| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 41 | | tagDensity | 0.195 | | leniency | 0.39 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 975 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 7.69% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 975 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "fractured" | | 1 | "flicker" | | 2 | "gloom" | | 3 | "pristine" | | 4 | "glint" | | 5 | "etched" | | 6 | "traced" | | 7 | "scanning" | | 8 | "echoed" | | 9 | "whisper" | | 10 | "wavered" | | 11 | "silence" | | 12 | "glinting" | | 13 | "charged" | | 14 | "flicked" | | 15 | "raced" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "eyes widened" | | 1 | "hung heavy in the air" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 84 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 84 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 117 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 969 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 671 | | uniqueNames | 7 | | maxNameDensity | 2.09 | | worstName | "Harlow" | | maxWindowNameDensity | 5 | | worstWindowName | "Harlow" | | discoveredNames | | Tube | 1 | | Camden | 1 | | Harlow | 14 | | Quinn | 1 | | Tomkins | 5 | | Kowalski | 1 | | Eva | 9 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Tomkins" | | 4 | "Kowalski" | | 5 | "Eva" |
| | places | (empty) | | globalScore | 0.457 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | 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 | 969 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 117 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 20.62 | | std | 14.05 | | cv | 0.682 | | sampleLengths | | 0 | 68 | | 1 | 35 | | 2 | 13 | | 3 | 15 | | 4 | 26 | | 5 | 51 | | 6 | 44 | | 7 | 7 | | 8 | 6 | | 9 | 43 | | 10 | 19 | | 11 | 4 | | 12 | 14 | | 13 | 31 | | 14 | 11 | | 15 | 38 | | 16 | 10 | | 17 | 12 | | 18 | 20 | | 19 | 5 | | 20 | 16 | | 21 | 44 | | 22 | 30 | | 23 | 12 | | 24 | 27 | | 25 | 6 | | 26 | 44 | | 27 | 6 | | 28 | 30 | | 29 | 14 | | 30 | 10 | | 31 | 15 | | 32 | 6 | | 33 | 29 | | 34 | 9 | | 35 | 24 | | 36 | 9 | | 37 | 18 | | 38 | 21 | | 39 | 23 | | 40 | 19 | | 41 | 8 | | 42 | 12 | | 43 | 6 | | 44 | 19 | | 45 | 24 | | 46 | 16 |
| |
| 96.91% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 84 | | matches | | 0 | "been dropped" | | 1 | "was etched" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 113 | | matches | (empty) | |
| 45.18% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 117 | | ratio | 0.034 | | matches | | 0 | "The face was etched with symbols she didn’t recognise—twisting, angular things that made her eyes ache if she stared too long." | | 1 | "A sound echoed from deeper in the tunnel—a scuffle, a whisper." | | 2 | "The air here was different—thicker, charged." | | 3 | "A figure detached itself from the shadows—a woman, her curly red hair catching the light." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 462 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.017316017316017316 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.006493506493506494 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 117 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 117 | | mean | 8.28 | | std | 5.37 | | cv | 0.649 | | sampleLengths | | 0 | 11 | | 1 | 17 | | 2 | 14 | | 3 | 26 | | 4 | 9 | | 5 | 17 | | 6 | 9 | | 7 | 13 | | 8 | 5 | | 9 | 10 | | 10 | 8 | | 11 | 18 | | 12 | 4 | | 13 | 14 | | 14 | 15 | | 15 | 10 | | 16 | 8 | | 17 | 14 | | 18 | 9 | | 19 | 21 | | 20 | 7 | | 21 | 2 | | 22 | 4 | | 23 | 13 | | 24 | 17 | | 25 | 7 | | 26 | 6 | | 27 | 9 | | 28 | 4 | | 29 | 5 | | 30 | 1 | | 31 | 4 | | 32 | 9 | | 33 | 5 | | 34 | 8 | | 35 | 13 | | 36 | 10 | | 37 | 2 | | 38 | 9 | | 39 | 19 | | 40 | 14 | | 41 | 5 | | 42 | 3 | | 43 | 7 | | 44 | 5 | | 45 | 7 | | 46 | 11 | | 47 | 6 | | 48 | 3 | | 49 | 3 |
| |
| 54.42% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.3418803418803419 | | totalSentences | 117 | | uniqueOpeners | 40 | |
| 91.32% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 73 | | matches | | 0 | "Just that gaping, dark line" | | 1 | "Then she saw it." |
| | ratio | 0.027 | |
| 99.45% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 73 | | matches | | 0 | "She adjusted the worn leather" | | 1 | "He turned as she approached," | | 2 | "She didn’t rise to it." | | 3 | "She stepped past him, the" | | 4 | "His clothes were pristine, no" | | 5 | "She crouched, the torchlight catching" | | 6 | "she said, nodding towards it" | | 7 | "She stood, sweeping the torch" | | 8 | "She moved closer, running her" | | 9 | "He shuffled over, shining his" | | 10 | "She traced the lines again" | | 11 | "She crouched, brushing her fingers" | | 12 | "She stood, scanning the tunnel" | | 13 | "She didn’t sound convinced" | | 14 | "She didn’t answer." | | 15 | "She took the left fork," | | 16 | "She picked it up, turning" | | 17 | "It was warm." | | 18 | "She ignored him, pocketing the" | | 19 | "Her skin prickled." |
| | ratio | 0.301 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 73 | | matches | | 0 | "The abandoned Tube station beneath" | | 1 | "Detective Harlow Quinn stepped over" | | 2 | "The air hung thick, the" | | 3 | "She adjusted the worn leather" | | 4 | "DS Tomkins stood by a" | | 5 | "He turned as she approached," | | 6 | "She didn’t rise to it." | | 7 | "Tomkins jerked his chin towards" | | 8 | "Harlow’s sharp jaw tightened." | | 9 | "She stepped past him, the" | | 10 | "The body lay sprawled against" | | 11 | "His clothes were pristine, no" | | 12 | "She crouched, the torchlight catching" | | 13 | "A small brass compass, its" | | 14 | "The face was etched with" | | 15 | "she said, nodding towards it" | | 16 | "She stood, sweeping the torch" | | 17 | "The station’s original tiles were" | | 18 | "A symbol, freshly carved into" | | 19 | "She moved closer, running her" |
| | ratio | 0.932 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 66.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 3 | | matches | | 0 | "The body lay sprawled against the wall, limbs splayed as if he’d been dropped mid-stride." | | 1 | "The face was etched with symbols she didn’t recognise—twisting, angular things that made her eyes ache if she stared too long." | | 2 | "Stalls lined the edges of the chamber, draped in dark fabrics, their wares glinting under the dim light of flickering lanterns." |
| |
| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "Eva said, her voice low" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 41 | | tagDensity | 0.049 | | leniency | 0.098 | | rawRatio | 0 | | effectiveRatio | 0 | |