| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 76.08% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1045 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "tightly" | | 1 | "suddenly" | | 2 | "quickly" | | 3 | "warily" |
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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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1045 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "charged" | | 1 | "pounding" | | 2 | "footsteps" | | 3 | "navigated" | | 4 | "echoing" | | 5 | "scanned" | | 6 | "etched" | | 7 | "glinting" | | 8 | "otherworldly" | | 9 | "raced" | | 10 | "sense of" | | 11 | "pulse" | | 12 | "scanning" | | 13 | "shattered" | | 14 | "steeled" | | 15 | "resolve" |
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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 | 0 | | narrationSentences | 59 | | matches | (empty) | |
| 70.22% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 59 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 66 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1045 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 52 | | wordCount | 894 | | uniqueNames | 13 | | maxNameDensity | 2.24 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Herrera" | | discoveredNames | | Harlow | 2 | | Quinn | 20 | | London | 1 | | Tomás | 1 | | Herrera | 19 | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Veil | 1 | | Market | 1 | | Saint | 1 | | Christopher | 1 | | Detective | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Raven" | | 5 | "Saint" | | 6 | "Christopher" |
| | places | | 0 | "London" | | 1 | "Soho" | | 2 | "Veil" | | 3 | "Market" |
| | globalScore | 0.381 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | 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 | 1045 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 66 | | matches | (empty) | |
| 29.77% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 38.7 | | std | 9.84 | | cv | 0.254 | | sampleLengths | | 0 | 52 | | 1 | 46 | | 2 | 50 | | 3 | 46 | | 4 | 65 | | 5 | 45 | | 6 | 41 | | 7 | 47 | | 8 | 36 | | 9 | 39 | | 10 | 38 | | 11 | 39 | | 12 | 30 | | 13 | 30 | | 14 | 37 | | 15 | 37 | | 16 | 8 | | 17 | 35 | | 18 | 45 | | 19 | 41 | | 20 | 35 | | 21 | 31 | | 22 | 34 | | 23 | 30 | | 24 | 39 | | 25 | 31 | | 26 | 38 |
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| 93.37% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 59 | | matches | | 0 | "been spotted" | | 1 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 165 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 66 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 900 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.024444444444444446 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.014444444444444444 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 66 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 66 | | mean | 15.83 | | std | 6.79 | | cv | 0.429 | | sampleLengths | | 0 | 21 | | 1 | 31 | | 2 | 18 | | 3 | 28 | | 4 | 27 | | 5 | 23 | | 6 | 18 | | 7 | 15 | | 8 | 13 | | 9 | 9 | | 10 | 20 | | 11 | 25 | | 12 | 11 | | 13 | 14 | | 14 | 11 | | 15 | 20 | | 16 | 19 | | 17 | 22 | | 18 | 12 | | 19 | 24 | | 20 | 11 | | 21 | 18 | | 22 | 18 | | 23 | 17 | | 24 | 22 | | 25 | 19 | | 26 | 19 | | 27 | 17 | | 28 | 22 | | 29 | 13 | | 30 | 17 | | 31 | 16 | | 32 | 14 | | 33 | 24 | | 34 | 13 | | 35 | 18 | | 36 | 19 | | 37 | 3 | | 38 | 5 | | 39 | 22 | | 40 | 13 | | 41 | 10 | | 42 | 15 | | 43 | 11 | | 44 | 9 | | 45 | 8 | | 46 | 33 | | 47 | 8 | | 48 | 27 | | 49 | 20 |
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| 46.97% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.3181818181818182 | | totalSentences | 66 | | uniqueOpeners | 21 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 59 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 59 | | matches | | 0 | "She refused to let the" | | 1 | "She knew this was the" | | 2 | "She had a bone token" | | 3 | "She considered her options, knowing" | | 4 | "She could hear the distant" | | 5 | "She followed the winding path," | | 6 | "She spotted him across the" | | 7 | "She moved closer, weaving between" | | 8 | "He quickly pocketed the vial" | | 9 | "She emerged suddenly into a" | | 10 | "His olive skin seemed to" | | 11 | "She thought back to the" | | 12 | "She shook her head, chasing" | | 13 | "He took a small step" | | 14 | "He threw the vial to" | | 15 | "She knew she had stumbled" | | 16 | "She would uncover the truth," |
| | ratio | 0.288 | |
| 53.22% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 48 | | totalSentences | 59 | | matches | | 0 | "Detective Harlow Quinn charged through" | | 1 | "The man, a former paramedic" | | 2 | "Quinn had been investigating the" | | 3 | "The rain plastered her closely" | | 4 | "She refused to let the" | | 5 | "Herrera turned into an alley," | | 6 | "The alley was dark and" | | 7 | "Herrera abruptly stopped and shoved" | | 8 | "Quinn reached the door and" | | 9 | "She knew this was the" | | 10 | "She had a bone token" | | 11 | "She considered her options, knowing" | | 12 | "The air was cool and" | | 13 | "She could hear the distant" | | 14 | "She followed the winding path," | | 15 | "The tunnels grew wider and" | | 16 | "Quinn scanned the throngs of" | | 17 | "She spotted him across the" | | 18 | "She moved closer, weaving between" | | 19 | "He quickly pocketed the vial" |
| | ratio | 0.814 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 59 | | matches | (empty) | | ratio | 0 | |
| 93.02% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 3 | | matches | | 0 | "She knew this was the entrance to The Veil Market, a hidden supernatural black market that operated beneath the city." | | 1 | "She considered her options, knowing the dangers that awaited her below." | | 2 | "The path twisted and turned, branching into a warren of tunnels that made it impossible to track her movements." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 2 | | matches | | 0 | "Herrera said, his voice echoing off the damp stones" | | 1 | "Herrera warned, his grip tightening on the vial" |
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| 59.09% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 11 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0.5 | | effectiveRatio | 0.182 | |