| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 2 | | adverbTags | | 0 | "The voice grated like [like]" | | 1 | "His fingers tightened around [around]" |
| | dialogueSentences | 17 | | tagDensity | 0.412 | | leniency | 0.824 | | rawRatio | 0.286 | | effectiveRatio | 0.235 | |
| 94.38% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 889 | | 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) | |
| 21.26% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 889 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "footsteps" | | 1 | "jaw clenched" | | 2 | "tracing" | | 3 | "depths" | | 4 | "echoed" | | 5 | "silence" | | 6 | "resolved" | | 7 | "hulking" | | 8 | "pulse" | | 9 | "glinting" | | 10 | "charm" | | 11 | "gleaming" | | 12 | "calculating" | | 13 | "chill" |
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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 | 62 | | matches | (empty) | |
| 96.77% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 62 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 72 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 892 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 71.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 766 | | uniqueNames | 14 | | maxNameDensity | 1.57 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 12 | | Underground | 1 | | Tube | 1 | | Transport | 1 | | London | 1 | | Civil | 1 | | War-era | 1 | | Morris | 1 | | Saint | 1 | | Christopher | 1 | | Herrera | 5 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Herrera" | | 6 | "Market" |
| | places | | | globalScore | 0.717 | | windowScore | 0.833 | |
| 63.79% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like a Civil War-era revolver" | | 1 | "looked like a cattle prod, and something" |
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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 | 892 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 72 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 27.88 | | std | 14.73 | | cv | 0.528 | | sampleLengths | | 0 | 41 | | 1 | 3 | | 2 | 43 | | 3 | 29 | | 4 | 7 | | 5 | 44 | | 6 | 47 | | 7 | 24 | | 8 | 9 | | 9 | 44 | | 10 | 49 | | 11 | 44 | | 12 | 7 | | 13 | 23 | | 14 | 40 | | 15 | 9 | | 16 | 48 | | 17 | 17 | | 18 | 12 | | 19 | 35 | | 20 | 11 | | 21 | 16 | | 22 | 28 | | 23 | 21 | | 24 | 37 | | 25 | 30 | | 26 | 47 | | 27 | 9 | | 28 | 19 | | 29 | 35 | | 30 | 44 | | 31 | 20 |
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| 99.60% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 62 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 126 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 72 | | ratio | 0.097 | | matches | | 0 | "Quinn unholstered her weapon but kept it lowered - she needed answers more than a body." | | 1 | "The peeling paint revealed faded Underground roundels beneath - this was no maintenance entrance." | | 2 | "She ducked instinctively, but no bullets whizzed past - the sounds had come from below." | | 3 | "Three others in the room immediately reached for weapons - a curved dagger, a taser made from what looked like a cattle prod, and something that hummed with unnatural energy." | | 4 | "Quinn recognized the stance - someone who'd killed before and wouldn't lose sleep over another body." | | 5 | "Quinn's boot scraped against something on the floor - a shard of mirror." | | 6 | "The Market's ambient noise rushed back in as she cleared the threshold - a dozen deals resumed as if the confrontation never happened." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 763 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.019659239842726082 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.007863695937090432 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 72 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 72 | | mean | 12.39 | | std | 6.02 | | cv | 0.486 | | sampleLengths | | 0 | 23 | | 1 | 18 | | 2 | 3 | | 3 | 11 | | 4 | 16 | | 5 | 16 | | 6 | 13 | | 7 | 16 | | 8 | 7 | | 9 | 14 | | 10 | 16 | | 11 | 14 | | 12 | 9 | | 13 | 17 | | 14 | 14 | | 15 | 7 | | 16 | 7 | | 17 | 15 | | 18 | 2 | | 19 | 9 | | 20 | 16 | | 21 | 17 | | 22 | 11 | | 23 | 11 | | 24 | 13 | | 25 | 10 | | 26 | 15 | | 27 | 9 | | 28 | 18 | | 29 | 17 | | 30 | 7 | | 31 | 10 | | 32 | 13 | | 33 | 8 | | 34 | 32 | | 35 | 9 | | 36 | 18 | | 37 | 30 | | 38 | 17 | | 39 | 6 | | 40 | 6 | | 41 | 17 | | 42 | 18 | | 43 | 4 | | 44 | 7 | | 45 | 11 | | 46 | 5 | | 47 | 12 | | 48 | 16 | | 49 | 12 |
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| 69.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.4444444444444444 | | totalSentences | 72 | | uniqueOpeners | 32 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 61 | | matches | | 0 | "Her salt-and-pepper hair clung to" | | 1 | "She rounded the corner just" | | 2 | "Her fingers tightened on her" | | 3 | "She ducked instinctively, but no" | | 4 | "She counted to three and" | | 5 | "Her shoulder bumped a stack" | | 6 | "His breath smelled of rotten" | | 7 | "She reached the fur curtain" | | 8 | "She exhaled slowly, calculating angles" | | 9 | "Her finger found the trigger" | | 10 | "He turned to Quinn, his" | | 11 | "His fingers tightened around the" | | 12 | "She backed toward the curtain," | | 13 | "She turned up her collar" |
| | ratio | 0.23 | |
| 17.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 61 | | matches | | 0 | "Rain lashed against Detective Harlow" | | 1 | "The suspect's dark silhouette darted" | | 2 | "The figure vaulted over a" | | 3 | "Quinn's sharp jaw clenched as" | | 4 | "Her salt-and-pepper hair clung to" | | 5 | "Quinn unholstered her weapon but" | | 6 | "The only response was the" | | 7 | "She rounded the corner just" | | 8 | "The peeling paint revealed faded" | | 9 | "Quinn hesitated at the threshold," | | 10 | "The door yawned open into" | | 11 | "Her fingers tightened on her" | | 12 | "She ducked instinctively, but no" | | 13 | "She counted to three and" | | 14 | "The stairs descended at a" | | 15 | "Quinn moved with deliberate silence," | | 16 | "The faint green glow at" | | 17 | "The abandoned Tube platform looked" | | 18 | "Patrons in hoods and masks" | | 19 | "A hulking figure by the" |
| | ratio | 0.885 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 1 | | matches | | 0 | "Three others in the room immediately reached for weapons - a curved dagger, a taser made from what looked like a cattle prod, and something that hummed with unn…" |
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| 53.57% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 1 | | matches | | 0 | "He turned, his dark brown eyes urgent" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |