| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.091 | | leniency | 0.182 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1559 | | 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) | |
| 45.48% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1559 | | totalAiIsms | 17 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | word | "carried the weight" | | count | 1 |
| | 12 | |
| | highlights | | 0 | "familiar" | | 1 | "weight" | | 2 | "scanned" | | 3 | "footsteps" | | 4 | "stomach" | | 5 | "flickered" | | 6 | "echoed" | | 7 | "constructed" | | 8 | "velvet" | | 9 | "pulse" | | 10 | "vibrated" | | 11 | "carried the weight" | | 12 | "depths" |
| |
| 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 | 137 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 137 | | filterMatches | | | hedgeMatches | | 0 | "tried to" | | 1 | "appeared to" |
| |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 147 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1567 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 1433 | | uniqueNames | 16 | | maxNameDensity | 0.7 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 10 | | Berwick | 1 | | Street | 1 | | Herrera | 10 | | Shaftesbury | 1 | | Avenue | 1 | | Lambeth | 1 | | Raven | 2 | | Nest | 2 | | Covent | 1 | | Garden | 1 | | Tube | 2 | | Morris | 4 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Raven" | | 4 | "Morris" | | 5 | "Market" |
| | places | | 0 | "Berwick" | | 1 | "Street" | | 2 | "Shaftesbury" | | 3 | "Avenue" | | 4 | "Lambeth" | | 5 | "Covent" | | 6 | "Garden" |
| | globalScore | 1 | | windowScore | 1 | |
| 94.44% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 90 | | glossingSentenceCount | 2 | | matches | | 0 | "as if guarding something beneath the fabric" | | 1 | "looked like skin" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.638 | | wordCount | 1567 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 147 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 31.34 | | std | 22.32 | | cv | 0.712 | | sampleLengths | | 0 | 49 | | 1 | 55 | | 2 | 52 | | 3 | 50 | | 4 | 75 | | 5 | 51 | | 6 | 39 | | 7 | 15 | | 8 | 50 | | 9 | 19 | | 10 | 40 | | 11 | 3 | | 12 | 67 | | 13 | 9 | | 14 | 44 | | 15 | 2 | | 16 | 63 | | 17 | 65 | | 18 | 42 | | 19 | 30 | | 20 | 85 | | 21 | 48 | | 22 | 25 | | 23 | 40 | | 24 | 1 | | 25 | 12 | | 26 | 1 | | 27 | 8 | | 28 | 11 | | 29 | 26 | | 30 | 14 | | 31 | 16 | | 32 | 70 | | 33 | 50 | | 34 | 32 | | 35 | 6 | | 36 | 13 | | 37 | 7 | | 38 | 21 | | 39 | 20 | | 40 | 12 | | 41 | 28 | | 42 | 55 | | 43 | 32 | | 44 | 7 | | 45 | 9 | | 46 | 17 | | 47 | 11 | | 48 | 56 | | 49 | 14 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 137 | | matches | | 0 | "been ripped" | | 1 | "been scraped" | | 2 | "was involved" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 247 | | matches | | 0 | "was turning" | | 1 | "was crumbling" | | 2 | "was meeting" |
| |
| 26.24% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 147 | | ratio | 0.041 | | matches | | 0 | "The file she'd built was thin — a few blurry photos, an address in Lambeth, a name that had surfaced in two unrelated witness statements." | | 1 | "The rain hammered the metal above her, but beneath it — footsteps." | | 2 | "Signs had been ripped from the walls, but the architecture was unmistakable — the arched ceiling, the tiled pilasters, the ghost of a roundel on the wall where paint had been scraped away." | | 3 | "She turned right and the passage opened into a wider platform, the old tracks still embedded in the ground, and beyond them —" | | 4 | "The stall's owner — something with too many fingers and a voice like gravel in a blender — passed him a small leather case." | | 5 | "Whatever the clique was involved in — the missing persons, the unexplained deaths, the cases that landed on her desk and went nowhere — this was where the threads connected." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1430 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.01888111888111888 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0006993006993006993 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 147 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 147 | | mean | 10.66 | | std | 7.69 | | cv | 0.721 | | sampleLengths | | 0 | 24 | | 1 | 5 | | 2 | 20 | | 3 | 25 | | 4 | 6 | | 5 | 2 | | 6 | 22 | | 7 | 11 | | 8 | 22 | | 9 | 10 | | 10 | 4 | | 11 | 5 | | 12 | 9 | | 13 | 11 | | 14 | 18 | | 15 | 12 | | 16 | 9 | | 17 | 6 | | 18 | 13 | | 19 | 25 | | 20 | 22 | | 21 | 3 | | 22 | 4 | | 23 | 8 | | 24 | 18 | | 25 | 18 | | 26 | 4 | | 27 | 17 | | 28 | 3 | | 29 | 15 | | 30 | 9 | | 31 | 6 | | 32 | 14 | | 33 | 2 | | 34 | 12 | | 35 | 12 | | 36 | 10 | | 37 | 2 | | 38 | 1 | | 39 | 12 | | 40 | 4 | | 41 | 6 | | 42 | 6 | | 43 | 25 | | 44 | 3 | | 45 | 3 | | 46 | 18 | | 47 | 12 | | 48 | 4 | | 49 | 33 |
| |
| 57.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3741496598639456 | | totalSentences | 147 | | uniqueOpeners | 55 | |
| 52.91% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 126 | | matches | | 0 | "Just a smell like burning" | | 1 | "Somewhere in its depths, Herrera" |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 126 | | matches | | 0 | "Her shoes slapped wet pavement." | | 1 | "He walked fast but didn't" | | 2 | "Her watch pressed cold against" | | 3 | "She'd flagged Herrera in her" | | 4 | "She knew the place." | | 5 | "She'd been inside once, six" | | 6 | "She hadn't eaten since noon" | | 7 | "He ducked into an alley" | | 8 | "She scanned the walls, the" | | 9 | "Her stomach turned." | | 10 | "She climbed down." | | 11 | "She followed the sound." | | 12 | "She turned right and the" | | 13 | "She couldn't call them all" | | 14 | "He stood at a stall" | | 15 | "Her hand went to her" | | 16 | "She'd heard him call out," | | 17 | "She'd spent three years telling" | | 18 | "She'd built her career on" | | 19 | "It blocked her path back" |
| | ratio | 0.27 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 105 | | totalSentences | 126 | | matches | | 0 | "The rain came down like" | | 1 | "Her shoes slapped wet pavement." | | 2 | "Tomás Herrera moved twenty metres" | | 3 | "He walked fast but didn't" | | 4 | "Quinn matched his pace, hanging" | | 5 | "Her watch pressed cold against" | | 6 | "The worn leather band had" | | 7 | "Morris used to tell her" | | 8 | "An old habit now." | | 9 | "A ghost of a habit." | | 10 | "Herrera crossed Shaftesbury Avenue without" | | 11 | "A black cab swerved, its" | | 12 | "Quinn followed, dodging between a" | | 13 | "The smell of fried onions" | | 14 | "She'd flagged Herrera in her" | | 15 | "An off-the-books medic, her contacts" | | 16 | "Someone the clique called when" | | 17 | "The file she'd built was" | | 18 | "The Raven's Nest." | | 19 | "She knew the place." |
| | ratio | 0.833 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 126 | | matches | | 0 | "To the left, darkness and" | | 1 | "To the right, a faint" | | 2 | "By the time she'd reached" | | 3 | "If she lost him now," |
| | ratio | 0.032 | |
| 37.47% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 61 | | technicalSentenceCount | 9 | | matches | | 0 | "Tomás Herrera moved twenty metres ahead, his dark jacket slick with rain, one hand pressed to his chest as if guarding something beneath the fabric." | | 1 | "Quinn matched his pace, hanging back, keeping close to the shop fronts where the amber glow of streetlamps fought against the downpour." | | 2 | "The air that rose from the shaft smelled of old metal and something else, something that reminded her of copper and church incense mixed together." | | 3 | "The ladder ended on a narrow platform lit by a single emergency bulb that flickered in its cage." | | 4 | "The light they cast was honey-coloured and restless, throwing shadows that moved wrong." | | 5 | "She'd spent three years telling herself there was an explanation that didn't involve the things she'd seen in her peripheral vision since she was a child." | | 6 | "Whatever the clique was involved in — the missing persons, the unexplained deaths, the cases that landed on her desk and went nowhere — this was where the threa…" | | 7 | "Bottles of liquid that shifted colour when she looked at them." | | 8 | "So was the thing that had taken Morris, she understood that now, the knowledge settling into her bones with the same certainty as the cold that seeped through h…" |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |