| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 983 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 84.74% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 983 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "etched" | | 1 | "magnetic" | | 2 | "disrupted" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 135 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 135 | | filterMatches | (empty) | | hedgeMatches | | 0 | "try to" | | 1 | "began to" | | 2 | "started to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 135 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 19 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 983 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 983 | | uniqueNames | 9 | | maxNameDensity | 0.92 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 9 | | Tube | 1 | | Camden | 2 | | Reeves | 7 | | Eva | 2 | | Kowalski | 2 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Reeves" | | 3 | "Eva" | | 4 | "Kowalski" | | 5 | "Market" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 90 | | 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 | 983 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 135 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 28.91 | | std | 16.64 | | cv | 0.576 | | sampleLengths | | 0 | 54 | | 1 | 59 | | 2 | 22 | | 3 | 1 | | 4 | 25 | | 5 | 33 | | 6 | 22 | | 7 | 7 | | 8 | 29 | | 9 | 54 | | 10 | 18 | | 11 | 44 | | 12 | 23 | | 13 | 7 | | 14 | 26 | | 15 | 59 | | 16 | 22 | | 17 | 5 | | 18 | 30 | | 19 | 48 | | 20 | 16 | | 21 | 28 | | 22 | 12 | | 23 | 35 | | 24 | 23 | | 25 | 49 | | 26 | 30 | | 27 | 7 | | 28 | 23 | | 29 | 49 | | 30 | 21 | | 31 | 24 | | 32 | 17 | | 33 | 61 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 135 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 163 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 135 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 983 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.019328585961342827 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.001017293997965412 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 135 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 135 | | mean | 7.28 | | std | 3.58 | | cv | 0.492 | | sampleLengths | | 0 | 19 | | 1 | 15 | | 2 | 7 | | 3 | 13 | | 4 | 4 | | 5 | 7 | | 6 | 8 | | 7 | 13 | | 8 | 5 | | 9 | 8 | | 10 | 10 | | 11 | 4 | | 12 | 4 | | 13 | 9 | | 14 | 9 | | 15 | 1 | | 16 | 6 | | 17 | 6 | | 18 | 2 | | 19 | 11 | | 20 | 8 | | 21 | 4 | | 22 | 14 | | 23 | 4 | | 24 | 3 | | 25 | 4 | | 26 | 6 | | 27 | 6 | | 28 | 6 | | 29 | 7 | | 30 | 6 | | 31 | 3 | | 32 | 6 | | 33 | 9 | | 34 | 5 | | 35 | 10 | | 36 | 6 | | 37 | 9 | | 38 | 10 | | 39 | 8 | | 40 | 11 | | 41 | 4 | | 42 | 6 | | 43 | 2 | | 44 | 2 | | 45 | 4 | | 46 | 6 | | 47 | 7 | | 48 | 6 | | 49 | 4 |
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| 40.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 19 | | diversityRatio | 0.32592592592592595 | | totalSentences | 135 | | uniqueOpeners | 44 | |
| 52.91% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 126 | | matches | | 0 | "Too little for a fatal" | | 1 | "Maybe he had interests in" |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 126 | | matches | | 0 | "She parked her car alongside" | | 1 | "She flashed her badge at" | | 2 | "Her boots hit each step" | | 3 | "Her brown eyes adjusted to" | | 4 | "She reached the platform." | | 5 | "He picked the wrong day." | | 6 | "She stopped at a particular" | | 7 | "She lifted it and looked" | | 8 | "Their spines showed titles on" | | 9 | "I have seen her name" | | 10 | "It doesn't link to your" | | 11 | "Its casing had a patina" | | 12 | "She picked it up." | | 13 | "It focuses on a specific" | | 14 | "You connect it to the" | | 15 | "She pulled it aside." | | 16 | "She retrieved the token." | | 17 | "It moves locations every full" | | 18 | "His face showed lines of" | | 19 | "She pieced the clues together" |
| | ratio | 0.206 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 118 | | totalSentences | 126 | | matches | | 0 | "Detective Harlow Quinn arrived at" | | 1 | "She parked her car alongside" | | 2 | "The barricades blocked the stairs" | | 3 | "She flashed her badge at" | | 4 | "The tunnel swallowed her." | | 5 | "Her boots hit each step" | | 6 | "The air tasted of rust" | | 7 | "Her brown eyes adjusted to" | | 8 | "The beam revealed the decay." | | 9 | "Posters from decades past peeled" | | 10 | "Graffiti overlaid some of them" | | 11 | "Sigils carved with precision." | | 12 | "She reached the platform." | | 13 | "The body lay in the" | | 14 | "DS Reeves stood nearby, notebook" | | 15 | "The scene looks like a" | | 16 | "The victim has a head" | | 17 | "The unusual location threw us" | | 18 | "Quinn approached the body and" | | 19 | "The wound appeared precise." |
| | ratio | 0.937 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 126 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 1 | | matches | | 0 | "The same elements that had taken her partner three years ago in unexplained circumstances." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |