| 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 | 1151 | | 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) | |
| 52.22% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1151 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "measured" | | 1 | "tracing" | | 2 | "etched" | | 3 | "standard" | | 4 | "weight" | | 5 | "aligned" | | 6 | "traced" | | 7 | "footsteps" |
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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 | 100 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 100 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 112 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1151 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 53.74% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 935 | | uniqueNames | 5 | | maxNameDensity | 1.93 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 18 | | Camden | 1 | | Eva | 7 | | One | 4 |
| | persons | | | places | | | globalScore | 0.537 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 88 | | 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 | 1151 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 112 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 34.88 | | std | 23.29 | | cv | 0.668 | | sampleLengths | | 0 | 77 | | 1 | 70 | | 2 | 12 | | 3 | 18 | | 4 | 59 | | 5 | 24 | | 6 | 3 | | 7 | 13 | | 8 | 65 | | 9 | 18 | | 10 | 43 | | 11 | 59 | | 12 | 9 | | 13 | 15 | | 14 | 81 | | 15 | 48 | | 16 | 17 | | 17 | 10 | | 18 | 20 | | 19 | 72 | | 20 | 50 | | 21 | 22 | | 22 | 27 | | 23 | 21 | | 24 | 69 | | 25 | 38 | | 26 | 14 | | 27 | 27 | | 28 | 18 | | 29 | 58 | | 30 | 12 | | 31 | 16 | | 32 | 46 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 100 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 154 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 112 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 935 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 12 | | adverbRatio | 0.012834224598930482 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0021390374331550803 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 112 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 112 | | mean | 10.28 | | std | 4.17 | | cv | 0.406 | | sampleLengths | | 0 | 13 | | 1 | 8 | | 2 | 10 | | 3 | 17 | | 4 | 13 | | 5 | 7 | | 6 | 9 | | 7 | 12 | | 8 | 12 | | 9 | 11 | | 10 | 7 | | 11 | 12 | | 12 | 16 | | 13 | 12 | | 14 | 18 | | 15 | 5 | | 16 | 14 | | 17 | 13 | | 18 | 7 | | 19 | 9 | | 20 | 11 | | 21 | 24 | | 22 | 3 | | 23 | 13 | | 24 | 9 | | 25 | 16 | | 26 | 11 | | 27 | 8 | | 28 | 8 | | 29 | 13 | | 30 | 18 | | 31 | 5 | | 32 | 11 | | 33 | 7 | | 34 | 7 | | 35 | 13 | | 36 | 9 | | 37 | 8 | | 38 | 5 | | 39 | 4 | | 40 | 7 | | 41 | 13 | | 42 | 13 | | 43 | 9 | | 44 | 15 | | 45 | 8 | | 46 | 9 | | 47 | 11 | | 48 | 7 | | 49 | 8 |
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| 44.64% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.26785714285714285 | | totalSentences | 112 | | uniqueOpeners | 30 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 100 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 100 | | matches | | 0 | "Her boots met the platform" | | 1 | "Her satchel rested low on" | | 2 | "She measured the distance from" | | 3 | "She knelt and examined the" | | 4 | "She stopped at the pillar" | | 5 | "She lifted the bone and" | | 6 | "She pressed the bone deeper." | | 7 | "She returned to the compass" | | 8 | "She lifted the compass." | | 9 | "Its needle fixed on the" | | 10 | "She entered first and examined" | | 11 | "She replaced the fabric." | | 12 | "She knelt beside a larger" | | 13 | "She paused at one displaying" | | 14 | "She lifted one and compared" | | 15 | "She replaced the token and" | | 16 | "She closed the volume and" | | 17 | "Her leather watch caught the" | | 18 | "She pointed to a trail" | | 19 | "She counted four separate pitches" |
| | ratio | 0.26 | |
| 15.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 89 | | totalSentences | 100 | | matches | | 0 | "Detective Harlow Quinn descended the" | | 1 | "Her boots met the platform" | | 2 | "Water trickled from a joint" | | 3 | "Eva waited at the platform" | | 4 | "Her satchel rested low on" | | 5 | "Quinn covered the distance in" | | 6 | "The victim lay on her" | | 7 | "Quinn observed the neck wound" | | 8 | "Blood formed a narrow trail" | | 9 | "Eva shifted her stance and" | | 10 | "Quinn circled the body once." | | 11 | "She measured the distance from" | | 12 | "The drops sat separate without" | | 13 | "She knelt and examined the" | | 14 | "The palms faced upward without" | | 15 | "The clothing lay undisturbed with" | | 16 | "Eva leaned closer." | | 17 | "Quinn rose and tracked the" | | 18 | "She stopped at the pillar" | | 19 | "A carved bone piece occupied" |
| | ratio | 0.89 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 100 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 2 | | matches | | 0 | "Water trickled from a joint overhead and collected in shallow pools that reflected the sporadic bulb light." | | 1 | "Blood formed a narrow trail that split into isolated drops leading back to a support pillar." |
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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 | |