| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 93.21% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2210 | | 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) | |
| 57.01% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2210 | | totalAiIsms | 19 | | found | | | highlights | | 0 | "echoed" | | 1 | "footsteps" | | 2 | "velvet" | | 3 | "etched" | | 4 | "aligned" | | 5 | "measured" | | 6 | "etching" | | 7 | "warmth" | | 8 | "weight" | | 9 | "standard" | | 10 | "chaotic" | | 11 | "aftermath" | | 12 | "structure" | | 13 | "pulse" |
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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 | 174 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 174 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 185 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2210 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 97.13% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1986 | | uniqueNames | 9 | | maxNameDensity | 1.06 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 21 | | Tube | 1 | | Camden | 1 | | Veil | 2 | | Market | 1 | | Kowalski | 1 | | Compass | 1 | | Eva | 10 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Kowalski" | | 4 | "Compass" | | 5 | "Eva" |
| | places | (empty) | | globalScore | 0.971 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 161 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared pale under the emergency lights" |
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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 | 2210 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 185 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 79 | | mean | 27.97 | | std | 15.84 | | cv | 0.566 | | sampleLengths | | 0 | 55 | | 1 | 80 | | 2 | 44 | | 3 | 61 | | 4 | 37 | | 5 | 48 | | 6 | 18 | | 7 | 9 | | 8 | 25 | | 9 | 47 | | 10 | 35 | | 11 | 14 | | 12 | 15 | | 13 | 24 | | 14 | 44 | | 15 | 32 | | 16 | 46 | | 17 | 24 | | 18 | 17 | | 19 | 10 | | 20 | 25 | | 21 | 46 | | 22 | 34 | | 23 | 27 | | 24 | 36 | | 25 | 5 | | 26 | 22 | | 27 | 43 | | 28 | 28 | | 29 | 17 | | 30 | 38 | | 31 | 48 | | 32 | 29 | | 33 | 7 | | 34 | 21 | | 35 | 22 | | 36 | 19 | | 37 | 50 | | 38 | 34 | | 39 | 27 | | 40 | 11 | | 41 | 18 | | 42 | 18 | | 43 | 25 | | 44 | 9 | | 45 | 17 | | 46 | 55 | | 47 | 14 | | 48 | 17 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 174 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 298 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 185 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1986 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 53 | | adverbRatio | 0.026686807653575024 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.006545820745216516 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 185 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 185 | | mean | 11.95 | | std | 5.09 | | cv | 0.426 | | sampleLengths | | 0 | 16 | | 1 | 10 | | 2 | 4 | | 3 | 25 | | 4 | 5 | | 5 | 12 | | 6 | 8 | | 7 | 18 | | 8 | 11 | | 9 | 9 | | 10 | 17 | | 11 | 4 | | 12 | 10 | | 13 | 12 | | 14 | 9 | | 15 | 9 | | 16 | 6 | | 17 | 17 | | 18 | 4 | | 19 | 7 | | 20 | 12 | | 21 | 7 | | 22 | 8 | | 23 | 14 | | 24 | 4 | | 25 | 6 | | 26 | 13 | | 27 | 9 | | 28 | 14 | | 29 | 16 | | 30 | 9 | | 31 | 6 | | 32 | 12 | | 33 | 9 | | 34 | 25 | | 35 | 6 | | 36 | 10 | | 37 | 18 | | 38 | 13 | | 39 | 6 | | 40 | 8 | | 41 | 6 | | 42 | 15 | | 43 | 14 | | 44 | 3 | | 45 | 12 | | 46 | 24 | | 47 | 2 | | 48 | 5 | | 49 | 14 |
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| 31.08% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 35 | | diversityRatio | 0.1837837837837838 | | totalSentences | 185 | | uniqueOpeners | 34 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 172 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 41 | | totalSentences | 172 | | matches | | 0 | "She heard the click as" | | 1 | "She passed through into the" | | 2 | "Her boots landed on the" | | 3 | "She paused to adjust the" | | 4 | "She checked it against the" | | 5 | "She held a notebook in" | | 6 | "Her curly red hair framed" | | 7 | "Her freckled complexion appeared pale" | | 8 | "She avoided the larger pools" | | 9 | "She crouched to bring her" | | 10 | "She checked the skin for" | | 11 | "She lowered the arm back" | | 12 | "She tucked one curl of" | | 13 | "She surveyed the immediate area." | | 14 | "She moved to the next" | | 15 | "Their pages fanned open from" | | 16 | "She slipped the Veil Compass" | | 17 | "She counted the sizes and" | | 18 | "She followed that set of" | | 19 | "They stopped at the wall" |
| | ratio | 0.238 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 160 | | totalSentences | 172 | | matches | | 0 | "Detective Harlow Quinn pressed the" | | 1 | "She heard the click as" | | 2 | "The panel slid aside." | | 3 | "She passed through into the" | | 4 | "The descent took several minutes." | | 5 | "Each step echoed upward before" | | 6 | "Another listed train schedules that" | | 7 | "Water stains ran in vertical" | | 8 | "The air smelled of mold" | | 9 | "Quinn reached the bottom." | | 10 | "Her boots landed on the" | | 11 | "She paused to adjust the" | | 12 | "The dial showed the current" | | 13 | "She checked it against the" | | 14 | "The platform stretched out before" | | 15 | "The Veil Market had transformed" | | 16 | "Fabric hung in tatters over" | | 17 | "Some liquids still moved within" | | 18 | "Others had dried into crusts" | | 19 | "A figure lay on the" |
| | ratio | 0.93 | |
| 29.07% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 172 | | matches | | 0 | "Now most lay overturned." |
| | ratio | 0.006 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 106 | | technicalSentenceCount | 5 | | matches | | 0 | "She passed through into the damp air of the abandoned Tube station beneath Camden and descended the metal stairs that led to the lower platform." | | 1 | "One showed an advertisement for a 1960s film festival with faded colors that hinted at red and yellow." | | 2 | "Her curly red hair framed her face under the round glasses that sat on her nose." | | 3 | "The path and tracks suggested movement that did not match physical limitations of the location." | | 4 | "The dark archway frame emitted a low vibration that matched the pulse under her palm on the hand print." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |