| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 88.36% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1289 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "suddenly" | | 1 | "really" | | 2 | "very" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 53.45% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1289 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "familiar" | | 1 | "glint" | | 2 | "echoed" | | 3 | "weight" | | 4 | "pulse" | | 5 | "silence" | | 6 | "traced" | | 7 | "unspoken" | | 8 | "echo" |
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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 | 128 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 128 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 128 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1289 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 1289 | | uniqueNames | 18 | | maxNameDensity | 0.7 | | worstName | "You" | | maxWindowNameDensity | 1.5 | | worstWindowName | "You" | | discoveredNames | | Aurora | 4 | | Raven | 2 | | Nest | 3 | | Soho | 1 | | Dad | 2 | | Cardiff | 2 | | Evan | 2 | | Brendan | 1 | | Carter | 1 | | Prague | 3 | | London | 1 | | Silas | 6 | | Yu-Fei | 1 | | Golden | 1 | | Empress | 1 | | Spymaster | 1 | | Rory | 2 | | You | 9 |
| | persons | | 0 | "Aurora" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Dad" | | 4 | "Evan" | | 5 | "Brendan" | | 6 | "Carter" | | 7 | "Silas" | | 8 | "Spymaster" | | 9 | "Rory" | | 10 | "You" |
| | places | | 0 | "Soho" | | 1 | "Cardiff" | | 2 | "Prague" | | 3 | "London" | | 4 | "Golden" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 91 | | 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 | 1289 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 128 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 26 | | mean | 49.58 | | std | 31.68 | | cv | 0.639 | | sampleLengths | | 0 | 68 | | 1 | 79 | | 2 | 1 | | 3 | 20 | | 4 | 25 | | 5 | 19 | | 6 | 26 | | 7 | 57 | | 8 | 36 | | 9 | 81 | | 10 | 22 | | 11 | 73 | | 12 | 16 | | 13 | 21 | | 14 | 95 | | 15 | 24 | | 16 | 102 | | 17 | 36 | | 18 | 97 | | 19 | 30 | | 20 | 116 | | 21 | 32 | | 22 | 89 | | 23 | 39 | | 24 | 55 | | 25 | 30 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 128 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 233 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 128 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1297 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 41 | | adverbRatio | 0.03161141094834233 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.004626060138781804 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 128 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 128 | | mean | 10.07 | | std | 6.8 | | cv | 0.675 | | sampleLengths | | 0 | 21 | | 1 | 22 | | 2 | 7 | | 3 | 18 | | 4 | 13 | | 5 | 25 | | 6 | 10 | | 7 | 17 | | 8 | 14 | | 9 | 1 | | 10 | 5 | | 11 | 15 | | 12 | 12 | | 13 | 13 | | 14 | 1 | | 15 | 7 | | 16 | 11 | | 17 | 17 | | 18 | 9 | | 19 | 2 | | 20 | 1 | | 21 | 10 | | 22 | 9 | | 23 | 4 | | 24 | 19 | | 25 | 12 | | 26 | 4 | | 27 | 7 | | 28 | 25 | | 29 | 1 | | 30 | 6 | | 31 | 21 | | 32 | 6 | | 33 | 7 | | 34 | 9 | | 35 | 7 | | 36 | 9 | | 37 | 15 | | 38 | 7 | | 39 | 6 | | 40 | 9 | | 41 | 1 | | 42 | 5 | | 43 | 12 | | 44 | 2 | | 45 | 6 | | 46 | 7 | | 47 | 7 | | 48 | 10 | | 49 | 6 |
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| 76.04% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.4609375 | | totalSentences | 128 | | uniqueOpeners | 59 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 110 | | matches | | 0 | "Then Evan started calling again" | | 1 | "Then you left without a" | | 2 | "Instead I turned into this." | | 3 | "Neatly trimmed beard and all." | | 4 | "Instead it became a museum" | | 5 | "Instead I find you here," | | 6 | "Instead the constants became these" |
| | ratio | 0.064 | |
| 85.45% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 110 | | matches | | 0 | "His frame filled the space" | | 1 | "He set the rag down." | | 2 | "She crossed to the bar" | | 3 | "Her straight black hair fell" | | 4 | "He reached for a bottle" | | 5 | "You vanished after that delivery" | | 6 | "She flexed her left wrist" | | 7 | "You listened to all of" | | 8 | "You handed me the keys" | | 9 | "His beard twitched as his" | | 10 | "I watched you dodge the" | | 11 | "I kept the lights on" | | 12 | "He shifted his stance." | | 13 | "You used to talk about" | | 14 | "I came back through London" | | 15 | "His fingers drummed once against" | | 16 | "You built walls after Evan." | | 17 | "I saw them go up" | | 18 | "You walk in tonight and" | | 19 | "She leaned forward." |
| | ratio | 0.336 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 76 | | totalSentences | 110 | | matches | | 0 | "The green neon sign cast" | | 1 | "Maps with faded creases covered" | | 2 | "Silas stood behind the counter," | | 3 | "His frame filled the space" | | 4 | "Strands of grey wove through" | | 5 | "The limp in his left" | | 6 | "He set the rag down." | | 7 | "The silver signet ring on" | | 8 | "She crossed to the bar" | | 9 | "Her straight black hair fell" | | 10 | "He reached for a bottle" | | 11 | "This stool still holds the" | | 12 | "You vanished after that delivery" | | 13 | "The girl who crashed in" | | 14 | "Aurora lifted the glass." | | 15 | "The whiskey burned a clean" | | 16 | "She flexed her left wrist" | | 17 | "Pre-law books stacked in that" | | 18 | "You listened to all of" | | 19 | "Eva pulled me deeper into" |
| | ratio | 0.691 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 110 | | matches | | 0 | "Now you stand like the" | | 1 | "Now I walk these streets" | | 2 | "Now I bend less." |
| | ratio | 0.027 | |
| 80.20% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 57 | | technicalSentenceCount | 5 | | matches | | 0 | "Black-and-white photographs captured faces from decades past, eyes that stared out as if they still judged the living." | | 1 | "The girl who crashed in the flat upstairs used to burst in here with wild theories and half-formed plans." | | 2 | "The amber liquid caught reflections of the wall maps, routes that led nowhere anymore." | | 3 | "You were the closest thing to family that walked through that door after my own blood stopped answering calls." | | 4 | "The girl who fled Cardiff with fire in her veins now measures every word." |
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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 | |