| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1816 | | 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) | |
| 64.21% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1816 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "pulse" | | 1 | "standard" | | 2 | "weight" | | 3 | "unreadable" | | 4 | "silence" | | 5 | "anticipation" | | 6 | "shattered" | | 7 | "footsteps" | | 8 | "echoing" | | 9 | "echoed" | | 10 | "flickered" |
| |
| 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 | 154 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 154 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 167 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1802 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 1675 | | uniqueNames | 15 | | maxNameDensity | 0.66 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 11 | | Camden | 2 | | High | 1 | | Street | 1 | | Veil | 2 | | Market | 2 | | Morris | 3 | | Tube | 3 | | Maglite | 7 | | Transport | 1 | | London | 1 | | Sauer | 1 | | Glass | 2 | | Old | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Maglite" | | 4 | "Sauer" | | 5 | "Glass" | | 6 | "Old" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Veil" | | 4 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 108 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like a leather-bound journal" | | 1 | "tasted like ozone and incense, and the mu" | | 2 | "sounded like anticipation" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.555 | | wordCount | 1802 | | matches | | 0 | "no visible tattoos on his arms but" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 167 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 73 | | mean | 24.68 | | std | 21.28 | | cv | 0.862 | | sampleLengths | | 0 | 18 | | 1 | 71 | | 2 | 44 | | 3 | 3 | | 4 | 10 | | 5 | 69 | | 6 | 43 | | 7 | 3 | | 8 | 42 | | 9 | 32 | | 10 | 41 | | 11 | 52 | | 12 | 37 | | 13 | 24 | | 14 | 5 | | 15 | 75 | | 16 | 10 | | 17 | 70 | | 18 | 3 | | 19 | 67 | | 20 | 23 | | 21 | 9 | | 22 | 55 | | 23 | 44 | | 24 | 2 | | 25 | 2 | | 26 | 10 | | 27 | 25 | | 28 | 12 | | 29 | 9 | | 30 | 22 | | 31 | 36 | | 32 | 28 | | 33 | 4 | | 34 | 42 | | 35 | 12 | | 36 | 72 | | 37 | 22 | | 38 | 26 | | 39 | 5 | | 40 | 48 | | 41 | 12 | | 42 | 3 | | 43 | 27 | | 44 | 35 | | 45 | 12 | | 46 | 29 | | 47 | 4 | | 48 | 6 | | 49 | 3 |
| |
| 98.43% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 154 | | matches | | 0 | "was gone" | | 1 | "been replaced" | | 2 | "been erected" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 272 | | matches | | 0 | "wasn't losing" | | 1 | "was watching" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 167 | | ratio | 0.066 | | matches | | 0 | "The suspect—a tall figure in a dark waterproof jacket—vaulted a cluster of wheelie bins at the corner of Camden High Street, sending them crashing into a shuttered fishmonger's." | | 1 | "It carried a smell that had no business being underground—cinnamon, copper, something that stung like menthol at the back of her throat." | | 2 | "The tile walls narrowed, pressing close, and the graffiti gave way to older markings—symbols she didn't recognise carved into the plaster." | | 3 | "Old Tube station tilework—the deep green and cream of a bygone era—still lined the curved ceiling, but someone had strung hundreds of mismatched lights across the space, casting everything in a feverish amber-gold glow." | | 4 | "Eyes found her—some pale, some not, some that seemed to catch the light wrong, like a cat's." | | 5 | "She caught a glimpse of movement past a row of stalls—a dark jacket disappearing around a corner." | | 6 | "She heard footsteps echoing down the left passage—quick, desperate, fading." | | 7 | "No way to call for either—the signal had died somewhere around the second flight of stairs." | | 8 | "The tunnel opened into a junction—a larger space where three passages met beneath a low concrete ceiling." | | 9 | "The features were close—the same build, the same jacket—but the jawline was too narrow, the skin too pale." | | 10 | "Something exploded from the darkness of the far tunnel—another figure, fast, low, closing the distance in three bounding strides." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1703 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.022900763358778626 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0035231943628890195 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 167 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 167 | | mean | 10.79 | | std | 7.74 | | cv | 0.717 | | sampleLengths | | 0 | 18 | | 1 | 5 | | 2 | 17 | | 3 | 28 | | 4 | 21 | | 5 | 22 | | 6 | 22 | | 7 | 3 | | 8 | 6 | | 9 | 4 | | 10 | 13 | | 11 | 14 | | 12 | 21 | | 13 | 21 | | 14 | 8 | | 15 | 3 | | 16 | 10 | | 17 | 22 | | 18 | 3 | | 19 | 16 | | 20 | 17 | | 21 | 3 | | 22 | 6 | | 23 | 12 | | 24 | 10 | | 25 | 10 | | 26 | 16 | | 27 | 14 | | 28 | 11 | | 29 | 10 | | 30 | 15 | | 31 | 5 | | 32 | 22 | | 33 | 16 | | 34 | 3 | | 35 | 18 | | 36 | 6 | | 37 | 8 | | 38 | 3 | | 39 | 7 | | 40 | 5 | | 41 | 6 | | 42 | 21 | | 43 | 5 | | 44 | 2 | | 45 | 41 | | 46 | 10 | | 47 | 4 | | 48 | 34 | | 49 | 20 |
| |
| 44.71% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.32934131736526945 | | totalSentences | 167 | | uniqueOpeners | 55 | |
| 48.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 138 | | matches | | 0 | "Maybe he'd caught himself on" | | 1 | "Maybe he'd been hurt worse" |
| | ratio | 0.014 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 138 | | matches | | 0 | "She pumped her legs harder," | | 1 | "She vaulted after him, one" | | 2 | "He cut left into a" | | 3 | "She could hear his breathing" | | 4 | "He didn't look back." | | 5 | "She'd been tracking this one" | | 6 | "She skidded on the wet" | | 7 | "She didn't let it slow" | | 8 | "She heard the chain snap," | | 9 | "She stood there, chest heaving," | | 10 | "Her hand found the small" | | 11 | "It carried a smell that" | | 12 | "She clicked off the Maglite," | | 13 | "Her pulse kicked in her" | | 14 | "She started down the stairs." | | 15 | "She patted her jacket pocket." | | 16 | "She stepped off the last" | | 17 | "She felt the weight of" | | 18 | "She extended a bony hand," | | 19 | "She didn't reach for her" |
| | ratio | 0.29 | |
| 57.83% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 111 | | totalSentences | 138 | | matches | | 0 | "The body hit the pavement" | | 1 | "Detective Harlow Quinn didn't slow." | | 2 | "She pumped her legs harder," | | 3 | "The suspect—a tall figure in" | | 4 | "She vaulted after him, one" | | 5 | "He cut left into a" | | 6 | "She could hear his breathing" | | 7 | "The words dissolved into the" | | 8 | "He didn't look back." | | 9 | "The street opened up ahead," | | 10 | "Quinn chased the sound of" | | 11 | "She'd been tracking this one" | | 12 | "A back-alley supplier." | | 13 | "Bone tokens, black-market trinkets, whispered" | | 14 | "The kind of informant who" | | 15 | "The suspect darted right, disappearing" | | 16 | "She skidded on the wet" | | 17 | "Pain flared white-hot." | | 18 | "She didn't let it slow" | | 19 | "The alley ended at a" |
| | ratio | 0.804 | |
| 36.23% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 138 | | matches | | 0 | "By the time she reached" |
| | ratio | 0.007 | |
| 95.86% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 76 | | technicalSentenceCount | 5 | | matches | | 0 | "The kind of informant who vanished into thin air the moment you got close, and this time she wasn't losing another lead." | | 1 | "It carried a smell that had no business being underground—cinnamon, copper, something that stung like menthol at the back of her throat." | | 2 | "A black market that sold enchanted goods, banned alchemical substances, information that the right people would kill for." | | 3 | "The man on the ground scrambled backward, dragging himself along the tracks, and Quinn drew her sidearm, the SIG's safety clicking off in the same instant." | | 4 | "In front of her, the thing wearing her suspect's face took a step forward, its gold eyes catching the light, its smile widening into something that had too many…" |
| |
| 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 | |