| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.30% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1352 | | totalAiIsmAdverbs | 1 | | 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) | |
| 26.04% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1352 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "chill" | | 1 | "warmth" | | 2 | "chaotic" | | 3 | "pulse" | | 4 | "rhythmic" | | 5 | "silence" | | 6 | "variable" | | 7 | "echo" | | 8 | "weight" | | 9 | "racing" | | 10 | "footfall" | | 11 | "echoes" | | 12 | "lilt" |
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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 | 139 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 139 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 143 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1342 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 89.76% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1328 | | uniqueNames | 19 | | maxNameDensity | 1.2 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Park | 1 | | Rory | 16 | | London | 1 | | Fae | 3 | | Grove | 2 | | Cardiff | 1 | | Heartstone | 3 | | Hel | 1 | | Yu-Fei | 1 | | Cheung | 1 | | Golden | 1 | | Empress | 1 | | Isolde | 1 | | Earth | 1 | | Dymas | 1 | | Evan | 1 | | Jennifer | 1 | | Carter | 1 | | Welsh | 1 |
| | persons | | 0 | "Rory" | | 1 | "Grove" | | 2 | "Heartstone" | | 3 | "Yu-Fei" | | 4 | "Cheung" | | 5 | "Empress" | | 6 | "Isolde" | | 7 | "Evan" | | 8 | "Jennifer" | | 9 | "Carter" |
| | places | | 0 | "Park" | | 1 | "London" | | 2 | "Fae" | | 3 | "Cardiff" | | 4 | "Hel" |
| | globalScore | 0.898 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 108 | | 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 | 1342 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 143 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 29.82 | | std | 22.48 | | cv | 0.754 | | sampleLengths | | 0 | 79 | | 1 | 60 | | 2 | 93 | | 3 | 68 | | 4 | 8 | | 5 | 25 | | 6 | 68 | | 7 | 30 | | 8 | 22 | | 9 | 3 | | 10 | 6 | | 11 | 5 | | 12 | 53 | | 13 | 30 | | 14 | 9 | | 15 | 38 | | 16 | 3 | | 17 | 41 | | 18 | 13 | | 19 | 28 | | 20 | 5 | | 21 | 47 | | 22 | 70 | | 23 | 39 | | 24 | 28 | | 25 | 27 | | 26 | 11 | | 27 | 9 | | 28 | 33 | | 29 | 42 | | 30 | 11 | | 31 | 54 | | 32 | 19 | | 33 | 17 | | 34 | 36 | | 35 | 4 | | 36 | 21 | | 37 | 1 | | 38 | 34 | | 39 | 35 | | 40 | 2 | | 41 | 12 | | 42 | 45 | | 43 | 22 | | 44 | 36 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 139 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 205 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 143 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1338 | | adjectiveStacks | 2 | | stackExamples | | 0 | "small crescent-shaped scar" | | 1 | "exposed, moss-slick root." |
| | adverbCount | 19 | | adverbRatio | 0.014200298953662182 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.007473841554559043 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 143 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 143 | | mean | 9.38 | | std | 5.11 | | cv | 0.544 | | sampleLengths | | 0 | 13 | | 1 | 5 | | 2 | 12 | | 3 | 15 | | 4 | 7 | | 5 | 12 | | 6 | 15 | | 7 | 10 | | 8 | 16 | | 9 | 12 | | 10 | 22 | | 11 | 13 | | 12 | 9 | | 13 | 12 | | 14 | 7 | | 15 | 12 | | 16 | 16 | | 17 | 9 | | 18 | 6 | | 19 | 6 | | 20 | 3 | | 21 | 6 | | 22 | 9 | | 23 | 6 | | 24 | 30 | | 25 | 11 | | 26 | 6 | | 27 | 8 | | 28 | 8 | | 29 | 5 | | 30 | 12 | | 31 | 6 | | 32 | 15 | | 33 | 6 | | 34 | 14 | | 35 | 10 | | 36 | 13 | | 37 | 4 | | 38 | 6 | | 39 | 9 | | 40 | 15 | | 41 | 7 | | 42 | 15 | | 43 | 3 | | 44 | 6 | | 45 | 1 | | 46 | 1 | | 47 | 3 | | 48 | 11 | | 49 | 8 |
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| 34.62% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 22 | | diversityRatio | 0.22377622377622378 | | totalSentences | 143 | | uniqueOpeners | 32 | |
| 24.88% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 134 | | matches | | 0 | "Instead, the shape bleeds onto" |
| | ratio | 0.007 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 134 | | matches | | 0 | "It serves as a physical" | | 1 | "She pulls the artifact free" | | 2 | "She parked her scooter, leaving" | | 3 | "She looks down at her" | | 4 | "She drops her arm." | | 5 | "Her black boots crush a" | | 6 | "She pauses mid-stride." | | 7 | "It rang out ten feet" | | 8 | "She strains her ears." | | 9 | "She commands her rigid muscles" | | 10 | "She forces a breath through" | | 11 | "She lowers her boot, pressing" | | 12 | "She sweeps the crimson beam" | | 13 | "She carries no weapon, clutching" | | 14 | "She snaps her head to" | | 15 | "She stares at the void," | | 16 | "It moves without the rigid" | | 17 | "It refuses to step out" | | 18 | "It consumes the ambient red" | | 19 | "It bounces against her chest," |
| | ratio | 0.216 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 125 | | totalSentences | 134 | | matches | | 0 | "Richmond Park vanishes the moment" | | 1 | "The transformation offers no bridge." | | 2 | "The heavy grind of night" | | 3 | "The crisp chill of a" | | 4 | "The air pressure spikes, popping" | | 5 | "Rory forces a swallow, blinking" | | 6 | "The Fae Grove refuses to" | | 7 | "A bruised, starless twilight filters" | | 8 | "Wildflowers carpet the forest floor" | | 9 | "The scent of them coats" | | 10 | "Rory rubs her thumb across" | | 11 | "The skin marks a childhood" | | 12 | "It serves as a physical" | | 13 | "The Heartstone lies heavy against" | | 14 | "She pulls the artifact free" | | 15 | "A deep crimson light bleeds" | | 16 | "The glow throbs against her" | | 17 | "A rhythmic warning." | | 18 | "The artifact serves as a" | | 19 | "The heat signifies close proximity" |
| | ratio | 0.933 | |
| 37.31% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 134 | | matches | | | ratio | 0.007 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 5 | | matches | | 0 | "She parked her scooter, leaving behind her delivery shift for Yu-Fei Cheung’s Golden Empress, trading the concrete safety of the restaurant for the unpredictabl…" | | 1 | "She forces a breath through her nose, demanding her racing heart slow down." | | 2 | "She stares at the void, her lungs burning, refusing to blink." | | 3 | "Rory stares, her mind stripping gears, rejecting the geometry in front of her." | | 4 | "She throws her arms out, regaining her balance, keeping her line of sight locked onto the trees." |
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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 | |