean | 12.66 | | std | 6.21 | | cv | 0.491 | | sampleLengths | | 0 | 21 | | 1 | 19 | | 2 | 23 | | 3 | 20 | | 4 | 10 | | 5 | 6 | | 6 | 13 | | 7 | 15 | | 8 | 14 | | 9 | 5 | | 10 | 17 | | 11 | 15 | | 12 | 3 | | 13 | 15 | | 14 | 18 | | 15 | 9 | | 16 | 10 | | 17 | 3 | | 18 | 19 | | 19 | 6 | | 20 | 24 | | 21 | 31 | | 22 | 6 | | 23 | 6 | | 24 | 16 | | 25 | 14 | | 26 | 12 | | 27 | 17 | | 28 | 13 | | 29 | 11 | | 30 | 31 | | 31 | 10 | | 32 | 9 | | 33 | 10 | | 34 | 20 | | 35 | 9 | | 36 | 20 | | 37 | 10 | | 38 | 13 | | 39 | 19 | | 40 | 6 | | 41 | 18 | | 42 | 12 | | 43 | 10 | | 44 | 4 | | 45 | 18 | | 46 | 8 | | 47 | 19 | | 48 | 6 | | 49 | 8 |
| |
| 44.59% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.2882882882882883 | | totalSentences | 111 | | uniqueOpeners | 32 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 97 | | matches | (empty) | | ratio | 0 | |
| 42.68% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 43 | | totalSentences | 97 | | matches | | 0 | "She held her worn leather" | | 1 | "She crouched beside the body," | | 2 | "His coat lay open over" | | 3 | "She leaned closer." | | 4 | "She took the compass, thumb" | | 5 | "She noted the man's fingers" | | 6 | "She examined the nearest constable's" | | 7 | "She tracked scuff marks leading" | | 8 | "They stopped short of the" | | 9 | "She pressed her palm against" | | 10 | "She swept her beam across" | | 11 | "She freed it and held" | | 12 | "Its length matched no common" | | 13 | "She followed the scuff trail" | | 14 | "She returned to the sand" | | 15 | "She brushed a fingertip along" | | 16 | "She found no wallet, no" | | 17 | "She set it beside the" | | 18 | "She recalled reports of an" | | 19 | "She gestured them back toward" |
| | ratio | 0.443 | |
| 1.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 89 | | totalSentences | 97 | | matches | | 0 | "Detective Harlow Quinn descended the" | | 1 | "The air hung thick with" | | 2 | "Police tape stretched across the" | | 3 | "Eva Kowalski stood by the" | | 4 | "She held her worn leather" | | 5 | "Harlow moved past the tape" | | 6 | "She crouched beside the body," | | 7 | "His coat lay open over" | | 8 | "Sand scattered around his hands" | | 9 | "She leaned closer." | | 10 | "The grains formed faint sigils," | | 11 | "She took the compass, thumb" | | 12 | "The needle swung toward the" | | 13 | "Eva stepped nearer." | | 14 | "Harlow rose and circled the" | | 15 | "She noted the man's fingers" | | 16 | "The bones Eva mentioned rested" | | 17 | "She examined the nearest constable's" | | 18 | "The time of death sat" | | 19 | "She tracked scuff marks leading" |
| | ratio | 0.918 | |
| 51.55% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 97 | | matches | | 0 | "Before she could signal the" |
| | ratio | 0.01 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 3 | | matches | | 0 | "His coat lay open over a shirt stained with dark ash patterns that spiraled outward like runes." | | 1 | "The bones Eva mentioned rested in separate plastic trays on a folding table: small human phalanges arranged in a circle, each etched with symbols that matched t…" | | 2 | "She recalled reports of an underground market that shifted under full moons, trading in artifacts that left such traces." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 78.57% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "Harlow continued (continue)" |
| | dialogueSentences | 14 | | tagDensity | 0.214 | | leniency | 0.429 | | rawRatio | 0.333 | | effectiveRatio | 0.143 | |