| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 15 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.10% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1449 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1449 | | totalAiIsms | 30 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "pulse" | | 1 | "perfect" | | 2 | "weight" | | 3 | "calculated" | | 4 | "pulsed" | | 5 | "traced" | | 6 | "footsteps" | | 7 | "rhythmic" | | 8 | "whisper" | | 9 | "warmth" | | 10 | "silence" | | 11 | "lilt" | | 12 | "chilled" | | 13 | "raced" | | 14 | "chill" | | 15 | "echoed" | | 16 | "vibrated" | | 17 | "cascading" | | 18 | "searing" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 157 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 157 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 168 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1438 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 1331 | | uniqueNames | 12 | | maxNameDensity | 1.05 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 1 | | Park | 1 | | Eva | 9 | | Heartstone | 1 | | October | 2 | | Evan | 3 | | Rory | 14 | | Good | 1 | | Welsh | 1 | | Cheung | 1 | | Golden | 1 | | Empress | 1 |
| | persons | | 0 | "Eva" | | 1 | "Evan" | | 2 | "Rory" | | 3 | "Cheung" |
| | places | | | globalScore | 0.974 | | windowScore | 0.833 | |
| 44.74% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 95 | | glossingSentenceCount | 4 | | matches | | 0 | "sounded like that" | | 1 | "felt like granite under her fingers, bu" | | 2 | "spirals that seemed to shift in her peripheral vision, unfurling like ferns" | | 3 | "felt like a keyhole" |
| |
| 60.92% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.391 | | wordCount | 1438 | | matches | | 0 | "not from pressure, but as if something beneath was pushing up" | | 1 | "Not outward, but inward, the spiral carving collapsing into itself with a sou" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 168 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 31.96 | | std | 21.86 | | cv | 0.684 | | sampleLengths | | 0 | 42 | | 1 | 46 | | 2 | 42 | | 3 | 61 | | 4 | 85 | | 5 | 7 | | 6 | 64 | | 7 | 75 | | 8 | 25 | | 9 | 8 | | 10 | 60 | | 11 | 7 | | 12 | 71 | | 13 | 7 | | 14 | 39 | | 15 | 49 | | 16 | 35 | | 17 | 8 | | 18 | 43 | | 19 | 34 | | 20 | 28 | | 21 | 38 | | 22 | 10 | | 23 | 2 | | 24 | 56 | | 25 | 1 | | 26 | 31 | | 27 | 28 | | 28 | 2 | | 29 | 38 | | 30 | 27 | | 31 | 41 | | 32 | 3 | | 33 | 40 | | 34 | 52 | | 35 | 27 | | 36 | 1 | | 37 | 36 | | 38 | 52 | | 39 | 9 | | 40 | 1 | | 41 | 41 | | 42 | 28 | | 43 | 25 | | 44 | 13 |
| |
| 98.56% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 157 | | matches | | 0 | "was carved" | | 1 | "was rusted" | | 2 | "were blistered" |
| |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 7 | | totalVerbs | 208 | | matches | | 0 | "was threading" | | 1 | "was screaming" | | 2 | "was spreading" | | 3 | "was widening" | | 4 | "was pushing" | | 5 | "was already moving" | | 6 | "was searing" |
| |
| 6.80% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 168 | | ratio | 0.048 | | matches | | 0 | "She’d counted her paces—forty-three from the last blackberry bramble, same as Eva had said." | | 1 | "Not a heartbeat—slower, heavier, like a deep drum heard through walls." | | 2 | "Or the way the wildflowers—white foxgloves, purple loosestrife—bloomed in perfect circles despite it being late October." | | 3 | "That’s what the cool-headed, intelligent part of her—the part that had calculated the quickest escape route from Evan’s flat, that had mapped every CCTV blind spot between there and the train station—said." | | 4 | "The hum changed pitch, dropping lower, and the pendant flared—a brief pulse of crimson light that cast her shadow long and sharp across the grass." | | 5 | "The pendant pulsed in quick succession—three fast beats, then a pause, then two." | | 6 | "It was spreading, seeping across the stone like living ink, forming shapes—letters, runes, a face that dissolved before she could focus on it." | | 7 | "The timing—her sudden reappearance in Rory’s life just weeks after the breakup, the offers of help that felt too good, too neat." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 475 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.03368421052631579 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.008421052631578947 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 168 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 168 | | mean | 8.56 | | std | 6.16 | | cv | 0.719 | | sampleLengths | | 0 | 14 | | 1 | 12 | | 2 | 10 | | 3 | 6 | | 4 | 7 | | 5 | 8 | | 6 | 14 | | 7 | 17 | | 8 | 11 | | 9 | 2 | | 10 | 12 | | 11 | 4 | | 12 | 2 | | 13 | 6 | | 14 | 5 | | 15 | 3 | | 16 | 8 | | 17 | 14 | | 18 | 11 | | 19 | 14 | | 20 | 11 | | 21 | 5 | | 22 | 3 | | 23 | 3 | | 24 | 4 | | 25 | 21 | | 26 | 6 | | 27 | 14 | | 28 | 16 | | 29 | 13 | | 30 | 7 | | 31 | 3 | | 32 | 10 | | 33 | 5 | | 34 | 16 | | 35 | 2 | | 36 | 4 | | 37 | 8 | | 38 | 16 | | 39 | 4 | | 40 | 32 | | 41 | 2 | | 42 | 5 | | 43 | 7 | | 44 | 25 | | 45 | 11 | | 46 | 14 | | 47 | 5 | | 48 | 3 | | 49 | 5 |
| |
| 43.71% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.32335329341317365 | | totalSentences | 167 | | uniqueOpeners | 54 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 138 | | matches | | 0 | "Just that hum, and the" | | 1 | "Light, quick, circling the clearing" | | 2 | "Too rhythmic, too deliberate." | | 3 | "Even the wind through the" | | 4 | "Too smooth, the Welsh lilt" | | 5 | "Then, from the darkness beyond" |
| | ratio | 0.043 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 138 | | matches | | 0 | "She hadn't stepped on moss" | | 1 | "She’d counted her paces—forty—three from" | | 2 | "Her phone screen cast a" | | 3 | "She tapped the screen." | | 4 | "She hadn’t brought a charger." | | 5 | "She thumbed the screen off" | | 6 | "Their pale bark glowed faintly," | | 7 | "She should go back." | | 8 | "Her phone screen lit up." | | 9 | "She approached the nearest standing" | | 10 | "It felt like granite under" | | 11 | "She traced one with her" | | 12 | "She opened her mouth to" | | 13 | "It moved with her, matching" | | 14 | "She took a step to" | | 15 | "They mirrored her." | | 16 | "Her heart hammered against her" | | 17 | "Her voice came out steady" | | 18 | "She faced the altar." | | 19 | "She could hear breathing now," |
| | ratio | 0.261 | |
| 83.19% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 104 | | totalSentences | 138 | | matches | | 0 | "The moss gave way under" | | 1 | "Rory froze, one foot half-lifted," | | 2 | "She hadn't stepped on moss" | | 3 | "The standing stones should have" | | 4 | "The ancient oaks that marked" | | 5 | "She’d counted her paces—forty—three from" | | 6 | "Her phone screen cast a" | | 7 | "The time hadn’t changed since" | | 8 | "She tapped the screen." | | 9 | "The battery indicator showed full" | | 10 | "She hadn’t brought a charger." | | 11 | "The word hung in the" | | 12 | "She thumbed the screen off" | | 13 | "The silver chain around her" | | 14 | "The Heartstone pendant, a deep" | | 15 | "Eva’s instructions had been specific." | | 16 | "A low hum, felt more" | | 17 | "A branch snapped somewhere to" | | 18 | "Rory turned slowly." | | 19 | "The movement felt syrupy, as" |
| | ratio | 0.754 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 138 | | matches | (empty) | | ratio | 0 | |
| 32.02% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 9 | | matches | | 0 | "Simple enough, even for a part-time delivery driver who’d fled an abusive ex and a pre-law degree in the same month." | | 1 | "That’s what the cool-headed, intelligent part of her—the part that had calculated the quickest escape route from Evan’s flat, that had mapped every CCTV blind s…" | | 2 | "In their centre, a flat stone altar, waist-high, stained dark with something that wasn’t moss." | | 3 | "The surface was carved with spirals that seemed to shift in her peripheral vision, unfurling like ferns." | | 4 | "The hum changed pitch, dropping lower, and the pendant flared—a brief pulse of crimson light that cast her shadow long and sharp across the grass." | | 5 | "She could hear breathing now, wet and ragged, as if through damaged lungs." | | 6 | "It was spreading, seeping across the stone like living ink, forming shapes—letters, runes, a face that dissolved before she could focus on it." | | 7 | "The timing—her sudden reappearance in Rory’s life just weeks after the breakup, the offers of help that felt too good, too neat." | | 8 | "It was widening, not from pressure, but as if something beneath was pushing up." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 16.67% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "she breathed (breathe)" | | 1 | "she whispered (whisper)" |
| | dialogueSentences | 15 | | tagDensity | 0.133 | | leniency | 0.267 | | rawRatio | 1 | | effectiveRatio | 0.267 | |