| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 31 | | tagDensity | 0.452 | | leniency | 0.903 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.20% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1172 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | |
| 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) | |
| 48.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1172 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "chill" | | 1 | "weight" | | 2 | "echoing" | | 3 | "etched" | | 4 | "standard" | | 5 | "scanning" | | 6 | "perfect" | | 7 | "magnetic" | | 8 | "silence" | | 9 | "could feel" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "hung in the air" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 84 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 84 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 101 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1172 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 858 | | uniqueNames | 9 | | maxNameDensity | 2.21 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Town | 1 | | Detective | 1 | | Harlow | 1 | | Quinn | 19 | | Miller | 11 | | Morris | 2 | | Veil | 2 | | Market | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Miller" | | 3 | "Morris" | | 4 | "Market" |
| | places | | | globalScore | 0.393 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 1172 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 101 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 35.52 | | std | 23.04 | | cv | 0.649 | | sampleLengths | | 0 | 109 | | 1 | 45 | | 2 | 25 | | 3 | 65 | | 4 | 16 | | 5 | 43 | | 6 | 54 | | 7 | 4 | | 8 | 10 | | 9 | 61 | | 10 | 29 | | 11 | 28 | | 12 | 31 | | 13 | 54 | | 14 | 12 | | 15 | 28 | | 16 | 55 | | 17 | 6 | | 18 | 9 | | 19 | 7 | | 20 | 41 | | 21 | 51 | | 22 | 13 | | 23 | 56 | | 24 | 24 | | 25 | 48 | | 26 | 59 | | 27 | 16 | | 28 | 4 | | 29 | 38 | | 30 | 26 | | 31 | 58 | | 32 | 47 |
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| 88.55% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 84 | | matches | | 0 | "was blackened" | | 1 | "was told" | | 2 | "been scrubbed" | | 3 | "being watched" |
| |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 141 | | matches | | 0 | "was already bleeding" | | 1 | "was spinning" | | 2 | "was using" | | 3 | "wasn't sleeping" | | 4 | "was hunting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 101 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 862 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.024361948955916472 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.009280742459396751 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 101 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 101 | | mean | 11.6 | | std | 7.55 | | cv | 0.65 | | sampleLengths | | 0 | 25 | | 1 | 12 | | 2 | 16 | | 3 | 26 | | 4 | 10 | | 5 | 1 | | 6 | 19 | | 7 | 13 | | 8 | 13 | | 9 | 19 | | 10 | 16 | | 11 | 9 | | 12 | 12 | | 13 | 5 | | 14 | 5 | | 15 | 17 | | 16 | 15 | | 17 | 11 | | 18 | 3 | | 19 | 13 | | 20 | 5 | | 21 | 38 | | 22 | 4 | | 23 | 6 | | 24 | 17 | | 25 | 8 | | 26 | 19 | | 27 | 4 | | 28 | 10 | | 29 | 8 | | 30 | 8 | | 31 | 6 | | 32 | 22 | | 33 | 4 | | 34 | 13 | | 35 | 6 | | 36 | 23 | | 37 | 5 | | 38 | 23 | | 39 | 6 | | 40 | 8 | | 41 | 17 | | 42 | 9 | | 43 | 22 | | 44 | 23 | | 45 | 3 | | 46 | 9 | | 47 | 6 | | 48 | 10 | | 49 | 12 |
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| 52.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.37 | | totalSentences | 100 | | uniqueOpeners | 37 | |
| 45.05% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 74 | | matches | | 0 | "Just a single, clean puncture" |
| | ratio | 0.014 | |
| 52.43% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 74 | | matches | | 0 | "She adjusted the collar of" | | 1 | "Her closely cropped salt-and-pepper hair" | | 2 | "She checked the worn leather" | | 3 | "He looked young, too young" | | 4 | "He shifted his weight from" | | 5 | "She didn't look at Miller." | | 6 | "She looked at the floor." | | 7 | "Her voice was low, a" | | 8 | "He held up an evidence" | | 9 | "She squinted at the face" | | 10 | "She ignored the cold seeping" | | 11 | "She focused on the victim's" | | 12 | "It was a contradiction." | | 13 | "She tapped the brass compass" | | 14 | "Her brown eyes narrowed, scanning" | | 15 | "She walked toward the edge" | | 16 | "It was a transaction gone" | | 17 | "She walked back to the" | | 18 | "She reached out, her gloved" | | 19 | "She stood, the decision settling" |
| | ratio | 0.419 | |
| 14.05% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 74 | | matches | | 0 | "The damp air of the" | | 1 | "She adjusted the collar of" | | 2 | "Her closely cropped salt-and-pepper hair" | | 3 | "She checked the worn leather" | | 4 | "The shift was already bleeding" | | 5 | "DC Miller stood by the" | | 6 | "He looked young, too young" | | 7 | "He shifted his weight from" | | 8 | "Miller said, his voice echoing" | | 9 | "Quinn stepped past the tape," | | 10 | "She didn't look at Miller." | | 11 | "She looked at the floor." | | 12 | "The body lay supine near" | | 13 | "Her voice was low, a" | | 14 | "Miller replied, stepping closer" | | 15 | "He held up an evidence" | | 16 | "Quinn took the bag." | | 17 | "The casing had a heavy" | | 18 | "She squinted at the face" | | 19 | "Quinn crouched, the leather of" |
| | ratio | 0.892 | |
| 67.57% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 74 | | matches | | | ratio | 0.014 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 2 | | matches | | 0 | "Etched into the glass were protective sigils, geometric patterns that didn't belong to any standard navigation tool she knew." | | 1 | "A clean wound with no weapon, surrounded by thermal damage that shouldn't exist." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 4 | | matches | | 0 | "Miller said, his voice echoing too loudly in the hollow space" | | 1 | "Quinn said, not looking up" | | 2 | "Miller asked, skepticism coloring his tone" | | 3 | "she snapped, her military precision flaring into something sharper, more dangerous" |
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| 53.23% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 3 | | fancyTags | | 0 | "Quinn corrected (correct)" | | 1 | "Quinn ordered (order)" | | 2 | "she snapped (snap)" |
| | dialogueSentences | 31 | | tagDensity | 0.355 | | leniency | 0.71 | | rawRatio | 0.273 | | effectiveRatio | 0.194 | |