| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.73% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1527 | | totalAiIsmAdverbs | 1 | | 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) | |
| 31.24% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1527 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "pulse" | | 1 | "churn" | | 2 | "silence" | | 3 | "throb" | | 4 | "stomach" | | 5 | "weight" | | 6 | "scanning" | | 7 | "whisper" | | 8 | "footsteps" | | 9 | "footfall" | | 10 | "could feel" | | 11 | "flickered" | | 12 | "pulsed" | | 13 | "sense of" |
| |
| 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 | 187 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 187 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 188 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1519 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 1518 | | uniqueNames | 8 | | maxNameDensity | 0.66 | | worstName | "Aurora" | | maxWindowNameDensity | 1 | | worstWindowName | "Richmond" | | discoveredNames | | Richmond | 2 | | Park | 2 | | Heartstone | 1 | | Grove | 2 | | October | 1 | | Eva | 1 | | Aurora | 10 | | Laila | 1 |
| | persons | | 0 | "Heartstone" | | 1 | "Eva" | | 2 | "Aurora" | | 3 | "Laila" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Grove" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 108 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 2.50% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 1.975 | | wordCount | 1519 | | matches | | 0 | "not birdsong, but a whistle" | | 1 | "not in distance but in time" | | 2 | "not in a simple circle but in shapes" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 188 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 33.02 | | std | 20.64 | | cv | 0.625 | | sampleLengths | | 0 | 66 | | 1 | 34 | | 2 | 36 | | 3 | 13 | | 4 | 63 | | 5 | 51 | | 6 | 39 | | 7 | 29 | | 8 | 7 | | 9 | 83 | | 10 | 14 | | 11 | 25 | | 12 | 48 | | 13 | 12 | | 14 | 10 | | 15 | 28 | | 16 | 8 | | 17 | 11 | | 18 | 5 | | 19 | 34 | | 20 | 46 | | 21 | 46 | | 22 | 45 | | 23 | 16 | | 24 | 67 | | 25 | 50 | | 26 | 1 | | 27 | 39 | | 28 | 18 | | 29 | 43 | | 30 | 15 | | 31 | 47 | | 32 | 3 | | 33 | 28 | | 34 | 48 | | 35 | 65 | | 36 | 54 | | 37 | 59 | | 38 | 3 | | 39 | 9 | | 40 | 43 | | 41 | 28 | | 42 | 44 | | 43 | 39 | | 44 | 43 | | 45 | 4 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 187 | | matches | | 0 | "been carved" | | 1 | "was gone" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 245 | | matches | | 0 | "was going" | | 1 | "wasn’t laughing" | | 2 | "was correcting" |
| |
| 36.47% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 1 | | flaggedSentences | 7 | | totalSentences | 188 | | ratio | 0.037 | | matches | | 0 | "London’s constant hum—distant sirens, buses, the low churn of the city—cut off the moment she passed the fence line." | | 1 | "One moment there was a wall of brambles; the next, the brambles simply weren’t there." | | 2 | "Between them wildflowers covered the ground in thick clusters—foxglove, stitchwort, bluebells—all blooming out of season, all with their petals closed tight." | | 3 | "A sound came from the trees—not birdsong, but a whistle." | | 4 | "A small shape, grey like a fox but wrong—too many legs, or legs too long." | | 5 | "Frost spread from the centre outward, not in a simple circle but in shapes—letters?" | | 6 | "That was what she told herself—porous wood expanding and contracting." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1527 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 49 | | adverbRatio | 0.032089063523248196 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.0091683038637852 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 188 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 188 | | mean | 8.08 | | std | 5.66 | | cv | 0.701 | | sampleLengths | | 0 | 15 | | 1 | 8 | | 2 | 25 | | 3 | 18 | | 4 | 5 | | 5 | 19 | | 6 | 2 | | 7 | 8 | | 8 | 2 | | 9 | 7 | | 10 | 19 | | 11 | 8 | | 12 | 5 | | 13 | 8 | | 14 | 10 | | 15 | 19 | | 16 | 9 | | 17 | 16 | | 18 | 9 | | 19 | 16 | | 20 | 5 | | 21 | 20 | | 22 | 6 | | 23 | 4 | | 24 | 10 | | 25 | 5 | | 26 | 3 | | 27 | 17 | | 28 | 4 | | 29 | 4 | | 30 | 4 | | 31 | 3 | | 32 | 5 | | 33 | 13 | | 34 | 7 | | 35 | 6 | | 36 | 15 | | 37 | 5 | | 38 | 5 | | 39 | 3 | | 40 | 14 | | 41 | 14 | | 42 | 21 | | 43 | 2 | | 44 | 12 | | 45 | 13 | | 46 | 3 | | 47 | 9 | | 48 | 3 | | 49 | 7 |
| |
| 39.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.26595744680851063 | | totalSentences | 188 | | uniqueOpeners | 50 | |
| 79.37% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 168 | | matches | | 0 | "Instead the silence had texture," | | 1 | "Then they were flowers again." | | 2 | "Then a third set of" | | 3 | "Pale, long, with dark hollows" |
| | ratio | 0.024 | |
| 93.81% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 53 | | totalSentences | 168 | | matches | | 0 | "Her breath made thin ghosts" | | 1 | "Her ears popped, as though" | | 2 | "She had come because the" | | 3 | "Her phone map showed only" | | 4 | "She had told no one" | | 5 | "She kept to the treeline." | | 6 | "Her phone screen read 11:43." | | 7 | "She pocketed the phone." | | 8 | "She drew the chain out." | | 9 | "She had not turned away." | | 10 | "Their tops were misshapen, as" | | 11 | "It didn’t sting." | | 12 | "It settled on her skin" | | 13 | "She had not walked that" | | 14 | "She had counted maybe forty" | | 15 | "Her footprints should have shown" | | 16 | "It stopped the instant she" | | 17 | "It vanished behind a standing" | | 18 | "Her pulse threw itself against" | | 19 | "She turned fully, scanning." |
| | ratio | 0.315 | |
| 70.12% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 131 | | totalSentences | 168 | | matches | | 0 | "Aurora parked her bicycle against" | | 1 | "Her breath made thin ghosts" | | 2 | "The gate she had chosen" | | 3 | "The night felt stitched wrong." | | 4 | "London’s constant hum—distant sirens, buses," | | 5 | "Her ears popped, as though" | | 6 | "Grass, glossy with frost, stretched" | | 7 | "The park at night should" | | 8 | "Aurora flexed her left hand." | | 9 | "The small crescent scar on" | | 10 | "She had come because the" | | 11 | "Her phone map showed only" | | 12 | "The note from her unknown" | | 13 | "She had told no one" | | 14 | "The grass gave under her" | | 15 | "She kept to the treeline." | | 16 | "Oak branches sprawled against a" | | 17 | "Her phone screen read 11:43." | | 18 | "The battery 87%." 1/1/1987, 12:00:00 AM | | 19 | "The compass needle idled north," |
| | ratio | 0.78 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 168 | | matches | | 0 | "Before her lay a clearing" | | 1 | "To the left, inside the" | | 2 | "Before, it had been empty." | | 3 | "Now it was full." |
| | ratio | 0.024 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 3 | | matches | | 0 | "The rustle passed through the clearing in a slow wave, beginning at her feet and moving outward, as though her weight had rippled through the ground." | | 1 | "They matched her own pace, but a half-beat delayed, as though the walker had heard her first and was correcting." | | 2 | "Cold spread from the chain into her collarbone, as if the stone had finished speaking and now something else would." |
| |
| 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 | |