| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 38 | | tagDensity | 0.211 | | leniency | 0.421 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.29% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1348 | | 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) | |
| 14.69% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1348 | | totalAiIsms | 23 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "scanned" | | 1 | "glinting" | | 2 | "shattered" | | 3 | "etched" | | 4 | "quivered" | | 5 | "traced" | | 6 | "pulse" | | 7 | "flicked" | | 8 | "raced" | | 9 | "echoing" | | 10 | "resonance" | | 11 | "flicker" | | 12 | "tracing" | | 13 | "pulsed" | | 14 | "echoed" | | 15 | "tension" | | 16 | "weight" | | 17 | "aligned" | | 18 | "flickered" |
| |
| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
| | 1 | | label | "clenched jaw/fists" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "eyes widened" | | 2 | "clenched fist" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 87 | | matches | (empty) | |
| 60.76% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 2 | | narrationSentences | 87 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 117 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1347 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 987 | | uniqueNames | 8 | | maxNameDensity | 1.72 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 17 | | Kowalski | 1 | | Veil | 2 | | Compass | 1 | | Eva | 10 | | Mara | 1 | | Shade | 1 | | Market | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Kowalski" | | 2 | "Veil" | | 3 | "Compass" | | 4 | "Eva" | | 5 | "Mara" |
| | places | (empty) | | globalScore | 0.639 | | windowScore | 0.5 | |
| 44.37% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | glossingSentenceCount | 3 | | matches | | 0 | "as if breathing" | | 1 | "felt like a throat being torn open" | | 2 | "seemed contradictory now formed a clear line: a Shade artisan, a compass, a sigil, a collector’s greed, a rift that threatened to spill into the world" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.742 | | wordCount | 1347 | | matches | | 0 | "not toward the market’s exit but toward a dark alcove" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 117 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 31.33 | | std | 15.96 | | cv | 0.509 | | sampleLengths | | 0 | 72 | | 1 | 53 | | 2 | 46 | | 3 | 12 | | 4 | 40 | | 5 | 18 | | 6 | 54 | | 7 | 46 | | 8 | 9 | | 9 | 14 | | 10 | 47 | | 11 | 39 | | 12 | 43 | | 13 | 21 | | 14 | 20 | | 15 | 30 | | 16 | 16 | | 17 | 18 | | 18 | 39 | | 19 | 36 | | 20 | 15 | | 21 | 9 | | 22 | 28 | | 23 | 39 | | 24 | 22 | | 25 | 16 | | 26 | 46 | | 27 | 28 | | 28 | 15 | | 29 | 46 | | 30 | 37 | | 31 | 11 | | 32 | 18 | | 33 | 15 | | 34 | 17 | | 35 | 41 | | 36 | 25 | | 37 | 23 | | 38 | 15 | | 39 | 54 | | 40 | 48 | | 41 | 45 | | 42 | 61 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 87 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 175 | | matches | (empty) | |
| 94.02% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 117 | | ratio | 0.017 | | matches | | 0 | "Ink seeped into the cracks, forming a pattern that resembled a sigil she’d seen on a case file—an inverted triangle intersected by a line." | | 1 | "The evidence no longer contradicted; it aligned." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 988 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.01720647773279352 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0020242914979757085 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 117 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 117 | | mean | 11.51 | | std | 5.86 | | cv | 0.509 | | sampleLengths | | 0 | 14 | | 1 | 17 | | 2 | 23 | | 3 | 18 | | 4 | 4 | | 5 | 12 | | 6 | 20 | | 7 | 17 | | 8 | 13 | | 9 | 12 | | 10 | 9 | | 11 | 12 | | 12 | 3 | | 13 | 9 | | 14 | 7 | | 15 | 13 | | 16 | 20 | | 17 | 13 | | 18 | 5 | | 19 | 7 | | 20 | 24 | | 21 | 9 | | 22 | 9 | | 23 | 5 | | 24 | 11 | | 25 | 20 | | 26 | 15 | | 27 | 3 | | 28 | 6 | | 29 | 5 | | 30 | 9 | | 31 | 9 | | 32 | 19 | | 33 | 9 | | 34 | 10 | | 35 | 12 | | 36 | 27 | | 37 | 7 | | 38 | 10 | | 39 | 10 | | 40 | 16 | | 41 | 9 | | 42 | 12 | | 43 | 3 | | 44 | 17 | | 45 | 7 | | 46 | 23 | | 47 | 5 | | 48 | 11 | | 49 | 3 |
| |
| 37.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.21367521367521367 | | totalSentences | 117 | | uniqueOpeners | 25 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 84 | | matches | | 0 | "Her left wrist bore a" | | 1 | "She scanned the crowd." | | 2 | "She tucked a curl behind" | | 3 | "she whispered, voice low" | | 4 | "She knelt, feeling the cold" | | 5 | "He glanced at the bone" | | 6 | "She flipped to a page" | | 7 | "She pressed her palm to" | | 8 | "she said, voice flat" | | 9 | "She turned to the vendor." | | 10 | "He held a brass pipe," | | 11 | "he said, voice low" | | 12 | "She turned to the alcove," | | 13 | "She pressed its button, a" | | 14 | "She placed the compass on" | | 15 | "She glanced at the corpse," | | 16 | "She lifted her watch, the" | | 17 | "She paused at the doorway," | | 18 | "She turned, the bone token" | | 19 | "She pulled her coat tighter," |
| | ratio | 0.238 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 84 | | matches | | 0 | "The air in the abandoned" | | 1 | "Harlow Quinn stepped through the" | | 2 | "Her left wrist bore a" | | 3 | "She scanned the crowd." | | 4 | "Figures in hooded cloaks moved" | | 5 | "A body curled on the" | | 6 | "Eva Kowalski knelt beside the" | | 7 | "She tucked a curl behind" | | 8 | "she whispered, voice low" | | 9 | "Quinn’s jaw tightened." | | 10 | "Eva lifted the compass, turning" | | 11 | "The brass casing bore a" | | 12 | "The needle quivered, pointing not" | | 13 | "Eva said, eyes flicking to" | | 14 | "Quinn’s gaze lingered on the" | | 15 | "Ink seeped into the cracks," | | 16 | "She knelt, feeling the cold" | | 17 | "A vendor in a tattered" | | 18 | "He glanced at the bone" | | 19 | "Quinn’s eyes narrowed." |
| | ratio | 0.976 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 3 | | matches | | 0 | "She turned to the alcove, the door now trembling as if breathing." | | 1 | "Quinn walked toward the exit, her steps echoing on the stone, the compass heavy in her pocket, the watch ticking in rhythm with her heartbeat." | | 2 | "The evidence that had seemed contradictory now formed a clear line: a Shade artisan, a compass, a sigil, a collector’s greed, a rift that threatened to spill in…" |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 4 | | matches | | 0 | "she whispered, voice low" | | 1 | "Eva said, eyes flicking to the alcove" | | 2 | "she said, voice flat" | | 3 | "he said, voice low" |
| |
| 97.37% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 2 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "she observed (observe)" |
| | dialogueSentences | 38 | | tagDensity | 0.184 | | leniency | 0.368 | | rawRatio | 0.286 | | effectiveRatio | 0.105 | |