| 80.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 3 | | adverbTags | | 0 | "he said quietly [quietly]" | | 1 | "she said softly [softly]" | | 2 | "he said simply [simply]" |
| | dialogueSentences | 50 | | tagDensity | 0.42 | | leniency | 0.84 | | rawRatio | 0.143 | | effectiveRatio | 0.12 | |
| 85.75% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1404 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "utterly" | | 1 | "really" | | 2 | "sharply" | | 3 | "softly" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 21.65% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1404 | | totalAiIsms | 22 | | found | | | highlights | | 0 | "pulse" | | 1 | "tracing" | | 2 | "familiar" | | 3 | "glint" | | 4 | "weight" | | 5 | "whisper" | | 6 | "reminder" | | 7 | "measured" | | 8 | "flicked" | | 9 | "flicker" | | 10 | "pulsed" | | 11 | "unravel" | | 12 | "predictable" | | 13 | "unreadable" | | 14 | "clandestine" | | 15 | "furrowed" | | 16 | "warmth" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 109 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 109 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 138 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1392 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 12 | | wordCount | 1037 | | uniqueNames | 8 | | maxNameDensity | 0.29 | | worstName | "Prague" | | maxWindowNameDensity | 1 | | worstWindowName | "Prague" | | discoveredNames | | Carter | 1 | | Raven | 2 | | Nest | 2 | | London | 1 | | Prague | 3 | | Cardiff | 1 | | Hidden | 1 | | Soho | 1 |
| | persons | | | places | | 0 | "London" | | 1 | "Prague" | | 2 | "Cardiff" | | 3 | "Soho" |
| | globalScore | 1 | | windowScore | 1 | |
| 79.58% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like weakness" | | 1 | "as if offering it across a chasm" |
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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 | 1392 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 138 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 33.14 | | std | 20.85 | | cv | 0.629 | | sampleLengths | | 0 | 95 | | 1 | 80 | | 2 | 65 | | 3 | 78 | | 4 | 10 | | 5 | 12 | | 6 | 27 | | 7 | 24 | | 8 | 40 | | 9 | 24 | | 10 | 14 | | 11 | 22 | | 12 | 46 | | 13 | 11 | | 14 | 6 | | 15 | 43 | | 16 | 69 | | 17 | 17 | | 18 | 39 | | 19 | 16 | | 20 | 36 | | 21 | 25 | | 22 | 40 | | 23 | 16 | | 24 | 28 | | 25 | 11 | | 26 | 28 | | 27 | 21 | | 28 | 7 | | 29 | 40 | | 30 | 41 | | 31 | 28 | | 32 | 23 | | 33 | 31 | | 34 | 57 | | 35 | 20 | | 36 | 30 | | 37 | 32 | | 38 | 7 | | 39 | 31 | | 40 | 53 | | 41 | 49 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 109 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 196 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 1 | | flaggedSentences | 8 | | totalSentences | 138 | | ratio | 0.058 | | matches | | 0 | "Maps lined the walls—faded parchment lines tracing borders she’d once studied in law school, now half-forgotten." | | 1 | "After so long, it still carried that old rhythm—like she’d never left." | | 2 | "The bartender towels lingered in his hand like a nervous gesture, and her fingers itched at the scar on her left wrist—a small crescent moon pressed into skin, a reminder of a childhood accident she’d never mentioned." | | 3 | "She stared at the ring—silver band, crest of a raven in mid-flight—her breath catching." | | 4 | "She searched his face—the neat lines around his eyes, the limp that spoke of a knee blown out in Prague, the beard trimmed to match his grey-streaked hair—and felt the years between them unravel." | | 5 | "“I’m done running errands for shadows.” Her gaze flicked to the bookshelf at the back of the room—the one she’d never noticed before—its spines brimming with leather-bound volumes." | | 6 | "The bar’s murmur receded; the neon sign downed its flicker." | | 7 | "Inside The Raven’s Nest, two lives converged once more—bound by the scars of memory, the ache of regret, and the fragile promise of forgiveness." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1054 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.03700189753320683 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.010436432637571158 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 138 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 138 | | mean | 10.09 | | std | 7.43 | | cv | 0.737 | | sampleLengths | | 0 | 23 | | 1 | 17 | | 2 | 21 | | 3 | 16 | | 4 | 10 | | 5 | 8 | | 6 | 10 | | 7 | 16 | | 8 | 15 | | 9 | 27 | | 10 | 12 | | 11 | 9 | | 12 | 27 | | 13 | 5 | | 14 | 6 | | 15 | 18 | | 16 | 6 | | 17 | 16 | | 18 | 14 | | 19 | 5 | | 20 | 37 | | 21 | 10 | | 22 | 6 | | 23 | 2 | | 24 | 4 | | 25 | 8 | | 26 | 13 | | 27 | 6 | | 28 | 15 | | 29 | 9 | | 30 | 12 | | 31 | 28 | | 32 | 4 | | 33 | 14 | | 34 | 6 | | 35 | 3 | | 36 | 2 | | 37 | 2 | | 38 | 7 | | 39 | 9 | | 40 | 8 | | 41 | 5 | | 42 | 2 | | 43 | 3 | | 44 | 20 | | 45 | 15 | | 46 | 6 | | 47 | 5 | | 48 | 6 | | 49 | 4 |
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| 41.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.2971014492753623 | | totalSentences | 138 | | uniqueOpeners | 41 | |
| 34.01% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 98 | | matches | | 0 | "Then he offered a glass." |
| | ratio | 0.01 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 71 | | totalSentences | 98 | | matches | | 0 | "She tightened the collar of" | | 1 | "It all felt achingly familiar" | | 2 | "She stepped inside, boots squeaking" | | 3 | "His auburn hair was shot" | | 4 | "His limp had eased over" | | 5 | "She remembered the uneven stride" | | 6 | "She’d thought him invincible then." | | 7 | "He straightened, set the glass" | | 8 | "She recognized the angle of" | | 9 | "His hazel eyes met her" | | 10 | "She exhaled the name, felt" | | 11 | "he said, voice low, measured" | | 12 | "She forced a nod, felt" | | 13 | "She’d counted every one of" | | 14 | "He cleared his throat and" | | 15 | "She shifted, brushing a strand" | | 16 | "She tried to sound casual," | | 17 | "He lifted a brow." | | 18 | "His gaze flicked to her" | | 19 | "Her heart skipped." |
| | ratio | 0.724 | |
| 26.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 85 | | totalSentences | 98 | | matches | | 0 | "Aurora Carter paused under the" | | 1 | "She tightened the collar of" | | 2 | "The bar’s hush swallowed her," | | 3 | "Maps lined the walls—faded parchment" | | 4 | "It all felt achingly familiar" | | 5 | "She stepped inside, boots squeaking" | | 6 | "A man stood at the" | | 7 | "The amber light caught the" | | 8 | "His auburn hair was shot" | | 9 | "His limp had eased over" | | 10 | "She remembered the uneven stride" | | 11 | "She’d thought him invincible then." | | 12 | "The limp had felt like" | | 13 | "He straightened, set the glass" | | 14 | "She recognized the angle of" | | 15 | "His hazel eyes met her" | | 16 | "The bartender towels lingered in" | | 17 | "She exhaled the name, felt" | | 18 | "he said, voice low, measured" | | 19 | "She forced a nod, felt" |
| | ratio | 0.867 | |
| 51.02% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 98 | | matches | | | ratio | 0.01 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 1 | | matches | | 0 | "She searched his face—the neat lines around his eyes, the limp that spoke of a knee blown out in Prague, the beard trimmed to match his grey-streaked hair—and f…" |
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| 77.38% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 2 | | matches | | 0 | "he said, voice low, measured" | | 1 | "She tucked, thumb brushing the edge of her scar" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 2 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "she repeated (repeat)" |
| | dialogueSentences | 50 | | tagDensity | 0.16 | | leniency | 0.32 | | rawRatio | 0.25 | | effectiveRatio | 0.08 | |