| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1377 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 38.27% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1377 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "fractured" | | 1 | "pulse" | | 2 | "traced" | | 3 | "throbbed" | | 4 | "weight" | | 5 | "silence" | | 6 | "aligned" | | 7 | "calculate" | | 8 | "navigate" | | 9 | "echoed" | | 10 | "pulsed" |
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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 | 209 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 5 | | hedgeCount | 0 | | narrationSentences | 209 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 209 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 22 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1377 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 1377 | | uniqueNames | 14 | | maxNameDensity | 1.89 | | worstName | "You" | | maxWindowNameDensity | 4.5 | | worstWindowName | "You" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | London | 2 | | Silas | 5 | | Prague | 1 | | Cardiff | 3 | | Edinburgh | 1 | | King | 1 | | Cross | 1 | | Brendan | 1 | | You | 26 | | Yu-Fei | 3 | | Don | 3 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "King" | | 4 | "Cross" | | 5 | "Brendan" | | 6 | "You" | | 7 | "Yu-Fei" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Prague" | | 3 | "Cardiff" | | 4 | "Edinburgh" |
| | globalScore | 0.556 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 107 | | 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 | 1377 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 209 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 78 | | mean | 17.65 | | std | 14.3 | | cv | 0.81 | | sampleLengths | | 0 | 112 | | 1 | 63 | | 2 | 6 | | 3 | 12 | | 4 | 12 | | 5 | 29 | | 6 | 13 | | 7 | 8 | | 8 | 14 | | 9 | 10 | | 10 | 13 | | 11 | 8 | | 12 | 17 | | 13 | 17 | | 14 | 6 | | 15 | 16 | | 16 | 26 | | 17 | 16 | | 18 | 22 | | 19 | 22 | | 20 | 7 | | 21 | 11 | | 22 | 18 | | 23 | 20 | | 24 | 29 | | 25 | 32 | | 26 | 10 | | 27 | 23 | | 28 | 5 | | 29 | 15 | | 30 | 12 | | 31 | 26 | | 32 | 10 | | 33 | 12 | | 34 | 22 | | 35 | 5 | | 36 | 22 | | 37 | 9 | | 38 | 26 | | 39 | 27 | | 40 | 3 | | 41 | 21 | | 42 | 30 | | 43 | 4 | | 44 | 25 | | 45 | 13 | | 46 | 14 | | 47 | 29 | | 48 | 7 | | 49 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 209 | | matches | | 0 | "being traced" | | 1 | "were supposed" |
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| 77.45% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 272 | | matches | | 0 | "was still stitching" | | 1 | "was looking" | | 2 | "were playing" | | 3 | "was learning" | | 4 | "were building" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 209 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1387 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.02090843547224225 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0007209805335255948 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 209 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 209 | | mean | 6.59 | | std | 3.93 | | cv | 0.596 | | sampleLengths | | 0 | 17 | | 1 | 15 | | 2 | 22 | | 3 | 12 | | 4 | 17 | | 5 | 14 | | 6 | 15 | | 7 | 15 | | 8 | 10 | | 9 | 11 | | 10 | 15 | | 11 | 12 | | 12 | 6 | | 13 | 5 | | 14 | 7 | | 15 | 5 | | 16 | 7 | | 17 | 15 | | 18 | 14 | | 19 | 1 | | 20 | 9 | | 21 | 3 | | 22 | 2 | | 23 | 6 | | 24 | 8 | | 25 | 6 | | 26 | 10 | | 27 | 4 | | 28 | 5 | | 29 | 4 | | 30 | 4 | | 31 | 4 | | 32 | 12 | | 33 | 4 | | 34 | 1 | | 35 | 5 | | 36 | 4 | | 37 | 6 | | 38 | 2 | | 39 | 1 | | 40 | 5 | | 41 | 16 | | 42 | 8 | | 43 | 6 | | 44 | 2 | | 45 | 10 | | 46 | 5 | | 47 | 11 | | 48 | 9 | | 49 | 1 |
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| 35.17% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 31 | | diversityRatio | 0.24880382775119617 | | totalSentences | 209 | | uniqueOpeners | 52 | |
| 35.65% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 187 | | matches | | 0 | "Once on paper." | | 1 | "Once on the street." |
| | ratio | 0.011 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 114 | | totalSentences | 187 | | matches | | 0 | "She pulled her coat tighter," | | 1 | "Her left wrist ached where" | | 2 | "His hazel eyes lifted over" | | 3 | "He set the cloth down," | | 4 | "You still drink the same" | | 5 | "It keeps the cold out." | | 6 | "I see you haven’t upgraded" | | 7 | "He moved to the far" | | 8 | "I didn’t expect to find" | | 9 | "I had to fold with" | | 10 | "She tracked the condensation pooling" | | 11 | "Her fingers traced the wooden" | | 12 | "You look like a ghost" | | 13 | "I live above the bookshelf." | | 14 | "You kept the place." | | 15 | "I kept the lock." | | 16 | "He poured a measure of" | | 17 | "I saw the postcard." | | 18 | "You crossed the water and" | | 19 | "She reached into her coat" |
| | ratio | 0.61 | |
| 2.78% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 171 | | totalSentences | 187 | | matches | | 0 | "The green neon sign buzzed" | | 1 | "Aurora pushed through the heavy" | | 2 | "The Raven’s Nest swallowed the" | | 3 | "Amber light caught the edges" | | 4 | "Maps covered the remaining plaster," | | 5 | "She pulled her coat tighter," | | 6 | "Her left wrist ached where" | | 7 | "Silas stood behind the polished" | | 8 | "His hazel eyes lifted over" | | 9 | "The grey-streaked auburn hair above" | | 10 | "He set the cloth down," | | 11 | "A slight limp carried his" | | 12 | "You still drink the same" | | 13 | "It keeps the cold out." | | 14 | "I see you haven’t upgraded" | | 15 | "The glasses hold the spirit." | | 16 | "The spirit doesn’t care about" | | 17 | "He moved to the far" | | 18 | "The neat trim of his" | | 19 | "I didn’t expect to find" |
| | ratio | 0.914 | |
| 26.74% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 187 | | matches | | | ratio | 0.005 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 1 | | matches | | 0 | "I work for a restaurant owner who ships fish at midnight." |
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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 | |