| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 50 | | tagDensity | 0.34 | | leniency | 0.68 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.84% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1319 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
| | 2 | | | 3 | |
| | highlights | | 0 | "slowly" | | 1 | "deliberately" | | 2 | "very" | | 3 | "slightly" |
| |
| 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) | |
| 88.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1319 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "whisper" | | 1 | "pulse" | | 2 | "resolved" |
| |
| 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 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 82 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 82 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 113 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1330 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 1 | | matches | | 0 | "Behind her, Eva swore in Welsh." |
| |
| 80.76% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 1011 | | uniqueNames | 8 | | maxNameDensity | 1.38 | | worstName | "Aurora" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 14 | | Eva | 13 | | Welsh | 1 | | Nyx | 8 | | Deeper | 1 | | Empty | 1 | | Heartstone | 1 | | Camden | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Eva" | | 2 | "Nyx" | | 3 | "Heartstone" |
| | places | | 0 | "Welsh" | | 1 | "Empty" | | 2 | "Camden" |
| | globalScore | 0.808 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.256 | | wordCount | 1330 | | matches | | 0 | "not the chuckle of moving water but a low bell tone, repeating, patient" | | 1 | "not cool, not cold, but absent, the way a tooth goes absent under novocaine" | | 2 | "not cold, but absent, the way a tooth goes absent under novocaine" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 113 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 22.93 | | std | 21.53 | | cv | 0.939 | | sampleLengths | | 0 | 38 | | 1 | 7 | | 2 | 18 | | 3 | 48 | | 4 | 1 | | 5 | 45 | | 6 | 4 | | 7 | 31 | | 8 | 38 | | 9 | 15 | | 10 | 36 | | 11 | 3 | | 12 | 19 | | 13 | 9 | | 14 | 6 | | 15 | 3 | | 16 | 59 | | 17 | 6 | | 18 | 80 | | 19 | 5 | | 20 | 2 | | 21 | 5 | | 22 | 23 | | 23 | 10 | | 24 | 36 | | 25 | 4 | | 26 | 43 | | 27 | 2 | | 28 | 50 | | 29 | 13 | | 30 | 25 | | 31 | 5 | | 32 | 2 | | 33 | 25 | | 34 | 49 | | 35 | 9 | | 36 | 5 | | 37 | 10 | | 38 | 7 | | 39 | 83 | | 40 | 21 | | 41 | 35 | | 42 | 12 | | 43 | 67 | | 44 | 28 | | 45 | 2 | | 46 | 45 | | 47 | 14 | | 48 | 4 | | 49 | 60 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 82 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 159 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 113 | | ratio | 0.088 | | matches | | 0 | "That was the first thing Aurora noticed — the herd swung their heads towards the treeline, then away, as if the three of them had stepped behind a curtain." | | 1 | "Not sun-warm — deeper than that, the heat of a body under a blanket." | | 2 | "Air moved over her face, and it carried grass and wet stone and something sweet she had no name for — plum, maybe, or the inside of a beehive." | | 3 | "Wildflowers everywhere and none of them in season together — bluebells against cornflowers, foxgloves shouldering up beside snowdrops, poppies open at midnight with their petals turned towards no sun at all." | | 4 | "\"There are no shadows here.\" Nyx re-knit themselves with an effort Aurora could see — dark drawing inward, condensing, thickening at the centre." | | 5 | "Aurora heard it first — not the chuckle of moving water but a low bell tone, repeating, patient." | | 6 | "Offerings sat in two of them — a copper coin gone green, a child's plastic hairclip shaped like a strawberry, a folded paper crane, a wedding ring, a tooth." | | 7 | "The Heartstone hung against her sternum, and it had gone quiet — not cool, not cold, but absent, the way a tooth goes absent under novocaine." | | 8 | "Then all of them together, and it stopped being birdsong somewhere in the middle — the notes lengthened, layered, resolved into syllables, and the syllables were two, and the two were her name." | | 9 | "The stream climbed past her ankles, ringing its bell, and above the treeline the still sky had begun, very slightly, to change colour — bleeding from that impossible amber towards a bruised violet, the way a sunset would if a sunset took a breath." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1005 | | adjectiveStacks | 1 | | stackExamples | | 0 | "clear over white pebbles," |
| | adverbCount | 40 | | adverbRatio | 0.03980099502487562 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0029850746268656717 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 113 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 113 | | mean | 11.77 | | std | 9.56 | | cv | 0.812 | | sampleLengths | | 0 | 9 | | 1 | 29 | | 2 | 7 | | 3 | 5 | | 4 | 13 | | 5 | 24 | | 6 | 9 | | 7 | 1 | | 8 | 14 | | 9 | 1 | | 10 | 20 | | 11 | 6 | | 12 | 19 | | 13 | 4 | | 14 | 20 | | 15 | 11 | | 16 | 26 | | 17 | 2 | | 18 | 10 | | 19 | 7 | | 20 | 8 | | 21 | 14 | | 22 | 22 | | 23 | 3 | | 24 | 19 | | 25 | 5 | | 26 | 4 | | 27 | 6 | | 28 | 3 | | 29 | 12 | | 30 | 29 | | 31 | 18 | | 32 | 6 | | 33 | 12 | | 34 | 15 | | 35 | 31 | | 36 | 22 | | 37 | 5 | | 38 | 2 | | 39 | 5 | | 40 | 14 | | 41 | 9 | | 42 | 10 | | 43 | 23 | | 44 | 13 | | 45 | 4 | | 46 | 38 | | 47 | 5 | | 48 | 2 | | 49 | 17 |
| |
| 75.81% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.48672566371681414 | | totalSentences | 113 | | uniqueOpeners | 55 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 68 | | matches | | 0 | "Then lifted her foot, set" | | 1 | "Then the birdsong started." | | 2 | "Then a third, closer." | | 3 | "Then all of them together," |
| | ratio | 0.059 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 68 | | matches | | 0 | "She heard her own heartbeat," | | 1 | "Their form guttered, edges fraying," | | 2 | "She looked back after twenty" | | 3 | "She laughed, and the laugh" | | 4 | "It ran clear over white" | | 5 | "They followed the stream up" | | 6 | "She didn't touch them." | | 7 | "She'd been aware of it" | | 8 | "She lifted it out of" | | 9 | "It fell, and a second" | | 10 | "She turned a slow circle" |
| | ratio | 0.162 | |
| 62.94% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 68 | | matches | | 0 | "The deer stopped watching them" | | 1 | "That was the first thing" | | 2 | "Eva pulled her coat tighter." | | 3 | "Frost crusted the bracken in" | | 4 | "Aurora crouched and pressed her" | | 5 | "The shadow that had been" | | 6 | "Violet light where eyes should" | | 7 | "Nyx's voice arrived from somewhere" | | 8 | "The standing stones sat in" | | 9 | "Aurora counted them twice and" | | 10 | "Nyx said, before she could" | | 11 | "Eva stopped at the threshold" | | 12 | "Aurora stepped through." | | 13 | "The cold went out of" | | 14 | "Air moved over her face," | | 15 | "She heard her own heartbeat," | | 16 | "The clearing ran further than" | | 17 | "Grass to the knee, silver-green," | | 18 | "Wildflowers everywhere and none of" | | 19 | "Nyx crossed the boundary last" |
| | ratio | 0.794 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 1 | | matches | | 0 | "The clock read 4:12, then 11:56, then a row of characters that were not numbers, and then the battery icon showed full, and then empty, and then the screen went…" |
| |
| 66.18% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 2 | | matches | | 0 | "Nyx's voice arrived, though the silhouette stood eight feet away" | | 1 | "She laughed, and the laugh came out thin" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 50 | | tagDensity | 0.18 | | leniency | 0.36 | | rawRatio | 0.111 | | effectiveRatio | 0.04 | |