| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.78% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1216 | | totalAiIsmAdverbs | 2 | | 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) | |
| 75.33% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1216 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "echo" | | 1 | "could feel" | | 2 | "warmth" | | 3 | "pulse" | | 4 | "stomach" | | 5 | "perfect" |
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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 | 66 | | matches | (empty) | |
| 34.63% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 3 | | narrationSentences | 66 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "seem to" | | 2 | "happened to" |
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| 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 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 68 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1206 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 17 | | wordCount | 1176 | | uniqueNames | 9 | | maxNameDensity | 0.34 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Warm" | | discoveredNames | | Richmond | 2 | | Park | 2 | | Heartstone | 1 | | Warm | 2 | | March | 1 | | Isolde | 3 | | Evan | 1 | | Cardiff | 1 | | Rory | 4 |
| | persons | | 0 | "Heartstone" | | 1 | "Isolde" | | 2 | "Evan" | | 3 | "Rory" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "March" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 3 | | matches | | 0 | "through here, apparently" | | 1 | "quite her own" | | 2 | "dark that seemed to have thickened behind her without her noticing, the way a room grows dim while you're absorbed in a book and you only notice the dark once you look up" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.829 | | wordCount | 1206 | | matches | | 0 | "not colder but different, thicker, like walking from a museum hallway into" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 66 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 44.67 | | std | 30.36 | | cv | 0.68 | | sampleLengths | | 0 | 11 | | 1 | 92 | | 2 | 85 | | 3 | 7 | | 4 | 69 | | 5 | 60 | | 6 | 10 | | 7 | 8 | | 8 | 98 | | 9 | 26 | | 10 | 34 | | 11 | 75 | | 12 | 3 | | 13 | 66 | | 14 | 11 | | 15 | 65 | | 16 | 45 | | 17 | 59 | | 18 | 9 | | 19 | 87 | | 20 | 62 | | 21 | 49 | | 22 | 4 | | 23 | 49 | | 24 | 7 | | 25 | 65 | | 26 | 50 |
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| 78.68% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 66 | | matches | | 0 | "was meant" | | 1 | "were painted" | | 2 | "were gone" | | 3 | "absorbed" | | 4 | "was prepared" | | 5 | "being paced" |
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| 62.54% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 194 | | matches | | 0 | "was being" | | 1 | "was reconsidering" | | 2 | "was waiting" | | 3 | "were moving" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 66 | | ratio | 0.091 | | matches | | 0 | "The park sounds—the distant traffic hush, the wind combing through the crowns of ordinary trees—fell away behind her all at once, as though someone had shut a door." | | 1 | "She was here for information, a name, a location—something Isolde's contact was meant to leave for her at the center of the grove, tucked beneath a particular stone, and all she had to do was walk to the middle, find it, and walk back out." | | 2 | "She counted her steps because counting steps was something to do with the part of her mind that wanted to spiral, and she'd learned a long time ago—thank you, Evan, thank you for that particular lesson—how to keep that part of her mind on a short leash." | | 3 | "She made herself keep moving toward the center of the grove, because turning back into a dark she couldn't account for seemed like the worse of two bad options, and because Isolde's contact was waiting, and because the alternative—admitting how frightened she'd become in the space of ninety seconds—was not something she was prepared to do, even alone, even with no one to perform composure for." | | 4 | "Not the rustle this time—a shape, upright, pale, gone the instant she turned her head toward it, the way a shadow will seem to have a shape until you look at it directly and it resolves into nothing at all." | | 5 | "She wanted to—every animal thing in her wanted to—but some colder, steadier part of her, the part that had gotten her out of a flat in Cardiff at two in the morning with nothing but a bag and a bus ticket, told her that running was for things that could be outrun, and she did not yet know what this was." |
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| 98.95% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 147 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 6 | | adverbRatio | 0.04081632653061224 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.02040816326530612 | |
| 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 | 18.27 | | std | 17.39 | | cv | 0.951 | | sampleLengths | | 0 | 11 | | 1 | 30 | | 2 | 62 | | 3 | 16 | | 4 | 11 | | 5 | 46 | | 6 | 7 | | 7 | 5 | | 8 | 7 | | 9 | 41 | | 10 | 28 | | 11 | 19 | | 12 | 33 | | 13 | 4 | | 14 | 4 | | 15 | 10 | | 16 | 3 | | 17 | 5 | | 18 | 3 | | 19 | 47 | | 20 | 12 | | 21 | 36 | | 22 | 7 | | 23 | 3 | | 24 | 4 | | 25 | 12 | | 26 | 34 | | 27 | 2 | | 28 | 5 | | 29 | 45 | | 30 | 3 | | 31 | 20 | | 32 | 3 | | 33 | 19 | | 34 | 47 | | 35 | 11 | | 36 | 3 | | 37 | 21 | | 38 | 13 | | 39 | 7 | | 40 | 21 | | 41 | 3 | | 42 | 2 | | 43 | 40 | | 44 | 5 | | 45 | 12 | | 46 | 42 | | 47 | 4 | | 48 | 5 | | 49 | 21 |
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| 53.54% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.3939393939393939 | | totalSentences | 66 | | uniqueOpeners | 26 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 64 | | matches | (empty) | | ratio | 0 | |
| 63.75% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 64 | | matches | | 0 | "She hadn't taken it off" | | 1 | "She still didn't know who'd" | | 2 | "She crossed between two of" | | 3 | "She'd expected off." | | 4 | "She was reconsidering that now," | | 5 | "She checked her phone out" | | 6 | "She had no way of" | | 7 | "Her voice came out smaller" | | 8 | "She hadn't expected anything to." | | 9 | "She was here for information," | | 10 | "She could feel the pendant's" | | 11 | "She started walking." | | 12 | "She counted her steps because" | | 13 | "It was small." | | 14 | "She stopped and looked and" | | 15 | "She told herself it was" | | 16 | "She kept walking." | | 17 | "She had not walked far" | | 18 | "She looked up now." | | 19 | "Her heart picked up its" |
| | ratio | 0.391 | |
| 92.81% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 64 | | matches | | 0 | "The standing stones came up" | | 1 | "Rory had walked Richmond Park" | | 2 | "The Heartstone sat heavy against" | | 3 | "She hadn't taken it off" | | 4 | "She still didn't know who'd" | | 5 | "She crossed between two of" | | 6 | "The park sounds—the distant traffic" | | 7 | "Wildflowers stood chest-high in every" | | 8 | "Rory stopped just inside the" | | 9 | "Everything about this is off." | | 10 | "She'd expected off." | | 11 | "Isolde had told her, in" | | 12 | "Rory had nodded along and" | | 13 | "She was reconsidering that now," | | 14 | "She checked her phone out" | | 15 | "The clock read 11:47." | | 16 | "She had no way of" | | 17 | "Her voice came out smaller" | | 18 | "She hadn't expected anything to." | | 19 | "She was here for information," |
| | ratio | 0.734 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 64 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 10 | | matches | | 0 | "She crossed between two of the oak stones and the temperature of the air changed, not colder but different, thicker, like walking from a museum hallway into an …" | | 1 | "The park sounds—the distant traffic hush, the wind combing through the crowns of ordinary trees—fell away behind her all at once, as though someone had shut a d…" | | 2 | "Wildflowers stood chest-high in every direction, white and violet and a blue so deep it looked bruised, all of them blooming in defiance of the cold that should…" | | 3 | "She was reconsidering that now, standing in a clearing full of flowers that shouldn't exist, under a sky that had no moon in it at all, only stars scattered too…" | | 4 | "She could feel the pendant's warmth pulsing steady and slow against her skin, a heartbeat that wasn't quite her own." | | 5 | "She counted her steps because counting steps was something to do with the part of her mind that wanted to spiral, and she'd learned a long time ago—thank you, E…" | | 6 | "And yet the stones were gone, swallowed into a dark that seemed to have thickened behind her without her noticing, the way a room grows dim while you're absorbe…" | | 7 | "Here and there, in patches, they bent, as if something low and unseen were moving through them on a path that intersected her own, always a few feet off, always…" | | 8 | "Something with a purpose, moving alongside her, matching her stride, waiting to see what she would do." | | 9 | "So she walked, faster now, toward a center she could not see, past flowers that bent toward a shape she refused to name, while the stars wheeled overhead in a s…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "Her voice came out, and the clearing swallowed it without an echo, which was somehow worse than if it had thrown her own voice back at her" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |