| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 91.50% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1764 | | totalAiIsmAdverbs | 3 | | found | | 0 | | adverb | "deliberately" | | count | 1 |
| | 1 | |
| | 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) | |
| 40.48% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1764 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "weight" | | 1 | "fractured" | | 2 | "unspoken" | | 3 | "silence" | | 4 | "structure" | | 5 | "unravel" | | 6 | "throbbed" | | 7 | "traced" | | 8 | "trembled" | | 9 | "could feel" | | 10 | "flickered" | | 11 | "familiar" |
| |
| 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 | 175 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 175 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 175 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1764 | | ratio | 0 | | matches | (empty) | |
| 48.08% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 4 | | matches | | 0 | "Cardiff feels like a city they let you borrow for a decade, she said finally." | | 1 | "I left London once, she said." | | 2 | "I miss the version of me that thought intelligence was a shield, she said quietly." | | 3 | "The certainty of being right, he said finally." |
| |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 1764 | | uniqueNames | 13 | | maxNameDensity | 0.68 | | worstName | "You" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 2 | | West | 1 | | End | 1 | | Prague | 4 | | Evan | 3 | | London | 2 | | Aurora | 8 | | Silas | 5 | | Bristol | 1 | | Eva | 1 | | You | 12 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Evan" | | 3 | "Aurora" | | 4 | "Silas" | | 5 | "Eva" | | 6 | "You" |
| | places | | 0 | "Soho" | | 1 | "West" | | 2 | "End" | | 3 | "Prague" | | 4 | "London" | | 5 | "Bristol" |
| | globalScore | 1 | | windowScore | 1 | |
| 83.63% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 113 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like a man who had spent a decade" | | 1 | "felt like to not be bracing for the nex" | | 2 | "sounded like a man stating the weather" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.567 | | wordCount | 1764 | | matches | | 0 | "not from shock, but from the sheer, unvarnished weight of recognition" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 175 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 44.1 | | std | 35.3 | | cv | 0.8 | | sampleLengths | | 0 | 86 | | 1 | 134 | | 2 | 80 | | 3 | 43 | | 4 | 1 | | 5 | 61 | | 6 | 21 | | 7 | 53 | | 8 | 20 | | 9 | 84 | | 10 | 47 | | 11 | 35 | | 12 | 19 | | 13 | 54 | | 14 | 57 | | 15 | 1 | | 16 | 74 | | 17 | 32 | | 18 | 82 | | 19 | 5 | | 20 | 5 | | 21 | 11 | | 22 | 86 | | 23 | 43 | | 24 | 46 | | 25 | 7 | | 26 | 27 | | 27 | 144 | | 28 | 28 | | 29 | 36 | | 30 | 69 | | 31 | 12 | | 32 | 21 | | 33 | 7 | | 34 | 78 | | 35 | 21 | | 36 | 15 | | 37 | 12 | | 38 | 13 | | 39 | 94 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 175 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 333 | | matches | | 0 | "were tracking" | | 1 | "was simply seeking" | | 2 | "was turning" | | 3 | "was holding" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 175 | | ratio | 0 | | matches | (empty) | |
| 98.91% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1770 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 73 | | adverbRatio | 0.04124293785310734 | | lyAdverbCount | 18 | | lyAdverbRatio | 0.010169491525423728 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 175 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 175 | | mean | 10.08 | | std | 7.7 | | cv | 0.764 | | sampleLengths | | 0 | 16 | | 1 | 13 | | 2 | 6 | | 3 | 33 | | 4 | 14 | | 5 | 4 | | 6 | 21 | | 7 | 24 | | 8 | 23 | | 9 | 36 | | 10 | 10 | | 11 | 3 | | 12 | 17 | | 13 | 14 | | 14 | 9 | | 15 | 36 | | 16 | 21 | | 17 | 3 | | 18 | 20 | | 19 | 3 | | 20 | 17 | | 21 | 1 | | 22 | 10 | | 23 | 16 | | 24 | 26 | | 25 | 4 | | 26 | 5 | | 27 | 4 | | 28 | 17 | | 29 | 13 | | 30 | 16 | | 31 | 11 | | 32 | 8 | | 33 | 5 | | 34 | 10 | | 35 | 3 | | 36 | 3 | | 37 | 4 | | 38 | 21 | | 39 | 5 | | 40 | 5 | | 41 | 13 | | 42 | 9 | | 43 | 3 | | 44 | 19 | | 45 | 9 | | 46 | 15 | | 47 | 7 | | 48 | 15 | | 49 | 10 |
| |
| 36.86% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 23 | | diversityRatio | 0.24 | | totalSentences | 175 | | uniqueOpeners | 42 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 165 | | matches | | 0 | "Then she saw him." | | 1 | "Sometimes until they snap." | | 2 | "Just to Bristol." | | 3 | "Somewhere behind the bar, a" | | 4 | "Just don’t drop anything." |
| | ratio | 0.03 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 97 | | totalSentences | 165 | | matches | | 0 | "She hadn’t planned to come" | | 1 | "Her boots were tracking cold" | | 2 | "She was simply seeking dry" | | 3 | "He sat at the far" | | 4 | "He was turning a tumbler" | | 5 | "His hair had grown longer," | | 6 | "He looked older." | | 7 | "He looked like a man" | | 8 | "They hadn’t seen each other" | | 9 | "He looked up." | | 10 | "His gaze traveled over her" | | 11 | "He didn’t smile." | | 12 | "He just nodded, a slow," | | 13 | "Her name was Aurora now," | | 14 | "He had watched it unravel." | | 15 | "You’re taller, he said." | | 16 | "His voice was lower than" | | 17 | "Her left wrist throbbed faintly," | | 18 | "She kept her fingers curled" | | 19 | "I’ve just grown into my" |
| | ratio | 0.588 | |
| 41.82% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 138 | | totalSentences | 165 | | matches | | 0 | "The green neon of The" | | 1 | "Aurora pushed through the heavy" | | 2 | "She hadn’t planned to come" | | 3 | "Her boots were tracking cold" | | 4 | "She was simply seeking dry" | | 5 | "He sat at the far" | | 6 | "He was turning a tumbler" | | 7 | "His hair had grown longer," | | 8 | "The slight limp in his" | | 9 | "He looked older." | | 10 | "He looked like a man" | | 11 | "Aurora’s breath caught, not from" | | 12 | "They hadn’t seen each other" | | 13 | "Life had pulled them in" | | 14 | "He looked up." | | 15 | "His gaze traveled over her" | | 16 | "He didn’t smile." | | 17 | "He just nodded, a slow," | | 18 | "The old nickname slipped out" | | 19 | "Her name was Aurora now," |
| | ratio | 0.836 | |
| 90.91% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 165 | | matches | | 0 | "Now I think about things" | | 1 | "To bad weather, then." | | 2 | "To bad weather." |
| | ratio | 0.018 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 72 | | technicalSentenceCount | 6 | | matches | | 0 | "Her boots were tracking cold river water across the threshold, her shoulders aching from another circuit through the West End alleys, the insulated bag still st…" | | 1 | "The slight limp in his left leg, born of a Prague misstep that had never fully healed, was more pronounced in the way he distributed his weight, favoring the ri…" | | 2 | "He just nodded, a slow, deliberate motion that carried the gravity of a man acknowledging a ghost." | | 3 | "I thought if I kept moving, if I kept running routes and delivering food and paying rent above a man who knew how to keep his doors locked, I could outrun the m…" | | 4 | "I thought I’d have a bookshelf full of precedents and a quiet office with a window that faced something other than a brick wall." | | 5 | "She could see the hidden door behind the bookshelf in her mind’s eye, the mechanism that had kept secrets for decades before it kept hers." |
| |
| 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 | |