| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 25 | | tagDensity | 0.16 | | leniency | 0.32 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.11% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 944 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "softly" | | 1 | "nervously" | | 2 | "very" |
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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) | |
| 9.96% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 944 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "stark" | | 1 | "echoing" | | 2 | "determined" | | 3 | "scanning" | | 4 | "silence" | | 5 | "intricate" | | 6 | "racing" | | 7 | "etched" | | 8 | "furrowed" | | 9 | "perfect" | | 10 | "grave" | | 11 | "potential" | | 12 | "resolve" | | 13 | "raced" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 54 | | matches | | |
| 63.49% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 54 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 74 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 944 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 610 | | uniqueNames | 10 | | maxNameDensity | 3.11 | | worstName | "Quinn" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 19 | | Tube | 1 | | Camden | 1 | | Dixon | 7 | | Morris | 1 | | Eva | 6 | | Kowalski | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Dixon" | | 3 | "Morris" | | 4 | "Eva" | | 5 | "Kowalski" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 93.18% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 944 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 74 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 29.5 | | std | 16.02 | | cv | 0.543 | | sampleLengths | | 0 | 65 | | 1 | 54 | | 2 | 39 | | 3 | 46 | | 4 | 11 | | 5 | 15 | | 6 | 61 | | 7 | 35 | | 8 | 10 | | 9 | 19 | | 10 | 16 | | 11 | 20 | | 12 | 14 | | 13 | 41 | | 14 | 10 | | 15 | 5 | | 16 | 28 | | 17 | 45 | | 18 | 20 | | 19 | 22 | | 20 | 18 | | 21 | 32 | | 22 | 7 | | 23 | 28 | | 24 | 53 | | 25 | 16 | | 26 | 33 | | 27 | 38 | | 28 | 36 | | 29 | 22 | | 30 | 44 | | 31 | 41 |
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| 98.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 54 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 96 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 74 | | ratio | 0.014 | | matches | | 0 | "The Veil Market, the compass, the sigils — all pieces of a larger, more dangerous puzzle." |
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| 98.91% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 610 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.03114754098360656 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.021311475409836064 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 74 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 74 | | mean | 12.76 | | std | 7.5 | | cv | 0.588 | | sampleLengths | | 0 | 24 | | 1 | 14 | | 2 | 17 | | 3 | 10 | | 4 | 19 | | 5 | 18 | | 6 | 17 | | 7 | 11 | | 8 | 28 | | 9 | 17 | | 10 | 11 | | 11 | 18 | | 12 | 11 | | 13 | 7 | | 14 | 8 | | 15 | 14 | | 16 | 14 | | 17 | 14 | | 18 | 19 | | 19 | 8 | | 20 | 12 | | 21 | 15 | | 22 | 10 | | 23 | 4 | | 24 | 15 | | 25 | 6 | | 26 | 6 | | 27 | 4 | | 28 | 20 | | 29 | 3 | | 30 | 11 | | 31 | 2 | | 32 | 25 | | 33 | 14 | | 34 | 3 | | 35 | 7 | | 36 | 3 | | 37 | 2 | | 38 | 9 | | 39 | 19 | | 40 | 21 | | 41 | 12 | | 42 | 12 | | 43 | 13 | | 44 | 7 | | 45 | 7 | | 46 | 10 | | 47 | 5 | | 48 | 5 | | 49 | 13 |
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| 54.95% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.33783783783783783 | | totalSentences | 74 | | uniqueOpeners | 25 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 53 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 53 | | matches | | 0 | "She stepped inside, her boots" | | 1 | "She noticed the faint scent" | | 2 | "She recognized the tone of" | | 3 | "His skin was ashen, and" | | 4 | "She noticed a small, intricate" | | 5 | "He handed her a small," | | 6 | "She wore round glasses and" | | 7 | "Her freckled complexion was a" | | 8 | "She tugged at her hair" | | 9 | "She pulled out a small" | | 10 | "She vowed to uncover the" |
| | ratio | 0.208 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 50 | | totalSentences | 53 | | matches | | 0 | "Detective Harlow Quinn stood at" | | 1 | "The air was cold and" | | 2 | "The faint glow of flickering" | | 3 | "She stepped inside, her boots" | | 4 | "Detective Quinn's sharp jawline was" | | 5 | "The place was eerily quiet," | | 6 | "She noticed the faint scent" | | 7 | "She recognized the tone of" | | 8 | "Quinn made her way through" | | 9 | "Dixon stood by a makeshift" | | 10 | "The barrier was a hastily" | | 11 | "Quinn asked, her voice steady" | | 12 | "Dixon swallowed hard, pointing to" | | 13 | "Quinn walked past the barrier," | | 14 | "A man lay sprawled on" | | 15 | "His skin was ashen, and" | | 16 | "Blood pooled around him, but" | | 17 | "Quinn crouched down, her eyes" | | 18 | "The man's eyes were wide" | | 19 | "She noticed a small, intricate" |
| | ratio | 0.943 | |
| 94.34% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 53 | | matches | | | ratio | 0.019 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 3 | | matches | | 0 | "She recognized the tone of her colleague, DS Dixon, a younger, more hesitant man who had joined the force after the loss of her former partner, DS Morris." | | 1 | "The barrier was a hastily erected chain-link fence, partially torn, as if something had forced its way through." | | 2 | "The air grew heavier with each step, as if the very walls were watching them, waiting for their next move." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 3 | | matches | | 0 | "Quinn asked, her voice steady and authoritative" | | 1 | "Quinn asked, her gaze still on the body" | | 2 | "Quinn said, her voice a mix of relief and urgency" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 25 | | tagDensity | 0.12 | | leniency | 0.24 | | rawRatio | 0 | | effectiveRatio | 0 | |