| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 92.94% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2126 | | 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) | |
| 20.04% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2126 | | totalAiIsms | 34 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | |
| | highlights | | 0 | "chill" | | 1 | "warmth" | | 2 | "pulsed" | | 3 | "silence" | | 4 | "vibrated" | | 5 | "fractured" | | 6 | "echoed" | | 7 | "echo" | | 8 | "weight" | | 9 | "footsteps" | | 10 | "throbbed" | | 11 | "structure" | | 12 | "standard" | | 13 | "loomed" | | 14 | "calculate" | | 15 | "perfect" | | 16 | "pulse" | | 17 | "raced" | | 18 | "calculated" | | 19 | "disrupted" | | 20 | "footfall" |
| |
| 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 | 473 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 5 | | hedgeCount | 2 | | narrationSentences | 473 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 473 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 15 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2126 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 2126 | | uniqueNames | 19 | | maxNameDensity | 0.38 | | worstName | "You" | | maxWindowNameDensity | 3 | | worstWindowName | "You" | | discoveredNames | | December | 1 | | London | 2 | | Fae | 1 | | Grove | 1 | | Richmond | 2 | | Park | 2 | | Cardiff | 1 | | Evan | 1 | | Heartstone | 1 | | Hel | 2 | | Crown | 1 | | Court | 1 | | Aurora | 3 | | Carter | 1 | | Silas | 1 | | Yu-Fei | 1 | | Wildflowers | 3 | | You | 8 | | Like | 3 |
| | persons | | 0 | "December" | | 1 | "Grove" | | 2 | "Evan" | | 3 | "Heartstone" | | 4 | "Aurora" | | 5 | "Carter" | | 6 | "Silas" | | 7 | "Wildflowers" | | 8 | "You" | | 9 | "Like" |
| | places | | 0 | "London" | | 1 | "Fae" | | 2 | "Richmond" | | 3 | "Park" | | 4 | "Cardiff" | | 5 | "Crown" |
| | globalScore | 1 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 119 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like a knuckle striking dry wood" | | 1 | "sounded like a warning now" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 2126 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 473 | | matches | (empty) | |
| 90.78% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 60.74 | | std | 28.41 | | cv | 0.468 | | sampleLengths | | 0 | 59 | | 1 | 64 | | 2 | 32 | | 3 | 54 | | 4 | 56 | | 5 | 9 | | 6 | 27 | | 7 | 75 | | 8 | 69 | | 9 | 40 | | 10 | 59 | | 11 | 74 | | 12 | 59 | | 13 | 57 | | 14 | 58 | | 15 | 90 | | 16 | 51 | | 17 | 85 | | 18 | 55 | | 19 | 51 | | 20 | 4 | | 21 | 121 | | 22 | 39 | | 23 | 12 | | 24 | 73 | | 25 | 113 | | 26 | 86 | | 27 | 65 | | 28 | 64 | | 29 | 61 | | 30 | 20 | | 31 | 120 | | 32 | 46 | | 33 | 108 | | 34 | 70 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 473 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 428 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 473 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 2134 | | adjectiveStacks | 1 | | stackExamples | | 0 | "Absolute quiet pressed against her" |
| | adverbCount | 42 | | adverbRatio | 0.019681349578256794 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.004686035613870665 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 473 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 473 | | mean | 4.49 | | std | 2.26 | | cv | 0.503 | | sampleLengths | | 0 | 11 | | 1 | 4 | | 2 | 9 | | 3 | 6 | | 4 | 12 | | 5 | 8 | | 6 | 3 | | 7 | 6 | | 8 | 8 | | 9 | 7 | | 10 | 2 | | 11 | 9 | | 12 | 15 | | 13 | 10 | | 14 | 6 | | 15 | 7 | | 16 | 9 | | 17 | 7 | | 18 | 5 | | 19 | 5 | | 20 | 6 | | 21 | 4 | | 22 | 7 | | 23 | 5 | | 24 | 2 | | 25 | 2 | | 26 | 8 | | 27 | 8 | | 28 | 4 | | 29 | 5 | | 30 | 4 | | 31 | 5 | | 32 | 3 | | 33 | 15 | | 34 | 4 | | 35 | 7 | | 36 | 15 | | 37 | 4 | | 38 | 8 | | 39 | 2 | | 40 | 2 | | 41 | 5 | | 42 | 6 | | 43 | 8 | | 44 | 6 | | 45 | 5 | | 46 | 2 | | 47 | 3 | | 48 | 4 | | 49 | 15 |
| |
| 33.09% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 80 | | diversityRatio | 0.226215644820296 | | totalSentences | 473 | | uniqueOpeners | 107 | |
| 49.88% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 401 | | matches | | 0 | "Just the pale flowers and" | | 1 | "Bright blue eyes." | | 2 | "Just breath and syllables." | | 3 | "Just a dark indentation where" | | 4 | "Just damp earth and crushed" | | 5 | "Only the silence." |
| | ratio | 0.015 | |
| 47.43% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 173 | | totalSentences | 401 | | matches | | 0 | "It held a damp, green" | | 1 | "She knew these species belonged" | | 2 | "She tapped the silver chain" | | 3 | "She adjusted the strap, pulled" | | 4 | "She opened the voice memo" | | 5 | "Her thumb hovered over the" | | 6 | "I entered the Fae Grove" | | 7 | "I proceed toward the eastern" | | 8 | "She stopped the recording." | | 9 | "It vibrated through the soles" | | 10 | "She checked her watch." | | 11 | "She tapped the glass." | | 12 | "She walked forward." | | 13 | "Their branches formed a natural" | | 14 | "I hear a secondary acoustic" | | 15 | "She recorded again." | | 16 | "Her voice remained steady." | | 17 | "She kept moving." | | 18 | "It bit into the flesh" | | 19 | "She rubbed the crescent scar" |
| | ratio | 0.431 | |
| 11.12% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 360 | | totalSentences | 401 | | matches | | 0 | "The oak stones stood like" | | 1 | "Aurora stepped past them." | | 2 | "The air inside the clearing" | | 3 | "It held a damp, green" | | 4 | "Wildflowers pushed through the dark" | | 5 | "She knew these species belonged" | | 6 | "She tapped the silver chain" | | 7 | "The crimson stone rested against" | | 8 | "A slow rhythm matched her" | | 9 | "She adjusted the strap, pulled" | | 10 | "The screen cast a pale" | | 11 | "She opened the voice memo" | | 12 | "Her thumb hovered over the" | | 13 | "I entered the Fae Grove" | | 14 | "Boundary markers align with Richmond" | | 15 | "Flora shows zero seasonal dormancy." | | 16 | "I proceed toward the eastern" | | 17 | "She stopped the recording." | | 18 | "The silence that answered her" | | 19 | "Something pressed against her eardrums." |
| | ratio | 0.898 | |
| 12.47% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 401 | | matches | | 0 | "If the Hel threshold opens," |
| | ratio | 0.002 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 15 | | technicalSentenceCount | 1 | | matches | | 0 | "Moonlight fractured through the canopy, casting long shadows that stretched away from her light source." |
| |
| 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 | |