| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.313 | | leniency | 0.625 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 80.26% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 760 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "carefully" | | 1 | "very" | | 2 | "really" |
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| 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) | |
| 14.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 760 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "glinting" | | 1 | "jaw clenched" | | 2 | "furrowed" | | 3 | "etched" | | 4 | "eyebrow" | | 5 | "scanned" | | 6 | "determined" | | 7 | "silence" | | 8 | "palpable" | | 9 | "racing" |
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| 0.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 4 | | maxInWindow | 4 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "jaw/fists clenched" | | count | 2 |
| | 2 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "eyes narrowed" | | 1 | "jaw clenched" | | 2 | "The air was heavy with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 40 | | matches | (empty) | |
| 71.43% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 40 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 50 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 55 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 767 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 6.56% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 488 | | uniqueNames | 12 | | maxNameDensity | 2.87 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 14 | | Tube | 1 | | Camden | 1 | | Officer | 1 | | Gibbs | 2 | | Veil | 1 | | Market | 1 | | Dr | 6 | | Henry | 1 | | Lee | 6 | | London | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Officer" | | 3 | "Gibbs" | | 4 | "Dr" | | 5 | "Henry" | | 6 | "Lee" |
| | places | | | globalScore | 0.066 | | windowScore | 0.167 | |
| 66.67% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 30 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a crude, inverted crescent mo" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 767 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 50 | | matches | (empty) | |
| 77.41% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 19 | | mean | 40.37 | | std | 16.99 | | cv | 0.421 | | sampleLengths | | 0 | 66 | | 1 | 25 | | 2 | 37 | | 3 | 68 | | 4 | 40 | | 5 | 58 | | 6 | 24 | | 7 | 42 | | 8 | 36 | | 9 | 34 | | 10 | 29 | | 11 | 64 | | 12 | 20 | | 13 | 16 | | 14 | 26 | | 15 | 23 | | 16 | 64 | | 17 | 35 | | 18 | 60 |
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| 78.95% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 40 | | matches | | 0 | "been transformed" | | 1 | "was rumored" | | 2 | "was drawn" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 72 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 50 | | ratio | 0.06 | | matches | | 0 | "Quinn's gaze swept the platform, taking in the scattered, makeshift stalls – remnants of the Veil Market, which was rumored to operate out of this location last night." | | 1 | "Quinn's eyes adjusted to the brighter light of the crime scene lamps, illuminating the victim – a young woman, early twenties, with curly red hair and round glasses perched on her forehead." | | 2 | "That was when she noticed it – a tiny, almost imperceptible symbol etched into the wall near the victim's head, partially obscured by a discarded market stall banner." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 486 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.01646090534979424 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0102880658436214 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 50 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 50 | | mean | 15.34 | | std | 11.33 | | cv | 0.738 | | sampleLengths | | 0 | 27 | | 1 | 12 | | 2 | 13 | | 3 | 14 | | 4 | 25 | | 5 | 11 | | 6 | 26 | | 7 | 28 | | 8 | 3 | | 9 | 14 | | 10 | 23 | | 11 | 17 | | 12 | 11 | | 13 | 12 | | 14 | 32 | | 15 | 26 | | 16 | 16 | | 17 | 8 | | 18 | 1 | | 19 | 2 | | 20 | 39 | | 21 | 8 | | 22 | 14 | | 23 | 14 | | 24 | 1 | | 25 | 4 | | 26 | 29 | | 27 | 14 | | 28 | 15 | | 29 | 14 | | 30 | 14 | | 31 | 28 | | 32 | 8 | | 33 | 20 | | 34 | 1 | | 35 | 7 | | 36 | 8 | | 37 | 6 | | 38 | 20 | | 39 | 6 | | 40 | 1 | | 41 | 4 | | 42 | 12 | | 43 | 9 | | 44 | 55 | | 45 | 10 | | 46 | 2 | | 47 | 23 | | 48 | 19 | | 49 | 41 |
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| 76.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.46 | | totalSentences | 50 | | uniqueOpeners | 23 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 33 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 7 | | totalSentences | 33 | | matches | | 0 | "Her eyes narrowed." | | 1 | "She had been tracking its" | | 2 | "She carefully plucked out the" | | 3 | "He gestured to the scattered" | | 4 | "Her eyes scanned the walls," | | 5 | "It looked like a crude," | | 6 | "Her gaze swept the platform" |
| | ratio | 0.212 | |
| 20.61% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 29 | | totalSentences | 33 | | matches | | 0 | "Detective Harlow Quinn stepped down" | | 1 | "The air was heavy with" | | 2 | "Quinn's sharp jaw clenched as" | | 3 | "Quinn asked, her military precision" | | 4 | "Officer Gibbs nodded, his eyes" | | 5 | "Quinn's gaze swept the platform," | | 6 | "Her eyes narrowed." | | 7 | "The market's itinerant nature and" | | 8 | "She had been tracking its" | | 9 | "Henry Lee, the department's chief" | | 10 | "Quinn's eyes adjusted to the" | | 11 | "A worn leather satchel lay" | | 12 | "Quinn murmured, recognizing the victim" | | 13 | "Quinn's attention was drawn to" | | 14 | "She carefully plucked out the" | | 15 | "Lee raised an eyebrow." | | 16 | "He gestured to the scattered" | | 17 | "Quinn's gaze lingered on the" | | 18 | "Her eyes scanned the walls," | | 19 | "That was when she noticed" |
| | ratio | 0.879 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 33 | | matches | (empty) | | ratio | 0 | |
| 67.67% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 19 | | technicalSentenceCount | 2 | | matches | | 0 | "Detective Harlow Quinn stepped down from the rusty Tube station staircase, her worn leather watch glinting in the faint light that filtered through the grimy pl…" | | 1 | "Quinn's gaze swept the platform, taking in the scattered, makeshift stalls – remnants of the Veil Market, which was rumored to operate out of this location last…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 87.50% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "Quinn murmured (murmur)" |
| | dialogueSentences | 16 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0.333 | | effectiveRatio | 0.125 | |