| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 19 | | tagDensity | 0.211 | | leniency | 0.421 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.41% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1393 | | totalAiIsmAdverbs | 1 | | 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) | |
| 46.16% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1393 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "streaming" | | 1 | "glint" | | 2 | "tension" | | 3 | "gloom" | | 4 | "footsteps" | | 5 | "weight" | | 6 | "silence" | | 7 | "echoed" | | 8 | "pulsed" | | 9 | "navigating" | | 10 | "mechanical" | | 11 | "flickered" | | 12 | "pulse" |
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| 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 | 76 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 76 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 91 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1387 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1105 | | uniqueNames | 17 | | maxNameDensity | 1.09 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Herrera" | | discoveredNames | | London | 2 | | Camden | 2 | | High | 1 | | Street | 1 | | Quinn | 12 | | Tomás | 1 | | Herrera | 11 | | Victorian | 2 | | Saint | 2 | | Christopher | 2 | | Tube | 1 | | Northern | 1 | | Blitz | 1 | | Scotland | 1 | | Yard | 1 | | Glock | 2 | | Seville | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Tomás" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Glock" |
| | places | | 0 | "London" | | 1 | "Camden" | | 2 | "High" | | 3 | "Street" | | 4 | "Victorian" | | 5 | "Scotland" | | 6 | "Seville" |
| | globalScore | 0.957 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | 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 | 1387 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 91 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 30.82 | | std | 19.36 | | cv | 0.628 | | sampleLengths | | 0 | 36 | | 1 | 49 | | 2 | 10 | | 3 | 59 | | 4 | 61 | | 5 | 19 | | 6 | 10 | | 7 | 14 | | 8 | 35 | | 9 | 74 | | 10 | 15 | | 11 | 18 | | 12 | 48 | | 13 | 39 | | 14 | 13 | | 15 | 25 | | 16 | 20 | | 17 | 53 | | 18 | 29 | | 19 | 51 | | 20 | 11 | | 21 | 4 | | 22 | 70 | | 23 | 27 | | 24 | 10 | | 25 | 43 | | 26 | 38 | | 27 | 4 | | 28 | 25 | | 29 | 35 | | 30 | 18 | | 31 | 19 | | 32 | 13 | | 33 | 25 | | 34 | 38 | | 35 | 41 | | 36 | 76 | | 37 | 19 | | 38 | 12 | | 39 | 4 | | 40 | 57 | | 41 | 47 | | 42 | 38 | | 43 | 19 | | 44 | 16 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 76 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 168 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 91 | | ratio | 0.055 | | matches | | 0 | "Neon bled across the puddles—garish greens and chemical pinks shuddering under the stomp of heavy boots." | | 1 | "The ramp descended past the modern drainage level into the brickwork of an abandoned Tube station—deeper than the Northern line, forgotten before the Blitz." | | 2 | "Chalk marks—serpents eating their tails, interlocking triangles, tallies counted in sets of seven—glowed faintly under her light, reflecting a sickly luminescence that had no right existing without UV." | | 3 | "Herrera dug his hand into his pocket and produced a sliver of polished ivory—or bone." | | 4 | "Whispers rose from the subterranean market—hundreds of voices bargaining in cadences that scraped against her eardrums like fingernails on slate." |
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| 82.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1121 | | adjectiveStacks | 3 | | stackExamples | | 0 | "turbulent brown torrent, disappearing" | | 1 | "illuminating wet ceramic tiles" | | 2 | "sulfurous orange light pulsed" |
| | adverbCount | 16 | | adverbRatio | 0.014272970561998216 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.01159678858162355 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 91 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 91 | | mean | 15.24 | | std | 8.02 | | cv | 0.526 | | sampleLengths | | 0 | 20 | | 1 | 16 | | 2 | 15 | | 3 | 15 | | 4 | 19 | | 5 | 10 | | 6 | 11 | | 7 | 3 | | 8 | 29 | | 9 | 16 | | 10 | 8 | | 11 | 24 | | 12 | 29 | | 13 | 5 | | 14 | 14 | | 15 | 10 | | 16 | 14 | | 17 | 19 | | 18 | 16 | | 19 | 7 | | 20 | 26 | | 21 | 9 | | 22 | 32 | | 23 | 15 | | 24 | 18 | | 25 | 4 | | 26 | 12 | | 27 | 8 | | 28 | 24 | | 29 | 9 | | 30 | 20 | | 31 | 10 | | 32 | 13 | | 33 | 4 | | 34 | 21 | | 35 | 20 | | 36 | 6 | | 37 | 15 | | 38 | 17 | | 39 | 15 | | 40 | 7 | | 41 | 9 | | 42 | 13 | | 43 | 8 | | 44 | 15 | | 45 | 28 | | 46 | 11 | | 47 | 4 | | 48 | 16 | | 49 | 4 |
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| 74.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.4725274725274725 | | totalSentences | 91 | | uniqueOpeners | 43 | |
| 44.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 75 | | matches | | 0 | "Only the hollow rush of" |
| | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 75 | | matches | | 0 | "Her voice cut through the" | | 1 | "He cut hard left into" | | 2 | "His dark curls whipped with" | | 3 | "Her hand drifted to the" | | 4 | "She gripped the chain links," | | 5 | "Her brown eyes narrowed, parsing" | | 6 | "She unclipped the heavy tactical" | | 7 | "Her service boots crunched on" | | 8 | "She pressed her spine against" | | 9 | "He offered it outward." | | 10 | "He turned slowly, raising his" | | 11 | "Her sharp jaw was set" | | 12 | "She eased the Glock back" |
| | ratio | 0.173 | |
| 46.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 62 | | totalSentences | 75 | | matches | | 0 | "Sheets of freezing London rain" | | 1 | "Neon bled across the puddles—garish" | | 2 | "Harlow Quinn surged through the" | | 3 | "Salt-and-pepper hair plastered against her" | | 4 | "Her voice cut through the" | | 5 | "Herrera didn't slow." | | 6 | "He cut hard left into" | | 7 | "His dark curls whipped with" | | 8 | "Quinn rounded the corner three" | | 9 | "Her hand drifted to the" | | 10 | "Herrera glanced over his shoulder." | | 11 | "The silver glint of a" | | 12 | "Herrera vaulted a rusted pallet," | | 13 | "The metal shrieked against masonry," | | 14 | "Quinn hit the gap without" | | 15 | "The sheet metal snagged her" | | 16 | "Rain rattled against dead buses" | | 17 | "Water rushed down the incline" | | 18 | "Herrera dropped to his belly," | | 19 | "Quinn reached the gate." |
| | ratio | 0.827 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 75 | | matches | (empty) | | ratio | 0 | |
| 72.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 5 | | matches | | 0 | "He cut hard left into an alleyway wedged between a shuttered kebab shop and a derelict Victorian warehouse, his trainers skidding on grease before finding purch…" | | 1 | "Only the hollow rush of subterranean water and an odd, dry static that set the hairs on her forearms on end." | | 2 | "Chalk marks—serpents eating their tails, interlocking triangles, tallies counted in sets of seven—glowed faintly under her light, reflecting a sickly luminescen…" | | 3 | "Herrera stood before a heavy wooden turnstile that had been crudely bolted into the Victorian masonry." | | 4 | "Whispers rose from the subterranean market—hundreds of voices bargaining in cadences that scraped against her eardrums like fingernails on slate." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 3 | | matches | | 0 | "Herrera lowered, his Seville accent sharpening around the vowels" | | 1 | "Herrera stepped, his boots hitting the flagstones on the other side" | | 2 | "Quinn said, her voice flat, steady, and ironclad" |
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| 97.37% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 19 | | tagDensity | 0.105 | | leniency | 0.211 | | rawRatio | 0.5 | | effectiveRatio | 0.105 | |