| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 8 | | tagDensity | 0.625 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 74.07% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 964 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "anxiously" | | 1 | "suddenly" | | 2 | "slowly" |
| |
| 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) | |
| 22.20% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 964 | | totalAiIsms | 15 | | found | | 0 | | word | "practiced ease" | | count | 1 |
| | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | |
| | highlights | | 0 | "practiced ease" | | 1 | "pounding" | | 2 | "scanned" | | 3 | "flickered" | | 4 | "footsteps" | | 5 | "echoing" | | 6 | "silence" | | 7 | "scanning" | | 8 | "could feel" | | 9 | "sense of" | | 10 | "clandestine" | | 11 | "measured" | | 12 | "sanctuary" | | 13 | "raced" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
| | 1 | | label | "couldn't help but" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "couldn't help but wonder" |
| |
| 73.98% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 3 | | narrationSentences | 49 | | matches | | 0 | "the sense of unease" | | 1 | "a surge of frustration" | | 2 | "r with dread" |
| |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 49 | | 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 | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 961 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 37.01% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 885 | | uniqueNames | 12 | | maxNameDensity | 2.26 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Harlow" | | discoveredNames | | Detective | 1 | | Harlow | 20 | | Quinn | 1 | | Raven | 2 | | Nest | 2 | | Soho | 1 | | Ford | 1 | | One | 1 | | Tomás | 1 | | Herrera | 3 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Ford" | | 4 | "Tomás" | | 5 | "Herrera" |
| | places | | | globalScore | 0.37 | | windowScore | 0.5 | |
| 43.62% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | glossingSentenceCount | 2 | | matches | | 0 | "seemed oblivious to her presence, their attention focused on the wares being offered" | | 1 | "something akin to sympathy in his gaze" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 961 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 52 | | matches | (empty) | |
| 49.20% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 35.59 | | std | 11.47 | | cv | 0.322 | | sampleLengths | | 0 | 46 | | 1 | 41 | | 2 | 12 | | 3 | 41 | | 4 | 31 | | 5 | 47 | | 6 | 33 | | 7 | 36 | | 8 | 45 | | 9 | 33 | | 10 | 54 | | 11 | 41 | | 12 | 34 | | 13 | 40 | | 14 | 38 | | 15 | 46 | | 16 | 14 | | 17 | 25 | | 18 | 29 | | 19 | 30 | | 20 | 11 | | 21 | 27 | | 22 | 46 | | 23 | 23 | | 24 | 37 | | 25 | 54 | | 26 | 47 |
| |
| 83.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 49 | | matches | | 0 | "was lined" | | 1 | "being offered" | | 2 | "being cocked" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 150 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 52 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 888 | | adjectiveStacks | 1 | | stackExamples | | 0 | "tall, olive-skinned individual" |
| | adverbCount | 29 | | adverbRatio | 0.03265765765765766 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.013513513513513514 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 52 | | echoCount | 0 | | echoWords | (empty) | |
| 81.58% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 52 | | mean | 18.48 | | std | 6.54 | | cv | 0.354 | | sampleLengths | | 0 | 18 | | 1 | 28 | | 2 | 20 | | 3 | 21 | | 4 | 12 | | 5 | 21 | | 6 | 20 | | 7 | 13 | | 8 | 18 | | 9 | 17 | | 10 | 16 | | 11 | 14 | | 12 | 4 | | 13 | 11 | | 14 | 18 | | 15 | 14 | | 16 | 22 | | 17 | 14 | | 18 | 16 | | 19 | 15 | | 20 | 16 | | 21 | 17 | | 22 | 28 | | 23 | 26 | | 24 | 24 | | 25 | 17 | | 26 | 20 | | 27 | 14 | | 28 | 18 | | 29 | 22 | | 30 | 17 | | 31 | 21 | | 32 | 17 | | 33 | 29 | | 34 | 14 | | 35 | 25 | | 36 | 9 | | 37 | 20 | | 38 | 30 | | 39 | 11 | | 40 | 4 | | 41 | 23 | | 42 | 12 | | 43 | 34 | | 44 | 14 | | 45 | 9 | | 46 | 14 | | 47 | 23 | | 48 | 21 | | 49 | 33 |
| |
| 70.51% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.4230769230769231 | | totalSentences | 52 | | uniqueOpeners | 22 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 49 | | matches | | 0 | "Suddenly, the suspect's car made" | | 1 | "Suddenly, a flash of movement" | | 2 | "Finally, the suspect ducked through" |
| | ratio | 0.061 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 7 | | totalSentences | 49 | | matches | | 0 | "She had been tracking this" | | 1 | "She grabbed her gun and" | | 2 | "It was a small, cramped" | | 3 | "he said, his voice calm" | | 4 | "he said, his voice dripping" | | 5 | "She couldn't afford to lose" | | 6 | "He was a criminal, no" |
| | ratio | 0.143 | |
| 82.45% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 37 | | totalSentences | 49 | | matches | | 0 | "The rain lashed against the" | | 1 | "She had been tracking this" | | 2 | "The suspect's car was just" | | 3 | "Harlow growled, her eyes narrowed" | | 4 | "The chase led them into" | | 5 | "Harlow could see the suspect" | | 6 | "Harlow cursed under her breath" | | 7 | "The alley opened up into" | | 8 | "Harlow slammed on the brakes," | | 9 | "She grabbed her gun and" | | 10 | "The suspect had vanished." | | 11 | "Harlow cursed again, her heart" | | 12 | "The square was lined with" | | 13 | "A flash of movement caught" | | 14 | "The suspect was nowhere to" | | 15 | "Harlow hesitated for a moment," | | 16 | "The stairwell was narrow and" | | 17 | "Harlow's senses were on high" | | 18 | "Harlow's grip on her gun" | | 19 | "The people around her seemed" |
| | ratio | 0.755 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 49 | | matches | (empty) | | ratio | 0 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 3 | | matches | | 0 | "Harlow could feel the hairs on the back of her neck standing on end, the sense of unease growing with every step." | | 1 | "Harlow's eyes narrowed as she took in the man's appearance, recognizing him as Tomás Herrera, a former paramedic who had lost his license after administering un…" | | 2 | "With a deep breath, she lowered her gun and stepped forward, following the suspect deeper into the Veil Market, her heart pounding with a mixture of fear and de…" |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 3 | | matches | | 0 | "he said, his voice calm and measured" | | 1 | "Harlow asked, her gaze sweeping the room" | | 2 | "he said, his voice dripping with sarcasm" |
| |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "Harlow growled (growl)" | | 1 | "Harlow demanded (demand)" |
| | dialogueSentences | 8 | | tagDensity | 0.625 | | leniency | 1 | | rawRatio | 0.4 | | effectiveRatio | 0.4 | |