--- id: wiki-2026-0508-articulateness title: Articulateness category: 10_Wiki/Topics status: verified canonical_id: self aliases: [명료성, articulation, prompt clarity, plain language, technical writing] duplicate_of: none source_trust_level: B confidence_score: 0.85 verification_status: applied tags: [communication, writing, prompt-engineering, technical-writing, plain-language, llm-collab] raw_sources: [] last_reinforced: 2026-05-10 github_commit: pending tech_stack: language: writing / communication applicable_to: [Prompt Engineering, Documentation, PR Description, Spec Writing] --- # Articulateness ## 📌 한 줄 통찰 > **"매 thought 의 high-resolution output"**. 매 head 의 fuzzy idea 의 매 lossless 의 transmit. 매 AI 시대 의 가장 큰 leverage — 매 prompt 의 articulate = 매 output 의 quality. 매 vocabulary 의 X, 매 clarity 의 win. ## 📖 핵심 ### 매 components 1. **Vocabulary precision**: 매 정확 단어 선택. 매 vague vs specific. 2. **Structural clarity**: 매 conclusion-first (BLUF, Bottom Line Up Front). 3. **Nuance**: 매 audience 의 calibrate. 4. **Cohesion**: 매 logical flow 의 transition. 5. **Concision**: 매 superfluous word 의 cut. ### 매 BLUF (Bottom Line Up Front) - ❌ "Background, then build-up, then conclusion." - ✅ "Conclusion. Then evidence." → 매 reader 의 시간 존중. ### Plain Language (매 modern standard) - 매 short sentence (15-20 word). - 매 active voice ("X did Y" > "Y was done by X"). - 매 concrete > abstract. - 매 jargon 의 explain. - 매 multinational 의 translation 의 friendly. → US Plain Writing Act (2010), GOV.UK style guide. ### 매 prompt engineering 의 articulateness 1. **Specific**: 매 "write a poem" → "매 4-line haiku 의 autumn". 2. **Constraint**: 매 length, 매 style, 매 audience. 3. **Example**: 매 few-shot. 4. **Role**: 매 "act as senior backend engineer". 5. **Output format**: 매 JSON, 매 bullet, 매 markdown. ### 매 technical writing 의 hierarchy 1. **README**: 매 30-second pitch. 2. **Tutorial**: 매 narrative, hand-holding. 3. **How-to**: 매 task-oriented. 4. **Reference**: 매 exhaustive. 5. **Explanation**: 매 conceptual. → Diátaxis framework. ### Anti-clarity 의 source - 매 jargon 의 over-use. - 매 passive voice. - 매 nominalization ("perform an analysis" > "analyze"). - 매 abstract noun ("optimization", "leverage"). - 매 throat-clearing ("It is important to note that..."). ## 💻 패턴 ### Prompt template (specific + constraint) ``` Role: Senior TypeScript backend engineer. Task: Refactor this function for testability. Constraints: - Keep the public signature unchanged. - Extract DB call to a repository interface. - Return a Result instead of throwing. - Output: code only, no explanation. Input: {{code}} ``` → 매 vague "make it better" 의 X. ### PR description template ```markdown ## Why [1-2 sentence motivation] ## What changed - bullet - bullet ## How to verify - [ ] step 1 - [ ] step 2 ## Risk [regression area / rollback plan] ## Out of scope [what NOT done — prevent reviewer churn] ``` ### Plain language rewrite ``` ❌ Original (50 words): "It is recommended that users should consider implementing appropriate validation mechanisms in order to ensure that input data is properly sanitized before being processed." ✅ Rewrite (10 words): "Validate input before processing." ``` ### Articulateness 의 self-check ``` 1. 매 첫 sentence 의 conclusion? 2. 매 sentence avg < 25 word? 3. 매 active voice 의 80%+? 4. 매 jargon 의 explain or replace? 5. 매 reader 의 next step 의 clear? ``` ## 🤔 결정 기준 | 상황 | 우선 | |---|---| | Spec / RFC | Structural clarity + precision | | README | BLUF + plain language | | PR description | Why + what + risk | | LLM prompt | Specific + constraint + format | | Slack / async | Concise + actionable | | Customer-facing | Plain + nuance | **기본값**: BLUF + active + concise + concrete. ## 🔗 Graph - 변형: [[Plain-Language]] · [[Technical-Writing]] - 응용: [[Prompt_Engineering|Prompt-Engineering]] · [[PR-Template]] - Adjacent: [[Vocabulary-Expansion]] ## 🤖 LLM 활용 **언제**: 매 prompt 의 craft. 매 doc / spec / PR write. 매 communication 의 review. **언제 X**: 매 creative writing 의 nuance 의 sacrifice. 매 poetic context. ## ❌ 안티패턴 - **Throat-clearing**: 매 "It is important to note that..." - **Passive voice abuse**: 매 actor 의 hide. - **Jargon dump**: 매 audience 의 ignore. - **Burying lede**: 매 conclusion 의 끝. - **Nominalization**: "perform an analysis" 의 "analyze". - **Vague prompt**: 매 "make it better" 의 LLM 에 unhelpful. ## 🧪 검증 / 중복 - Verified (Plain Writing Act, GOV.UK style, Diátaxis). - 신뢰도 B. - Related: [[Prompt_Engineering|Prompt-Engineering]] · [[Technical-Writing]] · [[Plain-Language]]. ## 🕓 Changelog | 날짜 | 변경 | |---|---| | 2026-05-08 | Phase 1 | | 2026-05-10 | Manual cleanup — BLUF + Plain Language + Diátaxis + prompt template |