| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 20 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1151 | | 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) | |
| 47.87% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1151 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "echoed" | | 1 | "footsteps" | | 2 | "flickered" | | 3 | "standard" | | 4 | "weight" | | 5 | "velvet" | | 6 | "intensity" | | 7 | "familiar" | | 8 | "glinting" | | 9 | "charged" |
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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 | 161 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 161 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 176 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 12 | | markdownWords | 44 | | totalWords | 1157 | | ratio | 0.038 | | matches | | 0 | "Never let them see you slow down, Harlow." | | 1 | "Where are you going, kid?" | | 2 | "Interesting." | | 3 | "What did you find, kid?" | | 4 | "Hell." | | 5 | "Don't think about Morris. Think about now." | | 6 | "BEDFORD STATION - CLOSED 1932." | | 7 | "Bedford Station. Camden. Abandoned." | | 8 | "Follow or don't." | | 9 | "Click." | | 10 | "Shit." | | 11 | "Shit shit shit." |
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| 62.50% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 1 | | matches | | 0 | "The Veil Market, they called it." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 1015 | | uniqueNames | 22 | | maxNameDensity | 0.49 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Covent | 2 | | Garden | 2 | | Endell | 1 | | Street | 1 | | Urdu | 1 | | Quinn | 5 | | Raven | 1 | | Nest | 1 | | St | 1 | | Park | 1 | | Morris | 3 | | Station | 1 | | Veil | 1 | | Market | 1 | | Sauer | 1 | | Locked | 1 | | Tube | 1 | | Saint | 1 | | Christopher | 1 | | Recognition | 1 | | Rookery | 1 | | Right | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Morris" | | 3 | "Station" | | 4 | "Market" | | 5 | "Saint" | | 6 | "Christopher" |
| | places | | 0 | "Covent" | | 1 | "Garden" | | 2 | "Endell" | | 3 | "Street" | | 4 | "Urdu" | | 5 | "St" | | 6 | "Recognition" |
| | globalScore | 1 | | windowScore | 1 | |
| 88.27% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like less" | | 1 | "looked like people" |
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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 | 1157 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 176 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 65 | | mean | 17.8 | | std | 15.26 | | cv | 0.857 | | sampleLengths | | 0 | 15 | | 1 | 26 | | 2 | 2 | | 3 | 3 | | 4 | 36 | | 5 | 46 | | 6 | 5 | | 7 | 37 | | 8 | 37 | | 9 | 27 | | 10 | 1 | | 11 | 55 | | 12 | 35 | | 13 | 5 | | 14 | 41 | | 15 | 3 | | 16 | 25 | | 17 | 1 | | 18 | 30 | | 19 | 7 | | 20 | 34 | | 21 | 13 | | 22 | 22 | | 23 | 6 | | 24 | 51 | | 25 | 4 | | 26 | 30 | | 27 | 5 | | 28 | 3 | | 29 | 40 | | 30 | 23 | | 31 | 16 | | 32 | 14 | | 33 | 1 | | 34 | 5 | | 35 | 45 | | 36 | 45 | | 37 | 15 | | 38 | 6 | | 39 | 26 | | 40 | 4 | | 41 | 16 | | 42 | 9 | | 43 | 14 | | 44 | 4 | | 45 | 23 | | 46 | 6 | | 47 | 1 | | 48 | 11 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 161 | | matches | | 0 | "been replaced" | | 1 | "were made" |
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| 55.07% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 184 | | matches | | 0 | "were coming" | | 1 | "was heading" | | 2 | "were getting" | | 3 | "was gaining" |
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| 61.69% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 176 | | ratio | 0.028 | | matches | | 0 | "He glanced back - young, mid-twenties, hood pulled tight." | | 1 | "No - a token." | | 2 | "The suspect reached a grate in the wall - an old service entrance, rusted, padlocked." | | 3 | "The air that rose from below smelled wrong - copper and ash and something floral she couldn't place." | | 4 | "Someone had hammered an old sign into the archway: *BEDFORD STATION - CLOSED 1932.*" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 337 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 9 | | adverbRatio | 0.026706231454005934 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.002967359050445104 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 176 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 176 | | mean | 6.57 | | std | 4.56 | | cv | 0.693 | | sampleLengths | | 0 | 10 | | 1 | 1 | | 2 | 1 | | 3 | 1 | | 4 | 1 | | 5 | 1 | | 6 | 9 | | 7 | 12 | | 8 | 1 | | 9 | 4 | | 10 | 2 | | 11 | 3 | | 12 | 7 | | 13 | 14 | | 14 | 15 | | 15 | 7 | | 16 | 7 | | 17 | 8 | | 18 | 9 | | 19 | 6 | | 20 | 9 | | 21 | 5 | | 22 | 4 | | 23 | 16 | | 24 | 5 | | 25 | 5 | | 26 | 7 | | 27 | 6 | | 28 | 13 | | 29 | 8 | | 30 | 5 | | 31 | 5 | | 32 | 4 | | 33 | 9 | | 34 | 4 | | 35 | 4 | | 36 | 6 | | 37 | 1 | | 38 | 9 | | 39 | 29 | | 40 | 3 | | 41 | 1 | | 42 | 1 | | 43 | 12 | | 44 | 12 | | 45 | 2 | | 46 | 11 | | 47 | 10 | | 48 | 5 | | 49 | 6 |
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| 66.10% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.45454545454545453 | | totalSentences | 176 | | uniqueOpeners | 80 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 127 | | matches | | 0 | "Away from the river." | | 1 | "Away from the usual hiding" | | 2 | "Then he vanished into the" | | 3 | "Then a hand grabbed her" |
| | ratio | 0.031 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 127 | | matches | | 0 | "Her boots hit the wet" | | 1 | "He glanced back - young," | | 2 | "He ran faster." | | 3 | "Her father's voice echoed from" | | 4 | "He cut left through a" | | 5 | "She followed, boots splashing through" | | 6 | "She knew these streets." | | 7 | "He burst out onto Endell" | | 8 | "She didn't catch the rest." | | 9 | "He was heading north." | | 10 | "He ran courier jobs for" | | 11 | "He turned again, down another" | | 12 | "Her leather watch strap was" | | 13 | "She was gaining." | | 14 | "He fumbled with something at" | | 15 | "She knew what that meant." | | 16 | "She'd seen it before, three" | | 17 | "He produced a key from" | | 18 | "He yanked the grate open." | | 19 | "He looked back at her" |
| | ratio | 0.268 | |
| 70.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 99 | | totalSentences | 127 | | matches | | 0 | "Her boots hit the wet" | | 1 | "He glanced back - young," | | 2 | "Streetlight caught the edge of" | | 3 | "Panic made people sloppy." | | 4 | "He ran faster." | | 5 | "Quinn pushed harder, legs burning," | | 6 | "Her father's voice echoed from" | | 7 | "He cut left through a" | | 8 | "She followed, boots splashing through" | | 9 | "The alley stank of rubbish" | | 10 | "Graffiti crawled up the brick" | | 11 | "A cat hissed from a" | | 12 | "The suspect's footsteps echoed ahead," | | 13 | "She knew these streets." | | 14 | "Soho bled into Covent Garden," | | 15 | "The tourist crowds had thinned." | | 16 | "The regulars were coming out." | | 17 | "Bats after dark, every one" | | 18 | "He burst out onto Endell" | | 19 | "A taxi blared its horn" |
| | ratio | 0.78 | |
| 78.74% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 127 | | matches | | 0 | "To seal the entrance." | | 1 | "To wait for a team" |
| | ratio | 0.016 | |
| 50.69% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 4 | | matches | | 0 | "Something that made him check over his shoulder every thirty seconds." | | 1 | "Something that made him run when she'd called his name." | | 2 | "Glass cases displaying things that glowed and whispered and twitched in their containers." | | 3 | "Their eyes tracked her with an intensity that made her skin crawl." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "she breathed (breathe)" |
| | dialogueSentences | 20 | | tagDensity | 0.05 | | leniency | 0.1 | | rawRatio | 1 | | effectiveRatio | 0.1 | |