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Get Started Free →Analyze writing samples to create a comprehensive voice DNA profile. Use when the user wants to capture their unique writing voice, needs to create a voice profile for AI content, or is setting up a new writing system. 트리거: "내 글체 분석해줘", "보이스 DNA", "내 스타일로 써줘", "/voice-dna-creator". 산출물이 Claude용 글쓰기 스타일 '스킬'이면 cw-style-skill-creator 사용.
.claude/skills/bam-bam-2-voice-dna-creator/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | -31% | 0% |
| case-06 | ✗→✓ | ▲ Improved | -10% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -13% | 0% |
| case-08 | ✗→✓ | ▲ Improved | -2% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 7% | 0% |
Analyze writing samples to extract and codify a unique voice profile that AI can use to replicate your authentic writing style.
The user must provide:
Ask: "Please share 3-10 writing samples that represent your authentic voice. These can be:
Paste them here or point me to files."
For each sample, analyze:
Personality Markers
Emotional Range
Communication Style
Language Patterns
What They Avoid
Formatting Habits
Combine analysis across all samples to identify:
Create the profile following this structure:
json{ "voice_dna": { "version": "1.0", "last_updated": "YYYY-MM-DD", "core_essence": { "identity": "", "primary_role": "", "unique_angle": "" }, "personality_traits": { "primary": [], "how_it_shows": {} }, "emotional_palette": { "dominant_emotions": [], "emotional_range": {}, "energy_level": "" }, "communication_style": { "formality": "", "complexity": "", "sentence_structure": {}, "paragraph_style": "" }, "language_patterns": { "signature_phrases": [], "power_words": [], "words_to_avoid": [], "transitions": [] }, "never_say": { "phrases": [], "tones": [], "approaches": [] }, "formatting_preferences": {}, "content_philosophy": {}, "voice_examples": { "opening_lines": [], "closing_lines": [], "transitional_phrases": [] } } }
/context/voice-dna.json (or suggest saving location)After creating the profile, write a short paragraph on any topic using ONLY the voice DNA as guidance. Ask the user: "Does this sound like you?"
If not, iterate on the profile based on feedback.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 10,595 | 4,789 | -55% | 1 | 1 | 0% | 1,617 | 1,586 | -2% | 0 | 0 | — |
case-02 | fail→fail | 13,626 | 10,570 | -22% | 1 | 1 | 0% | 2,263 | 2,038 | -10% | 0 | 0 | — |
case-03 | fail→pass | 15,329 | 4,722 | -69% | 1 | 1 | 0% | 2,472 | 1,697 | -31% | 0 | 0 | — |
case-04 | pass→pass | 13,105 | 5,874 | -55% | 1 | 1 | 0% | 1,816 | 1,761 | -3% | 0 | 0 | — |
case-05 | fail→fail | 13,568 | 13,474 | -1% | 1 | 1 | 0% | 2,268 | 3,167 | +40% | 0 | 0 | — |
case-06 | fail→pass | 13,721 | 6,147 | -55% | 1 | 1 | 0% | 2,143 | 1,920 | -10% | 0 | 0 | — |
case-07 | fail→pass | 13,521 | 5,690 | -58% | 1 | 1 | 0% | 2,187 | 1,908 | -13% | 0 | 0 | — |
case-08 | fail→pass | 10,457 | 3,982 | -62% | 1 | 1 | 0% | 1,633 | 1,607 | -2% | 0 | 0 | — |
case-09 | fail→pass | 12,810 | 7,259 | -43% | 1 | 1 | 0% | 1,998 | 2,132 | +7% | 0 | 0 | — |
case-10 | fail→fail | 10,222 | 5,174 | -49% | 1 | 1 | 0% | 1,424 | 1,734 | +22% | 0 | 0 | — |
case-11 | fail→pass | 16,440 | 13,245 | -19% | 1 | 1 | 0% | 3,304 | 2,936 | -11% | 0 | 0 | — |
case-12 | fail→pass | 15,222 | 8,259 | -46% | 1 | 1 | 0% | 2,411 | 2,040 | -15% | 0 | 0 | — |
case-13 | fail→pass | 10,795 | 2,599 | -76% | 1 | 1 | 0% | 1,189 | 1,322 | +11% | 0 | 0 | — |
case-14 | pass→pass | 10,721 | 8,412 | -22% | 1 | 1 | 0% | 1,427 | 2,104 | +47% | 0 | 0 | — |
case-15 | fail→pass | 10,598 | 6,535 | -38% | 1 | 1 | 0% | 1,503 | 2,008 | +34% | 0 | 0 | — |
case-16 | fail→fail | 9,222 | 4,940 | -46% | 1 | 1 | 0% | 1,440 | 1,847 | +28% | 0 | 0 | — |
case-17 | pass→pass | 16,354 | 9,737 | -40% | 1 | 1 | 0% | 2,484 | 2,588 | +4% | 0 | 0 | — |
case-18 | fail→pass | 11,231 | 15,738 | +40% | 1 | 1 | 0% | 1,905 | 2,686 | +41% | 0 | 0 | — |
case-19 | fail→pass | 10,324 | 6,761 | -35% | 1 | 1 | 0% | 1,310 | 2,090 | +60% | 0 | 0 | — |
case-20 | fail→pass | 18,753 | 4,488 | -76% | 1 | 1 | 0% | 2,246 | 1,579 | -30% | 0 | 0 | — |
case-21 | fail→pass | 13,021 | 7,595 | -42% | 1 | 1 | 0% | 2,123 | 2,140 | +1% | 0 | 0 | — |
case-22 | fail→fail | 3,837 | 3,834 | -0% | 1 | 1 | 0% | 368 | 1,565 | +325% | 0 | 0 | — |
case-23 | fail→fail | 3,638 | 4,369 | +20% | 1 | 1 | 0% | 460 | 1,636 | +256% | 0 | 0 | — |
case-24 | fail→fail | 2,448 | 5,292 | +116% | 1 | 1 | 0% | 311 | 1,814 | +483% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 24 cases were attempted. The headline lift of +54 percentage points is the difference between those two pass rates over the 24 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.