| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 60.72% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1273 | | totalAiIsmAdverbs | 10 | | found | | | highlights | | 0 | "completely" | | 1 | "sharply" | | 2 | "gently" | | 3 | "very" | | 4 | "slowly" | | 5 | "tightly" | | 6 | "perfectly" |
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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 | 1273 | | totalAiIsms | 29 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "gloom" | | 1 | "scanned" | | 2 | "perfect" | | 3 | "silence" | | 4 | "profound" | | 5 | "sense of" | | 6 | "stomach" | | 7 | "input" | | 8 | "pulsed" | | 9 | "rhythmic" | | 10 | "warmth" | | 11 | "predator" | | 12 | "measured" | | 13 | "lilt" | | 14 | "flawless" | | 15 | "raced" | | 16 | "jaw clenched" | | 17 | "chaotic" | | 18 | "beacon" | | 19 | "tracing" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 104 | | matches | (empty) | |
| 74.18% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 5 | | narrationSentences | 104 | | filterMatches | (empty) | | hedgeMatches | | 0 | "seemed to" | | 1 | "managed to" | | 2 | "began to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 104 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1273 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 1273 | | uniqueNames | 14 | | maxNameDensity | 0.63 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Thames | 1 | | Richmond | 1 | | Park | 1 | | Carter | 1 | | Fae | 1 | | Grove | 1 | | London | 2 | | December | 1 | | Cardiff | 1 | | Heartstone | 1 | | Hel | 1 | | Evan | 3 | | English | 1 | | Rory | 8 |
| | persons | | | places | | 0 | "Thames" | | 1 | "Richmond" | | 2 | "Park" | | 3 | "Fae" | | 4 | "Grove" | | 5 | "London" | | 6 | "Cardiff" | | 7 | "Hel" |
| | globalScore | 1 | | windowScore | 1 | |
| 59.64% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | glossingSentenceCount | 3 | | matches | | 0 | "felt like the held breath of a predator" | | 1 | "rustling that seemed to come from the edge of her peripheral vision" | | 2 | "felt like a hot coal pressed against he" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1273 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 104 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 50.92 | | std | 33.46 | | cv | 0.657 | | sampleLengths | | 0 | 114 | | 1 | 79 | | 2 | 63 | | 3 | 114 | | 4 | 80 | | 5 | 7 | | 6 | 63 | | 7 | 14 | | 8 | 110 | | 9 | 41 | | 10 | 5 | | 11 | 60 | | 12 | 40 | | 13 | 3 | | 14 | 19 | | 15 | 3 | | 16 | 69 | | 17 | 36 | | 18 | 63 | | 19 | 51 | | 20 | 44 | | 21 | 51 | | 22 | 45 | | 23 | 14 | | 24 | 85 |
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| 95.14% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 104 | | matches | | 0 | "being pulled" | | 1 | "was gone" | | 2 | "was trapped" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 9 | | totalVerbs | 200 | | matches | | 0 | "was reacting" | | 1 | "was coming" | | 2 | "was not speaking" | | 3 | "was producing" | | 4 | "was playing" | | 5 | "was mimicking" | | 6 | "was trying" | | 7 | "was opening" | | 8 | "was stepping" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 104 | | ratio | 0 | | matches | (empty) | |
| 84.66% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1278 | | adjectiveStacks | 2 | | stackExamples | | 0 | "muddy, frost-hardened ground" | | 1 | "small crescent-shaped scar" |
| | adverbCount | 56 | | adverbRatio | 0.04381846635367762 | | lyAdverbCount | 20 | | lyAdverbRatio | 0.01564945226917058 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 104 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 104 | | mean | 12.24 | | std | 6.99 | | cv | 0.571 | | sampleLengths | | 0 | 26 | | 1 | 16 | | 2 | 30 | | 3 | 19 | | 4 | 9 | | 5 | 14 | | 6 | 10 | | 7 | 20 | | 8 | 12 | | 9 | 3 | | 10 | 27 | | 11 | 4 | | 12 | 3 | | 13 | 7 | | 14 | 6 | | 15 | 31 | | 16 | 9 | | 17 | 10 | | 18 | 6 | | 19 | 18 | | 20 | 7 | | 21 | 19 | | 22 | 16 | | 23 | 28 | | 24 | 13 | | 25 | 7 | | 26 | 20 | | 27 | 14 | | 28 | 14 | | 29 | 4 | | 30 | 28 | | 31 | 7 | | 32 | 9 | | 33 | 14 | | 34 | 16 | | 35 | 24 | | 36 | 5 | | 37 | 9 | | 38 | 3 | | 39 | 9 | | 40 | 3 | | 41 | 9 | | 42 | 21 | | 43 | 19 | | 44 | 6 | | 45 | 12 | | 46 | 14 | | 47 | 14 | | 48 | 17 | | 49 | 5 |
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| 32.69% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.22115384615384615 | | totalSentences | 104 | | uniqueOpeners | 23 | |
| 32.36% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 103 | | matches | | 0 | "Then, a voice drifted through" |
| | ratio | 0.01 | |
| 56.89% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 42 | | totalSentences | 103 | | matches | | 0 | "She paused to catch her" | | 1 | "She slipped the phone into" | | 2 | "She had come to the" | | 3 | "Her bright blue eyes scanned" | | 4 | "They were not made of" | | 5 | "She looked down at her" | | 6 | "They bent away, recoiling from" | | 7 | "Her mind, usually a fortress" | | 8 | "She told herself it was" | | 9 | "She had fled Cardiff to" | | 10 | "She reached up, her fingers" | | 11 | "It pulsed with a faint," | | 12 | "It was reacting to something." | | 13 | "It was expectant." | | 14 | "It felt like the held" | | 15 | "She turned slowly, intending to" | | 16 | "They were further away now," | | 17 | "She had no way of" | | 18 | "Her internal clock felt scrambled," | | 19 | "She forced her feet to" |
| | ratio | 0.408 | |
| 8.54% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 103 | | matches | | 0 | "The fog rolling off the" | | 1 | "Aurora Carter pushed through a" | | 2 | "She paused to catch her" | | 3 | "The digital display on her" | | 4 | "She slipped the phone into" | | 5 | "She had come to the" | | 6 | "Her bright blue eyes scanned" | | 7 | "The standing stones." | | 8 | "They were not made of" | | 9 | "This was the boundary." | | 10 | "The Fae Grove." | | 11 | "Rory stepped between the two" | | 12 | "The transition was immediate and" | | 13 | "The ambient hum of distant" | | 14 | "The air pressure dropped so" | | 15 | "A heavy, suffocating silence rushed" | | 16 | "She looked down at her" | | 17 | "The muddy, frost-hardened ground of" | | 18 | "Wildflowers bloomed in the dead" | | 19 | "The sight should have been" |
| | ratio | 0.903 | |
| 48.54% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 103 | | matches | | 0 | "If it was mimicking Evan," |
| | ratio | 0.01 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 2 | | matches | | 0 | "They were further away now, their jagged outlines blurred by a sudden, creeping mist that rolled over the wildflowers." | | 1 | "The clicking sounds grew faster, more frantic, overlapping in a chaotic chorus that made her ears ring." |
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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 | |