| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.09% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 724 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 724 | | totalAiIsms | 15 | | found | | 0 | | | 1 | | | 2 | | word | "down her spine" | | count | 2 |
| | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | |
| | highlights | | 0 | "scanning" | | 1 | "chill" | | 2 | "down her spine" | | 3 | "quickened" | | 4 | "navigated" | | 5 | "glinting" | | 6 | "racing" | | 7 | "otherworldly" | | 8 | "wavered" | | 9 | "sense of" | | 10 | "unravel" | | 11 | "scanned" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "shiver down spine" | | count | 1 |
| | 1 | | label | "eyes widened/narrowed" | | count | 1 |
|
| | highlights | | 0 | "a shiver ran down her spine" | | 1 | "eyes widened" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 44 | | matches | (empty) | |
| 0.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 5 | | narrationSentences | 44 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 52 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 723 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 28.68% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 577 | | uniqueNames | 6 | | maxNameDensity | 2.43 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 14 | | Tube | 1 | | Camden | 1 | | Ray | 8 | | Veil | 3 | | Market | 3 |
| | persons | | | places | | | globalScore | 0.287 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 42 | | 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 | 723 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 52 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 19 | | mean | 38.05 | | std | 19.52 | | cv | 0.513 | | sampleLengths | | 0 | 73 | | 1 | 8 | | 2 | 51 | | 3 | 64 | | 4 | 29 | | 5 | 52 | | 6 | 26 | | 7 | 10 | | 8 | 32 | | 9 | 59 | | 10 | 44 | | 11 | 13 | | 12 | 20 | | 13 | 28 | | 14 | 46 | | 15 | 73 | | 16 | 34 | | 17 | 24 | | 18 | 37 |
| |
| 89.31% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 44 | | matches | | 0 | "was posed" | | 1 | "been missed" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 102 | | matches | | |
| 87.91% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 52 | | ratio | 0.019 | | matches | | 0 | "The positing, the symbols – all of it screamed of a message." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 578 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 11 | | adverbRatio | 0.01903114186851211 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.00865051903114187 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 52 | | echoCount | 0 | | echoWords | (empty) | |
| 84.32% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 52 | | mean | 13.9 | | std | 5.02 | | cv | 0.361 | | sampleLengths | | 0 | 21 | | 1 | 7 | | 2 | 12 | | 3 | 17 | | 4 | 16 | | 5 | 8 | | 6 | 12 | | 7 | 11 | | 8 | 18 | | 9 | 10 | | 10 | 13 | | 11 | 8 | | 12 | 12 | | 13 | 20 | | 14 | 11 | | 15 | 22 | | 16 | 7 | | 17 | 12 | | 18 | 14 | | 19 | 12 | | 20 | 14 | | 21 | 26 | | 22 | 5 | | 23 | 5 | | 24 | 13 | | 25 | 19 | | 26 | 11 | | 27 | 11 | | 28 | 12 | | 29 | 11 | | 30 | 14 | | 31 | 14 | | 32 | 13 | | 33 | 17 | | 34 | 13 | | 35 | 9 | | 36 | 11 | | 37 | 7 | | 38 | 21 | | 39 | 14 | | 40 | 15 | | 41 | 17 | | 42 | 26 | | 43 | 21 | | 44 | 26 | | 45 | 18 | | 46 | 16 | | 47 | 10 | | 48 | 14 | | 49 | 14 |
| |
| 58.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.38461538461538464 | | totalSentences | 52 | | uniqueOpeners | 20 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 44 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 9 | | totalSentences | 44 | | matches | | 0 | "Her partner, DI Ray, was" | | 1 | "She navigated the rubble-strewn platform," | | 2 | "She remembered the case files" | | 3 | "Her gut told her there" | | 4 | "She took a deep breath," | | 5 | "Her mind whirred with theories" | | 6 | "she asked, holding up the" | | 7 | "They knew that in this" | | 8 | "She felt it, that creeping" |
| | ratio | 0.205 | |
| 28.18% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 38 | | totalSentences | 44 | | matches | | 0 | "Detective Quinn stepped out of" | | 1 | "The air reeked of mildew" | | 2 | "The abandoned station beneath Camden" | | 3 | "A chill ran down her" | | 4 | "Her partner, DI Ray, was" | | 5 | "Quinn quickened her pace, her" | | 6 | "She navigated the rubble-strewn platform," | | 7 | "The air seemed to thicken," | | 8 | "Aurora, the victim, lay on" | | 9 | "Quinn's gaze narrowed as she" | | 10 | "The young woman's body was" | | 11 | "The delicate fingers of her" | | 12 | "A hint of supernatural energy" | | 13 | "Quinn's eyes locked onto the" | | 14 | "She remembered the case files" | | 15 | "This symbol was too reminiscent" | | 16 | "Her gut told her there" | | 17 | "Quinn's gaze snapped to Ray." | | 18 | "Ray hesitated, glancing at the" | | 19 | "Quinn crouched beside the body," |
| | ratio | 0.864 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 44 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 2 | | matches | | 0 | "With the vial secure in her hand, Quinn began to examine the surrounding area more closely, searching for any other clues that might have been missed." | | 1 | "The air seemed to grow thick with an unseen presence, as if the very shadows themselves were watching her every move." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "Ray called out (call out)" | | 1 | "Ray continued (continue)" |
| | dialogueSentences | 12 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.667 | | effectiveRatio | 0.333 | |