| 57.14% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn finally asked [finally]" | | 1 | "Milo said sharply [sharply]" |
| | dialogueSentences | 28 | | tagDensity | 0.357 | | leniency | 0.714 | | rawRatio | 0.2 | | effectiveRatio | 0.143 | |
| 66.53% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1195 | | totalAiIsmAdverbs | 8 | | found | | | highlights | | 0 | "cautiously" | | 1 | "slowly" | | 2 | "lightly" | | 3 | "carefully" | | 4 | "nervously" | | 5 | "suddenly" | | 6 | "sharply" | | 7 | "softly" |
| |
| 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) | |
| 33.05% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1195 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "echo" | | 1 | "chill" | | 2 | "whisper" | | 3 | "etched" | | 4 | "scanned" | | 5 | "silence" | | 6 | "furrowed" | | 7 | "shimmered" | | 8 | "disrupted" | | 9 | "jaw clenched" | | 10 | "flickered" | | 11 | "electric" | | 12 | "spectral" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "jaw clenched" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 69 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 69 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 86 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1180 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 10.10% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 822 | | uniqueNames | 13 | | maxNameDensity | 2.8 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 23 | | Tube | 1 | | Camden | 1 | | Sergeant | 1 | | Milo | 8 | | Grant | 1 | | Veil | 2 | | Market | 1 | | Compass | 1 | | Morris | 1 | | Eva | 7 | | Kowalski | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Milo" | | 4 | "Grant" | | 5 | "Morris" | | 6 | "Eva" | | 7 | "Kowalski" |
| | places | | | globalScore | 0.101 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | 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 | 1180 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 86 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 31.89 | | std | 18.48 | | cv | 0.579 | | sampleLengths | | 0 | 79 | | 1 | 59 | | 2 | 51 | | 3 | 71 | | 4 | 10 | | 5 | 67 | | 6 | 12 | | 7 | 29 | | 8 | 58 | | 9 | 46 | | 10 | 17 | | 11 | 34 | | 12 | 26 | | 13 | 37 | | 14 | 26 | | 15 | 30 | | 16 | 35 | | 17 | 12 | | 18 | 14 | | 19 | 49 | | 20 | 10 | | 21 | 33 | | 22 | 29 | | 23 | 31 | | 24 | 19 | | 25 | 46 | | 26 | 22 | | 27 | 14 | | 28 | 29 | | 29 | 21 | | 30 | 6 | | 31 | 19 | | 32 | 21 | | 33 | 5 | | 34 | 27 | | 35 | 36 | | 36 | 50 |
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| 90.01% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 69 | | matches | | 0 | "been called" | | 1 | "were obscured" | | 2 | "was disrupted" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 144 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 86 | | ratio | 0.105 | | matches | | 0 | "It was no ordinary crime scene—something about it refused to settle in her bones." | | 1 | "Her sharp eyes scanned the scene—the victim, a young woman dressed in layers of uneven fabric and worn leather boots, lay face up beneath the arched concrete ceiling." | | 2 | "“No witnesses, no CCTV obviously. Time of death seems about midnight, but the body’s in a state of... decomposition that doesn’t quite fit. And we found this.” He pulled something from a small evidence bag—a bone token, bleached white and etched with delicate runes Quinn recognized from a case file months ago." | | 3 | "The dust was disrupted around a small brass cicada-shaped object—a Veil Compass." | | 4 | "Quinn’s mind flashed back to DS Morris—the partner she’d lost three years ago under circumstances just as inexplicable." | | 5 | "A petite figure emerged, red curls bouncing in the shadows—Eva Kowalski, clutching her worn leather satchel close." | | 6 | "A sudden motion caught Quinn’s eye—the compass needle suddenly spun wildly, then pointed directly at a seam in the tunnel wall." | | 7 | "The mortar was loose, but beneath it—a faint pulsating glow hummed softly." | | 8 | "It was the edge of something far more dangerous—and Quinn wasn’t going to let it go unsolved." |
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| 97.01% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 834 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.0407673860911271 | | lyAdverbCount | 19 | | lyAdverbRatio | 0.022781774580335732 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 86 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 86 | | mean | 13.72 | | std | 8.35 | | cv | 0.609 | | sampleLengths | | 0 | 22 | | 1 | 22 | | 2 | 18 | | 3 | 17 | | 4 | 14 | | 5 | 16 | | 6 | 29 | | 7 | 13 | | 8 | 13 | | 9 | 25 | | 10 | 4 | | 11 | 28 | | 12 | 15 | | 13 | 24 | | 14 | 10 | | 15 | 7 | | 16 | 52 | | 17 | 8 | | 18 | 3 | | 19 | 9 | | 20 | 3 | | 21 | 26 | | 22 | 28 | | 23 | 10 | | 24 | 20 | | 25 | 11 | | 26 | 12 | | 27 | 23 | | 28 | 10 | | 29 | 7 | | 30 | 13 | | 31 | 3 | | 32 | 6 | | 33 | 12 | | 34 | 6 | | 35 | 20 | | 36 | 18 | | 37 | 9 | | 38 | 10 | | 39 | 5 | | 40 | 21 | | 41 | 9 | | 42 | 21 | | 43 | 4 | | 44 | 13 | | 45 | 18 | | 46 | 4 | | 47 | 8 | | 48 | 14 | | 49 | 17 |
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| 57.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.36046511627906974 | | totalSentences | 86 | | uniqueOpeners | 31 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 67 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 67 | | matches | | 0 | "She adjusted the collar of" | | 1 | "It was no ordinary crime" | | 2 | "He looked up as Quinn" | | 3 | "he said with a hesitant" | | 4 | "Her sharp eyes scanned the" | | 5 | "Her features were obscured by" | | 6 | "He pulled something from a" | | 7 | "She walked slowly around the" | | 8 | "she murmured, crouching to examine" | | 9 | "She pried it free and" | | 10 | "Her eyes narrowed." | | 11 | "She fought down the resurgence" | | 12 | "She tapped the compass lightly" | | 13 | "She gave a cold nod," | | 14 | "She trusted Eva’s research instincts," | | 15 | "Her gaze faltered" | | 16 | "She slipped on a pair" | | 17 | "She glanced down once more" | | 18 | "It was the edge of" |
| | ratio | 0.284 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 62 | | totalSentences | 67 | | matches | | 0 | "Detective Harlow Quinn stepped down" | | 1 | "The faint echo of dripping" | | 2 | "She adjusted the collar of" | | 3 | "A metallic tang of blood" | | 4 | "It was no ordinary crime" | | 5 | "Quinn had been called here" | | 6 | "This decrepit station hadn’t seen" | | 7 | "Detective Sergeant Milo Grant was" | | 8 | "He looked up as Quinn" | | 9 | "he said with a hesitant" | | 10 | "Quinn didn’t reply immediately." | | 11 | "Her sharp eyes scanned the" | | 12 | "Her features were obscured by" | | 13 | "Quinn finally asked, her voice" | | 14 | "Milo gestured toward the silence" | | 15 | "He pulled something from a" | | 16 | "A marker of entrance into" | | 17 | "Quinn’s brow furrowed." | | 18 | "Milo nodded cautiously." | | 19 | "Quinn’s gaze drifted to the" |
| | ratio | 0.925 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 67 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 2 | | matches | | 0 | "This decrepit station hadn’t seen a passenger in decades, yet here they were: a body sprawled near the old turnstiles, police officers muttering theories that f…" | | 1 | "The air near the far wall shimmered ever so faintly, as if the cold mist bent unnaturally against the bricks." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn finally asked, her voice low, steady" | | 1 | "she murmured, crouching to examine the floor" |
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| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 4 | | fancyTags | | 0 | "she murmured (murmur)" | | 1 | "Milo whispered (whisper)" | | 2 | "Her gaze faltered (falter)" | | 3 | "she muttered (mutter)" |
| | dialogueSentences | 28 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0.5 | | effectiveRatio | 0.286 | |