| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.357 | | leniency | 0.714 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.20% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1784 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 38.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1784 | | totalAiIsms | 22 | | found | | | highlights | | 0 | "weight" | | 1 | "unspoken" | | 2 | "output" | | 3 | "ensure" | | 4 | "tension" | | 5 | "resolve" | | 6 | "measured" | | 7 | "chill" | | 8 | "footsteps" | | 9 | "scanned" | | 10 | "warmth" | | 11 | "crystal" | | 12 | "silence" | | 13 | "flickered" |
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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 | 309 | | matches | (empty) | |
| 96.63% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 6 | | hedgeCount | 4 | | narrationSentences | 309 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 309 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 37 | | markdownWords | 53 | | totalWords | 1825 | | ratio | 0.029 | | matches | | 0 | "Analyze the Request:" | | 1 | "Role:" | | 2 | "Rules:" | | 3 | "Constraints:" | | 4 | "Length:" | | 5 | "Genre:" | | 6 | "Plot:" | | 7 | "Codex:" | | 8 | "Output:" | | 9 | "Character & Setting Integration:" | | 10 | "Protagonist:" | | 11 | "Setting:" | | 12 | "Conflict:" | | 13 | "Challenge:" | | 14 | "New Character:" | | 15 | "Change:" | | 16 | "Drafting Plan:" | | 17 | "Word Count:" | | 18 | "Style:" | | 19 | "Dialogue:" | | 20 | "Ending:" | | 21 | "Spelling:" | | 22 | "Formatting:" | | 23 | "Step-by-Step Writing:" | | 24 | "Opening:" | | 25 | "Inciting Incident:" | | 26 | "Interaction:" | | 27 | "Silas:" | | 28 | "Tension:" | | 29 | "Ending:" | | 30 | "Constraint Checklist:" | | 31 | "Writing Phase:" | | 32 | "(Self-Correction during drafting)" | | 33 | "(Self-Correction)" | | 34 | "(Self-Correction)" | | 35 | "(Self-Correction)" | | 36 | "(Let's start writing.)" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 148 | | wordCount | 1772 | | uniqueNames | 41 | | maxNameDensity | 1.75 | | worstName | "Julian" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Julian" | | discoveredNames | | Process | 1 | | Expert | 1 | | Past | 2 | | General | 1 | | English | 2 | | Literary | 2 | | Two | 1 | | Use | 1 | | Aurora | 18 | | Carter | 2 | | Rory | 4 | | Silas | 19 | | Blackwood | 1 | | Raven | 5 | | Nest | 5 | | Prose | 1 | | Setting | 2 | | Soho | 2 | | Unexpected | 1 | | Julian | 31 | | Cardiff | 4 | | University | 2 | | Aim | 1 | | Sharp | 1 | | Stop | 1 | | Dialogue | 3 | | Establish | 1 | | Mention | 1 | | Unspoken | 1 | | Spelling | 2 | | Active | 1 | | Show | 1 | | Word | 3 | | Codex | 2 | | Focus | 2 | | Ensure | 1 | | Check | 2 | | Wait | 2 | | Remove | 1 | | London | 2 | | You | 12 |
| | persons | | 0 | "Past" | | 1 | "Aurora" | | 2 | "Carter" | | 3 | "Rory" | | 4 | "Silas" | | 5 | "Blackwood" | | 6 | "Raven" | | 7 | "Julian" | | 8 | "Unspoken" | | 9 | "Show" | | 10 | "Codex" | | 11 | "You" |
| | places | | 0 | "Soho" | | 1 | "Cardiff" | | 2 | "University" | | 3 | "Dialogue" | | 4 | "Ensure" | | 5 | "London" |
| | globalScore | 0.625 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 123 | | 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 | 1825 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 309 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 143 | | mean | 12.76 | | std | 21.03 | | cv | 1.648 | | sampleLengths | | 0 | 2 | | 1 | 119 | | 2 | 148 | | 3 | 57 | | 4 | 70 | | 5 | 76 | | 6 | 35 | | 7 | 83 | | 8 | 84 | | 9 | 64 | | 10 | 44 | | 11 | 46 | | 12 | 1 | | 13 | 42 | | 14 | 8 | | 15 | 11 | | 16 | 11 | | 17 | 1 | | 18 | 13 | | 19 | 1 | | 20 | 24 | | 21 | 4 | | 22 | 12 | | 23 | 5 | | 24 | 9 | | 25 | 16 | | 26 | 30 | | 27 | 4 | | 28 | 5 | | 29 | 2 | | 30 | 25 | | 31 | 3 | | 32 | 3 | | 33 | 11 | | 34 | 5 | | 35 | 2 | | 36 | 1 | | 37 | 13 | | 38 | 5 | | 39 | 4 | | 40 | 8 | | 41 | 7 | | 42 | 2 | | 43 | 2 | | 44 | 4 | | 45 | 11 | | 46 | 10 | | 47 | 3 | | 48 | 3 | | 49 | 12 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 309 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 337 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 1 | | totalSentences | 309 | | ratio | 0.003 | | matches | | 0 | "(Aurora's scar, eyes, hair; Silas's ring, limp; Raven's Nest sign)." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1738 | | adjectiveStacks | 2 | | stackExamples | | 0 | "small crescent-shaped scar" | | 1 | "outside washed over her" |
| | adverbCount | 31 | | adverbRatio | 0.017836593785960874 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.00805523590333717 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 309 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 309 | | mean | 5.91 | | std | 4.36 | | cv | 0.739 | | sampleLengths | | 0 | 2 | | 1 | 1 | | 2 | 3 | | 3 | 5 | | 4 | 39 | | 5 | 20 | | 6 | 6 | | 7 | 4 | | 8 | 13 | | 9 | 4 | | 10 | 7 | | 11 | 11 | | 12 | 6 | | 13 | 1 | | 14 | 4 | | 15 | 5 | | 16 | 11 | | 17 | 12 | | 18 | 8 | | 19 | 9 | | 20 | 10 | | 21 | 8 | | 22 | 32 | | 23 | 16 | | 24 | 4 | | 25 | 5 | | 26 | 2 | | 27 | 6 | | 28 | 5 | | 29 | 10 | | 30 | 1 | | 31 | 2 | | 32 | 10 | | 33 | 9 | | 34 | 8 | | 35 | 10 | | 36 | 8 | | 37 | 6 | | 38 | 3 | | 39 | 1 | | 40 | 2 | | 41 | 8 | | 42 | 11 | | 43 | 5 | | 44 | 1 | | 45 | 4 | | 46 | 7 | | 47 | 11 | | 48 | 7 | | 49 | 13 |
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| 39.77% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 31 | | diversityRatio | 0.297029702970297 | | totalSentences | 303 | | uniqueOpeners | 90 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 263 | | matches | (empty) | | ratio | 0 | |
| 51.18% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 111 | | totalSentences | 263 | | matches | | 0 | "I must introduce a new" | | 1 | "I will ensure Silas is" | | 2 | "I will use actions like" | | 3 | "I need to expand descriptions" | | 4 | "I will describe the bar's" | | 5 | "She loosened the strap of" | | 6 | "He moved with a slight" | | 7 | "His grey-streaked auburn hair caught" | | 8 | "He did not look up" | | 9 | "He knew her schedule." | | 10 | "He knew the rhythm of" | | 11 | "She sat and rubbed her" | | 12 | "She watched the door." | | 13 | "He wore a tailored coat" | | 14 | "He scanned the room, his" | | 15 | "He stopped when he saw" | | 16 | "He looked different." | | 17 | "His hair was cut short" | | 18 | "His face held the sharp" | | 19 | "He walked toward her table," |
| | ratio | 0.422 | |
| 70.27% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 205 | | totalSentences | 263 | | matches | | 0 | "* **Plot:** Two old friends" | | 1 | "**Character & Setting Integration:**" | | 2 | "Silas is her mentor and" | | 3 | "An meeting with Silas contradicts" | | 4 | "I must introduce a new" | | 5 | "I will ensure Silas is" | | 6 | "Rory is a delivery girl." | | 7 | "The contrast highlights the" | | 8 | "* **Word Count:** Aim for" | | 9 | "Aurora is there (maybe finishing" | | 10 | "The contrast in their lives" | | 11 | "* UK Spelling?" | | 12 | "* Dialogue on own paragraph?" | | 13 | "* Word count > 1000?" | | 14 | "* Codex details used?" | | 15 | "(Aurora's scar, eyes, hair; Silas's" | | 16 | "*(Self-Correction during drafting)*: I need" | | 17 | "I will use actions like" | | 18 | "-> (Wait, is also uncertainty" | | 19 | "-> or just describe the" |
| | ratio | 0.779 | |
| 38.02% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 263 | | matches | | 0 | "Now I deliver food." | | 1 | "To find you." |
| | ratio | 0.008 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 2 | | matches | | 0 | "Silas stood behind the bar, polishing a glass with a rag that had seen better decades." | | 1 | "He watched the interaction with the calm detachment of a man who had seen too many endings." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |