| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 86.35% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1099 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1099 | | totalAiIsms | 27 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "loomed" | | 1 | "warmth" | | 2 | "pulse" | | 3 | "sanctuary" | | 4 | "scanned" | | 5 | "oppressive" | | 6 | "silence" | | 7 | "weight" | | 8 | "echo" | | 9 | "methodical" | | 10 | "flicker" | | 11 | "measured" | | 12 | "could feel" | | 13 | "comforting" | | 14 | "familiar" | | 15 | "whisper" | | 16 | "electric" | | 17 | "predator" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 122 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 122 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 122 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 12 | | totalWords | 1087 | | ratio | 0.011 | | matches | | 0 | "Richmond Grove. Midnight. When the moon is full. Come alone." | | 1 | "snap" | | 2 | "Laila." |
| |
| 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 | 16 | | wordCount | 1086 | | uniqueNames | 9 | | maxNameDensity | 0.46 | | worstName | "Grove" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Grove" | | discoveredNames | | Richmond | 2 | | Park | 1 | | London | 3 | | Carter | 1 | | English | 1 | | Grove | 5 | | Heartstone | 1 | | Pendant | 1 | | Evan | 1 |
| | persons | | | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "London" | | 3 | "English" | | 4 | "Grove" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 76 | | 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 | 1087 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 122 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 22 | | mean | 49.41 | | std | 32.08 | | cv | 0.649 | | sampleLengths | | 0 | 72 | | 1 | 7 | | 2 | 68 | | 3 | 100 | | 4 | 74 | | 5 | 2 | | 6 | 89 | | 7 | 35 | | 8 | 59 | | 9 | 28 | | 10 | 75 | | 11 | 19 | | 12 | 75 | | 13 | 4 | | 14 | 70 | | 15 | 67 | | 16 | 60 | | 17 | 6 | | 18 | 29 | | 19 | 1 | | 20 | 48 | | 21 | 99 |
| |
| 93.76% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 122 | | matches | | 0 | "were leached" | | 1 | "was swallowed" | | 2 | "was shaped" | | 3 | "was stripped" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 172 | | matches | | 0 | "was letting" | | 1 | "was being" |
| |
| 96.02% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 122 | | ratio | 0.016 | | matches | | 0 | "It thinned, grew colder, and carried a new scent underneath the mulch and rot—the cloying perfume of night-blooming jasmine that had no business flowering in an English autumn." | | 1 | "The hum intensified, the rotten-sweet smell choked her, and the watching eyes—she felt them from all sides now, a ring of unseen predators closing in around her in the silent, silvered clearing." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1098 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 34 | | adverbRatio | 0.030965391621129327 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006375227686703097 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 122 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 122 | | mean | 8.91 | | std | 6.72 | | cv | 0.754 | | sampleLengths | | 0 | 19 | | 1 | 14 | | 2 | 11 | | 3 | 28 | | 4 | 7 | | 5 | 7 | | 6 | 2 | | 7 | 9 | | 8 | 7 | | 9 | 19 | | 10 | 17 | | 11 | 7 | | 12 | 17 | | 13 | 11 | | 14 | 9 | | 15 | 2 | | 16 | 2 | | 17 | 10 | | 18 | 1 | | 19 | 5 | | 20 | 28 | | 21 | 15 | | 22 | 10 | | 23 | 26 | | 24 | 15 | | 25 | 11 | | 26 | 3 | | 27 | 9 | | 28 | 2 | | 29 | 14 | | 30 | 8 | | 31 | 11 | | 32 | 3 | | 33 | 3 | | 34 | 5 | | 35 | 12 | | 36 | 8 | | 37 | 2 | | 38 | 6 | | 39 | 17 | | 40 | 5 | | 41 | 5 | | 42 | 3 | | 43 | 12 | | 44 | 3 | | 45 | 1 | | 46 | 6 | | 47 | 11 | | 48 | 10 | | 49 | 11 |
| |
| 51.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.36065573770491804 | | totalSentences | 122 | | uniqueOpeners | 44 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 102 | | matches | | 0 | "Just the flowers, the stones," | | 1 | "Probably a fox." | | 2 | "Then she heard it again." | | 3 | "Nowhere to hide, but nothing" | | 4 | "Just the rough, time-worn bark" |
| | ratio | 0.049 | |
| 59.22% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 41 | | totalSentences | 102 | | matches | | 0 | "It thinned, grew colder, and" | | 1 | "She had passed between the" | | 2 | "It was simply gone, snipped" | | 3 | "Their colours were leached to" | | 4 | "She ran her thumb over" | | 5 | "It remained inert, its temperature" | | 6 | "She took a breath and" | | 7 | "Her eyes scanned the clearing," | | 8 | "It came from her left," | | 9 | "Her knuckles were white where" | | 10 | "She forced her shoulders to" | | 11 | "She was letting the place" | | 12 | "She took another step towards" | | 13 | "It was loud." | | 14 | "She spun around, her heart" | | 15 | "Her voice was a fragile" | | 16 | "It came out thin, hoarse." | | 17 | "It felt watchful." | | 18 | "She took a slow, deliberate" | | 19 | "It was a trade-off." |
| | ratio | 0.402 | |
| 77.65% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 102 | | matches | | 0 | "The ancient oaks of Richmond" | | 1 | "Aurora Carter pushed aside a" | | 2 | "The air, thick with the" | | 3 | "It thinned, grew colder, and" | | 4 | "She had passed between the" | | 5 | "The distant hum of the" | | 6 | "It was simply gone, snipped" | | 7 | "The world behind her ceased" | | 8 | "Here, in the Grove, the" | | 9 | "Their colours were leached to" | | 10 | "A film of unnatural stillness" | | 11 | "Rory’s hand went to her" | | 12 | "She ran her thumb over" | | 13 | "It remained inert, its temperature" | | 14 | "The note in her pocket" | | 15 | "She took a breath and" | | 16 | "The great oaks that marked" | | 17 | "Shadows clung to their bases," | | 18 | "Her eyes scanned the clearing," | | 19 | "It came from her left," |
| | ratio | 0.765 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 102 | | matches | (empty) | | ratio | 0 | |
| 34.16% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 7 | | matches | | 0 | "It thinned, grew colder, and carried a new scent underneath the mulch and rot—the cloying perfume of night-blooming jasmine that had no business flowering in an…" | | 1 | "Their colours were leached to ghost-white and silver under a moon that seemed too large, too close." | | 2 | "Come alone.* She was here for answers, for the person who had sent her this pendant, this key to a world she was only just beginning to comprehend." | | 3 | "The great oaks that marked the Grove’s boundary formed a jagged circle, their gnarled branches reaching for each other like the arthritic fingers of old men." | | 4 | "It began as a prickle at the nape of her neck, the kind of awareness that signals another’s gaze." | | 5 | "She wrapped her arms around herself, rubbing her coat sleeves as if to wipe the sensation away." | | 6 | "It coiled around the ancient oaks and slid across the moon-washed flowers, a sibilant breath that brushed against her ear." |
| |
| 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 | |