| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 82.62% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 863 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 13.09% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 863 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "chill" | | 1 | "throb" | | 2 | "magnetic" | | 3 | "stomach" | | 4 | "calculate" | | 5 | "echoed" | | 6 | "pulse" | | 7 | "warmth" | | 8 | "rhythmic" | | 9 | "echo" | | 10 | "measured" | | 11 | "blown wide" | | 12 | "raced" | | 13 | "cataloged" | | 14 | "whisper" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
| | 1 | | label | "clenched jaw/fists" | | count | 1 |
|
| | highlights | | 0 | "stomach dropped" | | 1 | "clenched her jaw" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 192 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 192 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 192 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 19 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 863 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 9 | | wordCount | 863 | | uniqueNames | 6 | | maxNameDensity | 0.46 | | worstName | "Aurora" | | maxWindowNameDensity | 1 | | worstWindowName | "Aurora" | | discoveredNames | | Carter | 1 | | London | 1 | | Heartstone | 1 | | Richmond | 1 | | Park | 1 | | Aurora | 4 |
| | persons | | | places | | 0 | "London" | | 1 | "Richmond" | | 2 | "Park" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | 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 | 863 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 192 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 4 | | mean | 0 | | std | 0 | | cv | 0 | | sampleLengths | | |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 192 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 168 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 192 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 866 | | adjectiveStacks | 1 | | stackExamples | | 0 | "slow counter-clockwise rotation." |
| | adverbCount | 23 | | adverbRatio | 0.026558891454965358 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.004618937644341801 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 192 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 192 | | mean | 4.49 | | std | 3.24 | | cv | 0.721 | | sampleLengths | | 0 | 19 | | 1 | 10 | | 2 | 4 | | 3 | 16 | | 4 | 11 | | 5 | 7 | | 6 | 8 | | 7 | 8 | | 8 | 2 | | 9 | 1 | | 10 | 1 | | 11 | 5 | | 12 | 13 | | 13 | 16 | | 14 | 11 | | 15 | 4 | | 16 | 4 | | 17 | 15 | | 18 | 5 | | 19 | 3 | | 20 | 4 | | 21 | 14 | | 22 | 8 | | 23 | 3 | | 24 | 11 | | 25 | 10 | | 26 | 3 | | 27 | 3 | | 28 | 5 | | 29 | 9 | | 30 | 11 | | 31 | 6 | | 32 | 6 | | 33 | 10 | | 34 | 6 | | 35 | 5 | | 36 | 5 | | 37 | 3 | | 38 | 1 | | 39 | 8 | | 40 | 2 | | 41 | 3 | | 42 | 5 | | 43 | 8 | | 44 | 3 | | 45 | 3 | | 46 | 3 | | 47 | 4 | | 48 | 6 | | 49 | 2 |
| |
| 96.70% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.5989583333333334 | | totalSentences | 192 | | uniqueOpeners | 115 | |
| 95.92% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 139 | | matches | | 0 | "Instead, the ground yielded like" | | 1 | "Then reversed course, climbing back" | | 2 | "Then the sounds began." | | 3 | "Then the right." |
| | ratio | 0.029 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 139 | | matches | | 0 | "Her boots sank into turf" | | 1 | "She hooked two fingers under" | | 2 | "She had tracked this frequency" | | 3 | "She shoved the chain back" | | 4 | "It tightened now." | | 5 | "She walked forward." | | 6 | "They paused halfway." | | 7 | "Her stomach dropped." | | 8 | "She forced her shoulders back." | | 9 | "She counted the lack of" | | 10 | "It pressed against her eardrums." | | 11 | "She tapped the pendant." | | 12 | "She kept to the spaces" | | 13 | "She raised her hand." | | 14 | "She let it drop." | | 15 | "She braced her back against" | | 16 | "She jerked her hand away." | | 17 | "Her breathing sharpened." | | 18 | "She spoke into the stagnant" | | 19 | "Her voice cracked." |
| | ratio | 0.245 | |
| 96.69% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 101 | | totalSentences | 139 | | matches | | 0 | "The ancient oak stones rose" | | 1 | "Aurora Carter stepped between them" | | 2 | "The London chill vanished." | | 3 | "The air grew thick and" | | 4 | "Her boots sank into turf" | | 5 | "The Heartstone pendant against her" | | 6 | "A single throb traveled down" | | 7 | "She hooked two fingers under" | | 8 | "The stone held a captive" | | 9 | "She had tracked this frequency" | | 10 | "The reason waited somewhere deeper." | | 11 | "A portal leak." | | 12 | "A neighbor’s missing dog." | | 13 | "A tear in the veil" | | 14 | "She shoved the chain back" | | 15 | "The skin there always tightened" | | 16 | "It tightened now." | | 17 | "She walked forward." | | 18 | "The clearing opened without gradient." | | 19 | "The next, she stood beneath" |
| | ratio | 0.727 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 139 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 16 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | |