| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 26 | | tagDensity | 0.115 | | leniency | 0.231 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1287 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 2.87% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1287 | | totalAiIsms | 25 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "pumping" | | 1 | "gloom" | | 2 | "echoed" | | 3 | "footsteps" | | 4 | "etched" | | 5 | "pulse" | | 6 | "charged" | | 7 | "electric" | | 8 | "pulsed" | | 9 | "depths" | | 10 | "thundered" | | 11 | "standard" | | 12 | "flickered" | | 13 | "glinting" | | 14 | "loomed" | | 15 | "stomach" | | 16 | "lurched" | | 17 | "shattered" | | 18 | "whisper" | | 19 | "flicked" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 203 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 203 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 224 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1246 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 90.75% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 66 | | wordCount | 1097 | | uniqueNames | 24 | | maxNameDensity | 1.19 | | worstName | "Tomás" | | maxWindowNameDensity | 2 | | worstWindowName | "Tomás" | | discoveredNames | | Camden | 1 | | High | 1 | | Street | 1 | | Harlow | 9 | | Quinn | 1 | | Tomás | 13 | | Herrera | 3 | | Raven | 1 | | Nest | 1 | | Saint | 1 | | Christopher | 1 | | Parkway | 1 | | Morris | 2 | | Tube | 1 | | Blitz | 1 | | Footsteps | 2 | | Seville | 1 | | Torch | 4 | | Market | 4 | | Glock | 5 | | Veil | 2 | | Rain | 3 | | Boots | 3 | | Hatch | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Morris" | | 7 | "Footsteps" | | 8 | "Torch" | | 9 | "Market" | | 10 | "Glock" | | 11 | "Rain" | | 12 | "Boots" | | 13 | "Hatch" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Raven" | | 4 | "Seville" |
| | globalScore | 0.907 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | 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 | 1246 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 224 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 72 | | mean | 17.31 | | std | 13.02 | | cv | 0.752 | | sampleLengths | | 0 | 65 | | 1 | 12 | | 2 | 54 | | 3 | 51 | | 4 | 20 | | 5 | 7 | | 6 | 29 | | 7 | 31 | | 8 | 12 | | 9 | 36 | | 10 | 35 | | 11 | 37 | | 12 | 22 | | 13 | 4 | | 14 | 24 | | 15 | 35 | | 16 | 20 | | 17 | 20 | | 18 | 5 | | 19 | 7 | | 20 | 30 | | 21 | 23 | | 22 | 9 | | 23 | 8 | | 24 | 8 | | 25 | 7 | | 26 | 51 | | 27 | 24 | | 28 | 24 | | 29 | 5 | | 30 | 12 | | 31 | 19 | | 32 | 32 | | 33 | 7 | | 34 | 24 | | 35 | 14 | | 36 | 25 | | 37 | 14 | | 38 | 7 | | 39 | 8 | | 40 | 2 | | 41 | 27 | | 42 | 9 | | 43 | 11 | | 44 | 4 | | 45 | 9 | | 46 | 8 | | 47 | 20 | | 48 | 24 | | 49 | 21 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 203 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 280 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 28 | | semicolonCount | 0 | | flaggedSentences | 27 | | totalSentences | 224 | | ratio | 0.121 | | matches | | 0 | "Brown eyes locked on the figure ahead—short curly dark hair, olive skin flashing under streetlamps, jacket flapping like a wounded bird." | | 1 | "The man—Tomás Herrera, she'd clocked his face from the Raven's Nest CCTV—glanced back." | | 2 | "Traffic snarled at the junction—black cabs honking, headlights slicing fog." | | 3 | "Her worn leather watch ticked under rain's assault—midnight past." | | 4 | "Padlock hung loose—forced earlier." | | 5 | "She rammed shoulder first—wood splintered inward." | | 6 | "Torch beam caught him at a junction—forked tunnels, one sealed with chain-link, the other dropping steeper." | | 7 | "Veil Market rumours—whispers from informants, black market under the city." | | 8 | "Hatch began closing—gears whirring." | | 9 | "Smells wafted—sulphur, blood, herbs burning electric." | | 10 | "Stalls crammed against tiled walls—vials bubbling purple, blades humming with trapped screams, cages holding things with too many eyes." | | 11 | "Grabbed a crossbow—bolts tipped glowing green." | | 12 | "But Herrera slipped deeper—answers on Morris's death buried there." | | 13 | "Phone light flickered on—dim blue." | | 14 | "Passed bone token for a satchel—bulging with vials." | | 15 | "Boots hit tiles—jarring knees." | | 16 | "Jars shattered—slime oozed, something inside shrieked." | | 17 | "A vendor lunged—tentacle arm whipping." | | 18 | "Guard dropped from hatch—horns first, crossbow raised." | | 19 | "It sank into a caged imp—creature exploded in green ichor." | | 20 | "Stairs at platform's end—down further." | | 21 | "Glock barked—warning shot ricocheted off pipes." | | 22 | "Torchlight from below—no, bioluminescent fungi clinging walls, pulsing like veins." | | 23 | "Podium held a chained shifter—fur matted, eyes feral." | | 24 | "Handed satchel to a figure—cloaked, face obscured." | | 25 | "Eyes turned—predatory." | | 26 | "Radio crackled faint—static whisper." |
| |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1135 | | adjectiveStacks | 2 | | stackExamples | | 0 | "ahead—short curly dark hair," | | 1 | "black ahead, abandoned Tube" |
| | adverbCount | 14 | | adverbRatio | 0.012334801762114538 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.000881057268722467 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 224 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 224 | | mean | 5.56 | | std | 3.93 | | cv | 0.707 | | sampleLengths | | 0 | 13 | | 1 | 13 | | 2 | 5 | | 3 | 13 | | 4 | 21 | | 5 | 12 | | 6 | 13 | | 7 | 4 | | 8 | 5 | | 9 | 10 | | 10 | 22 | | 11 | 3 | | 12 | 11 | | 13 | 8 | | 14 | 10 | | 15 | 4 | | 16 | 3 | | 17 | 2 | | 18 | 10 | | 19 | 7 | | 20 | 13 | | 21 | 7 | | 22 | 2 | | 23 | 2 | | 24 | 9 | | 25 | 16 | | 26 | 3 | | 27 | 9 | | 28 | 3 | | 29 | 16 | | 30 | 5 | | 31 | 7 | | 32 | 3 | | 33 | 2 | | 34 | 18 | | 35 | 4 | | 36 | 7 | | 37 | 2 | | 38 | 8 | | 39 | 2 | | 40 | 4 | | 41 | 6 | | 42 | 15 | | 43 | 11 | | 44 | 5 | | 45 | 5 | | 46 | 11 | | 47 | 5 | | 48 | 9 | | 49 | 13 |
| |
| 100.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.6383928571428571 | | totalSentences | 224 | | uniqueOpeners | 143 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 159 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 159 | | matches | | 0 | "Her boots slapped wet asphalt." | | 1 | "Her voice cut through the" | | 2 | "He bolted harder, shoulders pumping." | | 3 | "She vaulted a fallen umbrella," | | 4 | "He cleared it, vanished into" | | 5 | "She followed, radio crackling at" | | 6 | "Her worn leather watch ticked" | | 7 | "He didn't answer." | | 8 | "He kicked it free, yanked" | | 9 | "She rammed shoulder first—wood splintered" | | 10 | "Her hand found the torch" | | 11 | "His accent rolled thick, Seville" | | 12 | "He slotted the token into" | | 13 | "Her watch strap snapped under" | | 14 | "She hauled harder, military precision" | | 15 | "Her hand went to holster." | | 16 | "She crept to hatch edge," | | 17 | "He glanced up." | | 18 | "Their eyes met across the" | | 19 | "She twisted mid-air, coat ballooning." |
| | ratio | 0.189 | |
| 82.64% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 120 | | totalSentences | 159 | | matches | | 0 | "Neon signs bled pink and" | | 1 | "Her boots slapped wet asphalt." | | 2 | "Salt-and-pepper hair clung to her" | | 3 | "Brown eyes locked on the" | | 4 | "Her voice cut through the" | | 5 | "The man—Tomás Herrera, she'd clocked" | | 6 | "He bolted harder, shoulders pumping." | | 7 | "A Saint Christopher medallion swung" | | 8 | "Harlow's lungs burned." | | 9 | "She vaulted a fallen umbrella," | | 10 | "Traffic snarled at the junction—black" | | 11 | "Tomás darted between cars." | | 12 | "A horn blared." | | 13 | "He cleared it, vanished into" | | 14 | "She followed, radio crackling at" | | 15 | "Her worn leather watch ticked" | | 16 | "Partner's ghost whispered in her" | | 17 | "Alley swallowed them." | | 18 | "Brick walls closed in, graffiti" | | 19 | "Puddles splashed calves-deep." |
| | ratio | 0.755 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 159 | | matches | (empty) | | ratio | 0 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 2 | | matches | | 0 | "Partner's ghost whispered in her skull: Morris, gone three years, chasing shadows that didn't bleed normal." | | 1 | "Informants spun tales: wraiths that ate bullets, shifters dodging lead." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 26 | | tagDensity | 0.038 | | leniency | 0.077 | | rawRatio | 1 | | effectiveRatio | 0.077 | |