| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "He knocked back [back]" | | 1 | "He gestured vaguely [vaguely]" |
| | dialogueSentences | 55 | | tagDensity | 0.236 | | leniency | 0.473 | | rawRatio | 0.154 | | effectiveRatio | 0.073 | |
| 85.26% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1357 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "very" | | 1 | "utterly" | | 2 | "really" |
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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) | |
| 63.15% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1357 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "shattered" | | 1 | "predictable" | | 2 | "familiar" | | 3 | "eyebrow" | | 4 | "unspoken" | | 5 | "silence" | | 6 | "tension" | | 7 | "weight" | | 8 | "etched" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 100 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 100 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 140 | | 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 | 1352 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 56 | | wordCount | 953 | | uniqueNames | 7 | | maxNameDensity | 2.62 | | worstName | "Silas" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Silas" | | discoveredNames | | Silas | 25 | | Raven | 3 | | Nest | 3 | | Aurora | 9 | | Jonathan | 14 | | Charles | 1 | | Bridge | 1 |
| | persons | | 0 | "Silas" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Aurora" | | 4 | "Jonathan" |
| | places | | | globalScore | 0.188 | | windowScore | 0.167 | |
| 80.56% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 2 | | matches | | 0 | "way that seemed to cost him" | | 1 | "as if memorising the face of the bar owner, trying to find the ghost of the field agent" |
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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 | 1352 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 140 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 59 | | mean | 22.92 | | std | 17.53 | | cv | 0.765 | | sampleLengths | | 0 | 11 | | 1 | 3 | | 2 | 48 | | 3 | 23 | | 4 | 20 | | 5 | 33 | | 6 | 4 | | 7 | 2 | | 8 | 40 | | 9 | 54 | | 10 | 23 | | 11 | 5 | | 12 | 28 | | 13 | 4 | | 14 | 78 | | 15 | 11 | | 16 | 29 | | 17 | 43 | | 18 | 18 | | 19 | 27 | | 20 | 15 | | 21 | 7 | | 22 | 27 | | 23 | 7 | | 24 | 55 | | 25 | 10 | | 26 | 8 | | 27 | 28 | | 28 | 16 | | 29 | 23 | | 30 | 34 | | 31 | 49 | | 32 | 26 | | 33 | 5 | | 34 | 11 | | 35 | 5 | | 36 | 46 | | 37 | 30 | | 38 | 8 | | 39 | 2 | | 40 | 4 | | 41 | 24 | | 42 | 41 | | 43 | 12 | | 44 | 22 | | 45 | 2 | | 46 | 46 | | 47 | 16 | | 48 | 27 | | 49 | 45 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 100 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 159 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 140 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 958 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.030271398747390398 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.011482254697286013 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 140 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 140 | | mean | 9.66 | | std | 6.5 | | cv | 0.673 | | sampleLengths | | 0 | 11 | | 1 | 3 | | 2 | 17 | | 3 | 15 | | 4 | 16 | | 5 | 9 | | 6 | 7 | | 7 | 7 | | 8 | 13 | | 9 | 7 | | 10 | 13 | | 11 | 4 | | 12 | 3 | | 13 | 11 | | 14 | 2 | | 15 | 4 | | 16 | 2 | | 17 | 13 | | 18 | 16 | | 19 | 11 | | 20 | 9 | | 21 | 19 | | 22 | 11 | | 23 | 15 | | 24 | 10 | | 25 | 13 | | 26 | 5 | | 27 | 20 | | 28 | 3 | | 29 | 5 | | 30 | 3 | | 31 | 1 | | 32 | 18 | | 33 | 5 | | 34 | 2 | | 35 | 21 | | 36 | 15 | | 37 | 17 | | 38 | 8 | | 39 | 3 | | 40 | 10 | | 41 | 12 | | 42 | 7 | | 43 | 4 | | 44 | 10 | | 45 | 20 | | 46 | 9 | | 47 | 9 | | 48 | 9 | | 49 | 11 |
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| 48.81% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.35714285714285715 | | totalSentences | 140 | | uniqueOpeners | 50 | |
| 34.36% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 97 | | matches | | 0 | "Then, with a slow, deliberate" |
| | ratio | 0.01 | |
| 88.04% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 97 | | matches | | 0 | "His slight limp was more" | | 1 | "She said it without malice," | | 2 | "They’d moved past polite fictions" | | 3 | "He took the stairs slower" | | 4 | "She stopped in the shadowed" | | 5 | "His silver signet ring caught" | | 6 | "His hair, once the same" | | 7 | "He was a ghost from" | | 8 | "He pulled out a stool" | | 9 | "He reached for a bottle" | | 10 | "He knocked back the whiskey" | | 11 | "She saw the man Jonathan" | | 12 | "She could extrapolate the man" | | 13 | "He finally looked at Silas," | | 14 | "He gestured vaguely at the" | | 15 | "He was staring at a" | | 16 | "He looked old." | | 17 | "He stood up, the stool" | | 18 | "He reached into his coat" | | 19 | "He looked at Silas, really" |
| | ratio | 0.33 | |
| 6.39% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 88 | | totalSentences | 97 | | matches | | 0 | "The glass shattered against the" | | 1 | "Aurora wiped her hands on" | | 2 | "The basement training room under" | | 3 | "The dummy she’d just disarmed" | | 4 | "Silas picked a sliver of" | | 5 | "His slight limp was more" | | 6 | "She said it without malice," | | 7 | "They’d moved past polite fictions" | | 8 | "A specific cadence." | | 9 | "Silas’s hazel eyes sharpened, all" | | 10 | "He took the stairs slower" | | 11 | "Aurora gave him a thirty-second" | | 12 | "She stopped in the shadowed" | | 13 | "The Raven’s Nest was empty," | | 14 | "The green neon from the" | | 15 | "Silas stood behind the bar," | | 16 | "His silver signet ring caught" | | 17 | "A man stood before him," | | 18 | "The voice was a gravelly" | | 19 | "School rugby matches." |
| | ratio | 0.907 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 97 | | matches | | 0 | "Before he could retort, the" | | 1 | "Now it was a map" |
| | ratio | 0.021 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 1 | | matches | | 0 | "He just watched the clear water swirl around the empty glass, washing away the last trace of the man who had drunk from it, as if that could cleanse anything at…" |
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| 48.08% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 2 | | matches | | 0 | "Aurora wiped, the ghost of a smile on her lips" | | 1 | "Silas corrected, his voice flat" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "Silas corrected (correct)" |
| | dialogueSentences | 55 | | tagDensity | 0.055 | | leniency | 0.109 | | rawRatio | 0.333 | | effectiveRatio | 0.036 | |