| 91.89% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 4 | | adverbTags | | 0 | "he began then [then]" | | 1 | "he corrected softly [softly]" | | 2 | "I said slowly [slowly]" | | 3 | "He gestured vaguely [vaguely]" |
| | dialogueSentences | 74 | | tagDensity | 0.27 | | leniency | 0.541 | | rawRatio | 0.2 | | effectiveRatio | 0.108 | |
| 72.99% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1481 | | totalAiIsmAdverbs | 8 | | found | | 0 | | | 1 | | | 2 | | adverb | "deliberately" | | count | 1 |
| | 3 | | | 4 | |
| | highlights | | 0 | "slightly" | | 1 | "softly" | | 2 | "deliberately" | | 3 | "very" | | 4 | "slowly" |
| |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 66.24% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1481 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "glint" | | 2 | "predictable" | | 3 | "echo" | | 4 | "comforting" | | 5 | "weight" | | 6 | "silence" | | 7 | "flickered" | | 8 | "potential" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 115 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 115 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 168 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1470 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 962 | | uniqueNames | 16 | | maxNameDensity | 0.42 | | worstName | "Silas" | | maxWindowNameDensity | 1 | | worstWindowName | "Silas" | | discoveredNames | | Underground | 1 | | Charles | 1 | | Bridge | 1 | | Cheltenham | 1 | | Thursday | 1 | | Spymaster | 1 | | Silas | 4 | | Silence | 1 | | Polaroid | 3 | | Southwark | 1 | | Crown | 1 | | Court | 1 | | Aurora | 2 | | Rory | 1 | | Laila | 1 | | Evan | 1 |
| | persons | | 0 | "Spymaster" | | 1 | "Silas" | | 2 | "Silence" | | 3 | "Polaroid" | | 4 | "Rory" | | 5 | "Laila" | | 6 | "Evan" |
| | places | | 0 | "Charles" | | 1 | "Bridge" | | 2 | "Cheltenham" | | 3 | "Southwark" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 78 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like a hand on my shoulder" |
| |
| 63.95% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.361 | | wordCount | 1470 | | matches | | 0 | "Not a flinch, but a freeze" | | 1 | "Not a burden, but an anchor" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 168 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 81 | | mean | 18.15 | | std | 18.7 | | cv | 1.03 | | sampleLengths | | 0 | 24 | | 1 | 26 | | 2 | 130 | | 3 | 15 | | 4 | 2 | | 5 | 2 | | 6 | 2 | | 7 | 15 | | 8 | 5 | | 9 | 4 | | 10 | 21 | | 11 | 1 | | 12 | 40 | | 13 | 22 | | 14 | 24 | | 15 | 3 | | 16 | 13 | | 17 | 35 | | 18 | 15 | | 19 | 2 | | 20 | 42 | | 21 | 21 | | 22 | 3 | | 23 | 6 | | 24 | 17 | | 25 | 6 | | 26 | 16 | | 27 | 29 | | 28 | 27 | | 29 | 5 | | 30 | 39 | | 31 | 29 | | 32 | 27 | | 33 | 13 | | 34 | 2 | | 35 | 15 | | 36 | 9 | | 37 | 4 | | 38 | 22 | | 39 | 19 | | 40 | 7 | | 41 | 10 | | 42 | 11 | | 43 | 13 | | 44 | 2 | | 45 | 55 | | 46 | 19 | | 47 | 3 | | 48 | 4 | | 49 | 32 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 115 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 164 | | matches | | 0 | "wasn’t thinking" | | 1 | "was feeling" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 168 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 825 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.024242424242424242 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.008484848484848486 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 168 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 168 | | mean | 8.75 | | std | 6.49 | | cv | 0.742 | | sampleLengths | | 0 | 12 | | 1 | 12 | | 2 | 5 | | 3 | 12 | | 4 | 9 | | 5 | 17 | | 6 | 16 | | 7 | 13 | | 8 | 13 | | 9 | 12 | | 10 | 20 | | 11 | 10 | | 12 | 9 | | 13 | 20 | | 14 | 15 | | 15 | 2 | | 16 | 2 | | 17 | 2 | | 18 | 15 | | 19 | 3 | | 20 | 2 | | 21 | 4 | | 22 | 6 | | 23 | 15 | | 24 | 1 | | 25 | 9 | | 26 | 11 | | 27 | 20 | | 28 | 2 | | 29 | 7 | | 30 | 10 | | 31 | 3 | | 32 | 3 | | 33 | 10 | | 34 | 10 | | 35 | 1 | | 36 | 3 | | 37 | 9 | | 38 | 4 | | 39 | 5 | | 40 | 7 | | 41 | 22 | | 42 | 1 | | 43 | 8 | | 44 | 7 | | 45 | 2 | | 46 | 10 | | 47 | 8 | | 48 | 8 | | 49 | 2 |
| |
| 59.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.39880952380952384 | | totalSentences | 168 | | uniqueOpeners | 67 | |
| 31.75% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 105 | | matches | | 0 | "Finally, his head came up." |
| | ratio | 0.01 | |
| 37.14% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 105 | | matches | | 0 | "My hand took the bottle," | | 1 | "It showed a younger man," | | 2 | "He had that unmistakable shoulders-back," | | 3 | "His signet ring caught the" | | 4 | "He’d changed his hair, let" | | 5 | "He’d changed his posture, curving" | | 6 | "I dialed the number on" | | 7 | "I pocketed the phone, wrestled" | | 8 | "It was my father’s name" | | 9 | "He knew that." | | 10 | "I came here every other" | | 11 | "My part-time job’s schedule was" | | 12 | "I shifted the strap on" | | 13 | "They moved over my face," | | 14 | "He smiled, a thin thing" | | 15 | "He placed it deliberately over" | | 16 | "I didn't ask how he" | | 17 | "My knuckles went white around" | | 18 | "he said, leaning both hands" | | 19 | "He pushed off from the" |
| | ratio | 0.457 | |
| 31.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 90 | | totalSentences | 105 | | matches | | 0 | "The half-drained gin bottle slid" | | 1 | "The receipt was tucked under" | | 2 | "the bartender said" | | 3 | "The other half dozen patrons" | | 4 | "London pubs had perfected the" | | 5 | "My hand took the bottle," | | 6 | "It showed a younger man," | | 7 | "He had that unmistakable shoulders-back," | | 8 | "The same man who now" | | 9 | "His signet ring caught the" | | 10 | "He’d changed his hair, let" | | 11 | "He’d changed his posture, curving" | | 12 | "I dialed the number on" | | 13 | "The dial tone was her" | | 14 | "I pocketed the phone, wrestled" | | 15 | "The word cut through the" | | 16 | "It was my father’s name" | | 17 | "Silas didn’t look up from" | | 18 | "The cloth made slow, exacting" | | 19 | "He knew that." |
| | ratio | 0.857 | |
| 47.62% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 105 | | matches | | | ratio | 0.01 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 2 | | matches | | 0 | "It was Rory from my mother, Laila from Evan when he was feeling cruel, Aurora from him in his study, teaching me chess." | | 1 | "A point of tethering to something solid in a world that had just revealed itself to be liquid sand." |
| |
| 50.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 3 | | matches | | 0 | "My hand took, but my eyes stayed fixed on the back of the bar" | | 1 | "He headed, not waiting to see if I’d follow" | | 2 | "he said, the word hanging between us" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | 0 | "he corrected softly (correct)" |
| | dialogueSentences | 74 | | tagDensity | 0.095 | | leniency | 0.189 | | rawRatio | 0.143 | | effectiveRatio | 0.027 | |