| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "The gatekeeper stood away [away]" |
| | dialogueSentences | 63 | | tagDensity | 0.111 | | leniency | 0.222 | | rawRatio | 0.143 | | effectiveRatio | 0.032 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2393 | | 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) | |
| 85.37% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2393 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "scanned" | | 1 | "pulse" | | 2 | "jaw clenched" | | 3 | "affection" | | 4 | "fluttered" | | 5 | "stomach" | | 6 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 192 | | matches | (empty) | |
| 83.33% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 4 | | narrationSentences | 192 | | filterMatches | | | hedgeMatches | | 0 | "started to" | | 1 | "tried to" | | 2 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 248 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 51 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2387 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 66 | | wordCount | 2028 | | uniqueNames | 26 | | maxNameDensity | 0.64 | | worstName | "Harlow" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Herrera" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Saint | 3 | | Christopher | 3 | | Herrera | 12 | | Harlow | 13 | | Greek | 1 | | Street | 1 | | Tottenham | 1 | | Court | 1 | | Road | 2 | | TfL | 1 | | Northern | 1 | | Morris | 4 | | Camden | 2 | | Town | 1 | | Victorian | 1 | | Tube | 1 | | Charing | 1 | | Cross | 1 | | Professional | 1 | | Standards | 1 | | Tomás | 5 | | Deena | 3 | | Market | 1 | | Doors | 3 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Herrera" | | 5 | "Harlow" | | 6 | "Morris" | | 7 | "Tomás" | | 8 | "Deena" | | 9 | "Market" | | 10 | "Doors" |
| | places | | 0 | "Greek" | | 1 | "Street" | | 2 | "Tottenham" | | 3 | "Court" | | 4 | "Road" | | 5 | "Northern" | | 6 | "Camden" | | 7 | "Town" | | 8 | "Charing" | | 9 | "Cross" | | 10 | "Professional" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 147 | | glossingSentenceCount | 2 | | matches | | 0 | "smelled like incense gone wrong" | | 1 | "looked like a ghost trying to remember ho" |
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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 | 2387 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 248 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 98 | | mean | 24.36 | | std | 29.72 | | cv | 1.22 | | sampleLengths | | 0 | 120 | | 1 | 54 | | 2 | 1 | | 3 | 22 | | 4 | 14 | | 5 | 8 | | 6 | 14 | | 7 | 5 | | 8 | 34 | | 9 | 5 | | 10 | 1 | | 11 | 6 | | 12 | 10 | | 13 | 4 | | 14 | 3 | | 15 | 51 | | 16 | 2 | | 17 | 2 | | 18 | 59 | | 19 | 8 | | 20 | 12 | | 21 | 9 | | 22 | 57 | | 23 | 52 | | 24 | 4 | | 25 | 3 | | 26 | 3 | | 27 | 62 | | 28 | 58 | | 29 | 2 | | 30 | 57 | | 31 | 3 | | 32 | 78 | | 33 | 49 | | 34 | 12 | | 35 | 80 | | 36 | 2 | | 37 | 4 | | 38 | 4 | | 39 | 66 | | 40 | 1 | | 41 | 65 | | 42 | 1 | | 43 | 1 | | 44 | 4 | | 45 | 4 | | 46 | 14 | | 47 | 84 | | 48 | 10 | | 49 | 4 |
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| 99.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 192 | | matches | | 0 | "was gone" | | 1 | "been opened" | | 2 | "been scraped" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 354 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 248 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 2033 | | adjectiveStacks | 1 | | stackExamples | | 0 | "done under different lights" |
| | adverbCount | 43 | | adverbRatio | 0.02115100836202656 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 248 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 248 | | mean | 9.63 | | std | 6.63 | | cv | 0.689 | | sampleLengths | | 0 | 20 | | 1 | 25 | | 2 | 14 | | 3 | 2 | | 4 | 18 | | 5 | 14 | | 6 | 10 | | 7 | 13 | | 8 | 4 | | 9 | 17 | | 10 | 9 | | 11 | 17 | | 12 | 11 | | 13 | 1 | | 14 | 3 | | 15 | 19 | | 16 | 14 | | 17 | 8 | | 18 | 13 | | 19 | 1 | | 20 | 5 | | 21 | 3 | | 22 | 5 | | 23 | 9 | | 24 | 10 | | 25 | 7 | | 26 | 5 | | 27 | 1 | | 28 | 6 | | 29 | 10 | | 30 | 4 | | 31 | 3 | | 32 | 7 | | 33 | 6 | | 34 | 10 | | 35 | 10 | | 36 | 11 | | 37 | 1 | | 38 | 6 | | 39 | 2 | | 40 | 2 | | 41 | 19 | | 42 | 14 | | 43 | 3 | | 44 | 5 | | 45 | 14 | | 46 | 4 | | 47 | 8 | | 48 | 12 | | 49 | 9 |
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| 45.83% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.3064516129032258 | | totalSentences | 248 | | uniqueOpeners | 76 | |
| 18.12% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 184 | | matches | | 0 | "Somewhere above, a train crossed" |
| | ratio | 0.005 | |
| 56.96% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 75 | | totalSentences | 184 | | matches | | 0 | "Her worn leather watch ticked" | | 1 | "She touched the inside pocket" | | 2 | "She’d stared at them on" | | 3 | "He moved like he scanned" | | 4 | "He didn’t turn." | | 5 | "His hands came up at" | | 6 | "Her shoulder hit the nearer" | | 7 | "She kept running." | | 8 | "He cut left past bins" | | 9 | "His voice floated back, thin" | | 10 | "He knocked a crate into" | | 11 | "It spun and smacked the" | | 12 | "He looked back." | | 13 | "He slipped on a patch" | | 14 | "He grinned without joy." | | 15 | "He kicked off the kerb" | | 16 | "She tracked the sway of" | | 17 | "He veered past a woman" | | 18 | "He took the stairs three" | | 19 | "He vanished into the Northern" |
| | ratio | 0.408 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 175 | | totalSentences | 184 | | matches | | 0 | "The green neon over the" | | 1 | "Harlow watched from the shadow" | | 2 | "Her worn leather watch ticked" | | 3 | "She touched the inside pocket" | | 4 | "The Raven’s Nest spilled laughter" | | 5 | "The maps on the walls" | | 6 | "She’d stared at them on" | | 7 | "Tonight wasn’t for drinking." | | 8 | "A tall man ducked out" | | 9 | "He moved like he scanned" | | 10 | "The Saint Christopher medallion flashed" | | 11 | "Tomás Herrera kept his face" | | 12 | "He didn’t turn." | | 13 | "His hands came up at" | | 14 | "Bouncers in black stepped off" | | 15 | "Her shoulder hit the nearer" | | 16 | "She kept running." | | 17 | "Rain made the cobbles shine." | | 18 | "Herrera’s trainers struck water and" | | 19 | "He cut left past bins" |
| | ratio | 0.951 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 184 | | matches | (empty) | | ratio | 0 | |
| 99.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 99 | | technicalSentenceCount | 6 | | matches | | 0 | "Herrera stood three carriages down, separated by glass and the reflection of a woman’s face that looked older than the one in her passport." | | 1 | "He had a cut along his forearm, puckered scar tissue that didn’t care for the light." | | 2 | "Forearms like tree trunks under tattoos that had been done under different lights by different hands." | | 3 | "A woman’s silhouette slid up beside the gatekeeper, draped in cloth that didn’t want to hold a colour under the arch’s shadow." | | 4 | "Spitalfields dealers buying powders that made you see a world that looked back." | | 5 | "Tomás’s face in triage rooms, in back alleys, in front of pubs, passing a bag to someone who looked like a ghost trying to remember how to stand up." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 63 | | tagDensity | 0.032 | | leniency | 0.063 | | rawRatio | 0 | | effectiveRatio | 0 | |